It did get me thinking about something much bigger than the Census itself though: why are we so obsessed with digitising every single piece of government infrastructure? There seems to be this automatic assumption now that digital means better. Digital means faster, cheaper, more efficient and more modern. Except sometimes it doesn’t. Sometimes we’ve taken something incredibly simple, built an enormous technological system around it, spent an obscene amount of money doing so, introduced cybersecurity risks that didn’t previously exist and somehow made the experience more annoying.

The Census is probably one of the best examples of this because it operates at a completely ridiculous scale. Australia has roughly 27 million people, and the entire purpose of the Census is to create a statistical snapshot of basically all of us. Obviously that doesn’t mean 27 million people simultaneously opening a browser at 7:03pm and attacking the ABS servers. People complete it at different times, households submit information together, some people use paper forms, some people do it early and others presumably forget until someone reminds them.

But even after accounting for all of that, you’re still potentially dealing with millions of Australians interacting with the same government service over a relatively concentrated period. That’s not a normal website anymore. That’s a major infrastructure problem.

The Census Is Basically One Giant Traffic Spike

From a technical perspective, I actually find the whole thing fascinating. You need infrastructure capable of scaling rapidly, load balancing, databases that can deal with enormous spikes in activity, redundancy, monitoring, backups, disaster recovery and enough cybersecurity protection to deal with whatever nonsense people inevitably decide to throw at a major government system while the entire country is using it.

The particularly strange thing about the Census is that you’re designing all of that around an event that happens once every five years. Most websites can provision infrastructure around relatively predictable traffic patterns and then leave some breathing room for unexpected spikes. The Census is different because the event itself is essentially one enormous national traffic spike. You know it’s coming, you know roughly when it’s coming and you know millions of people are going to pile into the same system around the same time.

Modern cloud infrastructure obviously makes this considerably more manageable than it would have been twenty years ago. Elastic computing exists specifically because throwing more capacity at temporary demand is a solvable problem. But that doesn’t make the engineering, security, testing and procurement around the system trivial. If anything, the fact that this is government infrastructure collecting incredibly sensitive information makes the requirements considerably more complicated.

And because we’re talking about government procurement, I can only imagine the number of zeroes involved. I would have loved to be the contractor that got that job.

This is where I start committing technological heresy, because despite building software for a living and generally believing that technology can make almost everything better, I genuinely think there are situations where the government should just use paper.

Not exclusively. I’m not suggesting we burn down AWS, purchase 27 million HB pencils and return Australia to 1973. But somewhere along the way we’ve started treating analogue systems as inherently outdated rather than recognising that analogue and digital systems have completely different strengths and weaknesses.

Paper has one particularly wonderful built-in feature: it doesn’t go offline because six million people are using paper at the same time. My Census form doesn’t suddenly display a 503 because someone in Perth is also holding a pen. There’s no database connection to time out, no JavaScript bundle refusing to load and no national authentication service deciding that tonight would be a fantastic evening for an existential crisis.

Of course, paper creates an entirely different set of problems. Someone has to distribute it, collect it, scan it, process it, store it and eventually transform millions of handwritten answers into useful structured data. That isn’t cheap or easy either. But that’s why I don’t think the answer should necessarily be paper or digital. It should be both, and both should be treated as genuine ways of completing the Census rather than one being the modern system and the other being the backup for people who haven’t discovered computers yet.

A hybrid system also distributes risk. Which brings me to the part of the Census that is considerably more uncomfortable.

This Is an Absolutely Delicious Database to Hack

Think about the information contained in an individual Census response. Not the nice aggregated statistics that eventually appear on the ABS website. I mean the actual information Australians submit.

Your name, age, address, household, relationships, employment, education, ancestry, religion, income range, health circumstances and family structure can all form part of an extraordinarily detailed picture of a person and the people they live with. From a statistical perspective, that information is incredible. From a cybersecurity perspective, it is the sort of database that makes me slightly uncomfortable knowing it exists at all.

Before someone interprets that as me saying the Census has been hacked, I’m not. I have seen no evidence that Census responses have been leaked, compromised or stolen. But the risk inherent in collecting enormous quantities of sensitive information is still something worth talking about. Any sufficiently valuable centralised collection of information becomes an attractive target, and Australia doesn’t exactly have a spotless recent history when it comes to organisations holding gigantic amounts of personal information.

Imagine, purely hypothetically, the catastrophe if raw Census responses were ever compromised. It would be an absolutely monumental mess. Horrifying, obviously, but also almost comically Australian. “Yeah, sorry everyone. Remember that legally required national survey where we asked you to describe basically your entire household? Funny story...”

That is one of the fundamental trade-offs of centralising information. Centralisation makes data incredibly useful because you can analyse everything together, but it also makes whatever is holding that information incredibly valuable. The bigger and more comprehensive the dataset becomes, the more catastrophic a serious breach potentially becomes.

There is actually something funny about comparing this with snail mail. Physical information absolutely isn’t secure by default. Someone can steal your mail, intercept a form, break into an office or access records they shouldn’t. But physical theft has a scaling problem. If you want to steal ten million paper Census forms, you’re going to need a fairly impressive van.

Digital information doesn’t have that limitation. A sufficiently serious compromise can potentially expose enormous quantities of information at once. That’s one of the strange things about our transition towards digital infrastructure: we’ve massively improved accessibility, processing speed and analytical capability while simultaneously inventing entirely new categories of catastrophic failure.

Unfortunately, I Absolutely Love Census Data

This is where my moral high ground completely collapses, because despite everything I’ve just written, I freakin’ love Census data.

I use it constantly.

Once all of those individual responses have been processed, protected and turned into aggregated statistical datasets, the Census becomes an extraordinary resource for understanding Australia. You can analyse demographics, population movements, household structures, employment, education, age distributions, housing, income, cultural backgrounds and the differences between completely different parts of the country.

This isn’t just interesting trivia either. It can genuinely improve decision-making. If an area suddenly has significantly more young families living in it, infrastructure requirements are going to change. If another region is ageing rapidly, healthcare requirements are going to change. If Australia’s population is gradually migrating from one part of the country towards another, housing, transport, schools, hospitals and public services eventually need to follow them.

Good government requires good information. Otherwise we’re effectively allocating billions of dollars based on vibes, and while that occasionally appears to be our existing economic policy, I’d rather we didn’t formalise it.

The slightly awkward part is that I also use this information for marketing.

Obviously I’m not accessing individual Census responses. I’m using the aggregated public datasets released afterwards. But Census data is enormously useful for demographic modelling because it allows you to understand the characteristics of different geographical areas and build much better population profiles.

What I’m particularly interested in isn’t simply asking where people live now. I want to understand where they’re going.

If you combine multiple Census periods, you can start looking at how demographic characteristics move geographically over time. People age, families form, people move, suburbs gentrify, housing affordability pushes populations further outward, employment centres change and infrastructure creates entirely new areas of growth. Entire demographic groups can gradually migrate across a city or region.

With enough historical information, you can start modelling those movements and eventually ask what the next movement might look like. That’s incredibly useful for governments planning infrastructure, but it’s also incredibly useful for businesses. If you’re deciding where to open a physiotherapy clinic, restaurant, retail store or practically any location-dependent business, knowing where your customers might live five years from now is considerably more useful than simply knowing where they lived five years ago.

So yes, I am deeply suspicious of enormous government datasets.

Please release the enormous government dataset as soon as possible.

Thank you.

Doesn’t the Government Already Know Most of This?

There was another thought that kept popping into my head while I was completing the Census: why am I telling the government some of this information in the first place?

The Australian Government and state governments already maintain an extraordinary number of administrative datasets. Births and deaths are registered. The tax system contains financial and employment information. Governments maintain business records. Medicare exists. Centrelink exists. Immigration records exist. Education systems exist. Property records exist. ASIC exists. The ATO exists. There are already enormous quantities of information about Australians scattered throughout government.

Now, there are extremely good reasons those databases aren’t all joined together into one gigantic government super-database where every public servant can search your name and see your entire existence. Different agencies collect information for different purposes and operate under different legislation, privacy requirements and access controls. Combining all of it indiscriminately would arguably create an even bigger privacy nightmare than the Census itself.

But from the citizen’s perspective, it still creates this bizarre contradiction where the government simultaneously knows an enormous amount about us while behaving like none of its departments have ever met each other.

We submit information to one department. Another department asks us for the same information. Then another government service asks again. Then every five years we fill out a Census form containing information that may overlap with administrative records already sitting somewhere else inside government.

That’s partly because there are legitimate privacy protections preventing government agencies from simply sharing everything with each other, which is probably a good thing. But it also exposes one of the biggest problems with government digital transformation: government itself is incredibly fragmented.

So rather than digital systems removing bureaucracy, sometimes we just digitise the bureaucracy.

And Who Has to Clean This Data?

The other thing that caught my attention while filling it out was the number of questions that allow relatively open text responses.

This is admittedly the data nerd part of my frustration because the moment I see a free-text field in a dataset I immediately think about the poor bugger who eventually has to clean it.

If you allow humans to freely type things into a database, humans will very quickly demonstrate why humans should not be allowed to freely type things into databases. One person writes “Marketing Manager”, another writes “Marketing Mgr”, another writes “Digital Marketing”, another just writes “marketing”, and someone inevitably describes themselves as a “professional Facebook wizard”.

There are legitimate reasons to allow free-text responses. Predefined categories can miss unusual occupations, cultural identities, emerging industries and answers that whoever designed the form simply didn’t anticipate. You don’t want the structure of your questionnaire determining what kinds of Australians are allowed to statistically exist.

But from a data-processing perspective, it must be an absolute nightmare. You’re dealing with spelling mistakes, abbreviations, slightly different descriptions of identical things, jokes, nonsense and completely legitimate answers that don’t fit neatly into existing classifications.

Enjoy your fuzzy matching.

Godspeed.

So... Should We Actually Be Worried About the Census?

This is where I reach the incredibly satisfying conclusion that I don’t actually know.

I started this entire thought process because I was annoyed at a website, but the Census sits directly in the middle of two things I strongly believe. I believe personal information should be protected aggressively and that governments shouldn’t collect information merely because collecting it might someday be useful. At the same time, I believe good decisions require good data, and you cannot meaningfully understand a country of roughly 27 million people without collecting information about the people who actually live in it.

Collect too little information and government planning becomes worse. Collect enormous amounts of information and you’ve created an enormous privacy and cybersecurity responsibility. Digitise the process and the information becomes faster to process, easier to analyse and potentially cheaper to collect at scale, but you’ve also created technological dependencies and concentrated cyber risks that paper never had. Keep everything analogue and you reduce some of those digital risks while making collection and processing slower, more cumbersome and potentially more expensive.

It’s a Catch-22. Damned if you do, damned if you don’t.

Maybe that’s actually what bothers me about the constant push towards government digitisation. Digital transformation isn’t inherently progress. Data collection isn’t inherently surveillance. Paper isn’t inherently obsolete. Technology isn’t automatically the correct solution simply because it’s newer. Every one of these systems involves trade-offs, and we’ve become extraordinarily good at talking about the benefits of digitisation without spending nearly enough time talking about the new risks and dependencies we’re creating along the way.

Maybe the question governments should be asking isn’t, “How do we digitise this?”

Maybe it should be, “Does digitising this actually make it better?”

Because if the answer is no, I’m perfectly happy with a piece of paper.

Just make sure you digitise the results afterwards.

I have models to build.

So I think this is an interesting thing. We seem to be very worried about Big AI being bad. OpenAI is a cesspit. Anthropic is literally the demon spawn. Google is apparently taking evil to a whole new level. Depending on which corner of the internet you happen to wander into, there is always a corporation currently responsible for the impending collapse of civilisation.

And look, some of the criticism is absolutely warranted. These are extraordinarily powerful companies building extraordinarily powerful technology, often faster than governments, regulators and society can properly understand what they’re building. There are legitimate questions around privacy, copyright, employment, misinformation, surveillance, environmental impact, monopolisation and the increasingly uncomfortable amount of power being concentrated into a handful of companies.

But I’d like to propose another outcome, which is pretty much the normal with me at this point. Big AI is only partly the problem. Unfortunately, the actual problem might be significantly worse, because we keep talking about AI as though OpenAI, Anthropic, Google and the other frontier labs are holding the keys to the machine.

They’re not. The machine has already escaped.

Axiom Accidentally Sent Me Down a Rabbit Hole

As I’ve mentioned before, I’ve been working on my own AI orchestrator called AXIOM. I’ve written an entire Brainwaves article about it already, so I won’t repeat the whole thing here. The important part is that I’m now onto version three, and building it has forced me considerably further down the AI rabbit hole than I expected to go.

AXIOM isn’t really an AI model itself. It’s closer to an orchestration system. Different models, tools, machines and agents can be given jobs, work autonomously, communicate with other systems and perform increasingly complicated tasks without me manually sitting there typing prompts into ChatGPT. Once you start experimenting with this stuff properly, you realise it really isn’t that difficult anymore.

Obviously there is a technical barrier. You need to understand computers. You need some programming knowledge. You need the hardware. You need to understand models, context windows, inference, APIs, agents and a bunch of other wonderfully nerdy things. But none of this requires being a Google engineer. I can do it, and that’s where my existential crisis begins, because if I can do it, plenty of other people can too.

I’ve Been Avoiding Writing About This

I’ve actually been avoiding writing Brainwaves articles about the state of the world lately. Everything feels too heavy. Every time I turn on the news there is another war, political crisis, economic problem, technological nightmare, environmental disaster or some other horrible thing happening somewhere.

Obviously humanity has always been like this. We’re very good at romanticising the past while conveniently forgetting that most of human history consisted of disease, war, famine and somebody invading somebody else because their king wanted another paddock. But the information environment is different now. Everything happens in front of us, constantly, and AI has somehow managed to become simultaneously one of the things that makes me most optimistic about the future and one of the things that makes me most concerned about it.

That’s the annoying part: I love this technology. I can learn things in hours that previously would have taken weeks. I can explore disciplines outside my existing expertise, build software faster, analyse enormous datasets and prototype stupid ideas simply because I wondered whether they were possible. It is genuinely incredible.

Then you pull back the curtain slightly further and think: oh. Oh no.

You Can Run This Stuff Yourself

I don’t think most people realise how accessible local AI has become. When the average person thinks about AI, they probably think about ChatGPT, Claude or Gemini. You type something into a website, your request travels somewhere into a gigantic data centre, the model processes it, the company applies its policies and safety systems, and something comes back.

That creates a comforting assumption that someone, somewhere, is in control.

Except you don’t actually need the company.

You can download models and run them locally. Completely locally. No internet connection required. The best model I currently run on my laptop is GPT-OSS 120B. It consumes an absolutely ridiculous amount of memory when running, but the fact that I can run a roughly GPT-4o-class open-weight language model on a laptop sitting in front of me is absurd.

Not a data centre or some university supercomputer. My laptop.

Once the model is sitting on your computer, you can connect it to agent software, give it access to files, development environments and tools, let it write code, analyse information and perform tasks. You suddenly have this strange little synthetic worker sitting inside your computer that doesn’t necessarily need an internet connection or a corporation sitting between you and it.

Which is incredibly exciting, until you discover abliteration.

Abliteration Is Where This Gets Uncomfortable

“Abliteration” is one of those words that sounds like it was invented by someone on Reddit at 3am, but the basic concept is fascinating and slightly horrifying.

AI models contain mechanisms that influence whether they comply with certain requests. Researchers and hobbyists have discovered techniques for modifying models in ways that substantially weaken or remove some of those refusal behaviours. The technical details get increasingly complicated, and at a certain point involve mathematics that causes my brain to politely leave the room, but the practical outcome is simple: models can be modified so that safeguards become significantly weaker.

Now combine that with everything I just described. Local models, no central provider, no API moderation, agent frameworks, autonomous execution, powerful consumer hardware, open-source software and models deliberately modified to refuse fewer instructions.

That’s the bit that worries me, because suddenly our entire conversation about “AI safety” starts looking strangely incomplete.

We Keep Asking Corporations to Control Something They No Longer Control

Governments can regulate OpenAI. They can regulate Anthropic. They can regulate Google. They can require age verification, restrict websites, force platforms to remove certain models, block services, write enormous pieces of legislation with exciting names and hold parliamentary hearings where politicians ask technology executives questions about things neither side particularly wants to explain properly.

But what exactly do you regulate when somebody can download the model?

Australia can block access to a website, but a sufficiently motivated person can find another route. A model can disappear from one hosting service and appear somewhere else. Files can be copied. Software can be forked. Models can be modified. Once something is sitting on somebody’s computer, the government cannot magically reach through the screen and put the safety features back.

This is the part of the AI debate I think we’re dramatically underestimating. We are treating AI like a service when, increasingly, it is infrastructure.

And infrastructure spreads.

My Client Got Hacked, Which Somehow Made This Worse

The rabbit hole actually started somewhere much more boring: a client got hacked.

That made me start thinking seriously about whether I should be doing more proactive security testing across the websites and infrastructure I manage. Attackers are already using automation and AI-assisted tooling, so eventually defensive security reaches an uncomfortable conclusion: refusing to understand offensive techniques doesn’t make your systems safer. It just means somebody else understands your vulnerabilities better than you do.

So I’ve been researching how autonomous agents could assist with authorised penetration testing against systems I manage. The objective is completely legitimate: find vulnerabilities before somebody malicious does, patch them, improve monitoring and make the websites safer. That’s a genuinely good application of the technology.

But while researching what these systems are capable of, you inevitably discover what the exact same underlying technology can do when you remove the words “authorised” and “defensive”. The same autonomous architecture that can continuously inspect my infrastructure for vulnerabilities could be adapted by someone else to continuously search for vulnerable infrastructure to attack.

The underlying capability doesn’t understand morality. We add the morality.

And Cybersecurity Is Only One Example

This problem isn’t limited to hacking. Generative image systems can also run locally. Video systems are improving. Voice cloning is improving. Language models are improving. Automation frameworks are improving. Agents are gaining access to browsers, operating systems, terminals and external tools.

And safeguards are not universal.

We’ve already seen deeply disturbing cases involving AI-generated sexualised deepfakes, including reports involving students and school communities. That genuinely makes me feel sick, and it demonstrates the central problem perfectly. You cannot solve malicious human behaviour by asking a model nicely not to participate, especially when another version of that model exists without the restriction.

Hacking is one thing. Synthetic media is another. Fraud, impersonation, misinformation, automated harassment and whatever other depraved use somebody thinks of next all exist on the same spectrum. AI hasn’t invented human depravity. We’ve been doing perfectly well in that department for thousands of years.

What AI changes is how much one person can do.

The Same Technology Can Also Be Incredible

This is where I keep getting stuck, because I don’t think “AI is evil” is an intellectually serious conclusion either.

I’m currently exploring AI-assisted penetration testing to make client infrastructure safer. That’s good. I’m building systems that analyse businesses and help them understand where they should invest, where opportunities exist and how they can make better decisions. That’s good too. Even calling some of that “AI” is questionable because half the time we’re really talking about traditional statistics, semantic analysis, machine learning and data engineering with AI slapped on the front because apparently everything needs AI branding now.

I’m also experimenting with pipelines that combine my photography with computer vision, photogrammetry, Gaussian splatting and generative systems to create better digital representations of client products. That’s incredibly cool. Similar technology can be used for architecture, historical preservation, education, training, simulation, accessibility, medicine, engineering and scientific research.

You can build systems that help people learn. Systems that help small businesses compete with enormous companies. Systems that make software accessible to people who could never previously afford development teams. Systems that analyse mountains of information and surface things humans would have missed.

The technology isn’t inherently evil.

That’s almost the problem.

AI Isn’t the Enemy

AI is still a tool, but I think we’ve created a fundamentally different category of tool.

A hammer can build a house or cave someone’s skull in. The difference is that a hammer cannot independently manufacture another hammer, research better skull-caving techniques, write the instructions, translate them into 40 languages, produce the marketing campaign and then operate continuously while you sleep.

AI can increasingly participate in that entire chain.

That’s what changes the equation. The problem isn’t simply that AI can be misused, because every technology can be misused. The problem is scale. One malicious person can suddenly produce the output that previously required dozens, hundreds or potentially thousands of people. One person can generate enormous quantities of misinformation, automate scams, manufacture fake identities or generate synthetic images, voices and videos. One technically capable attacker can potentially automate parts of cyberattacks that previously required significantly more expertise and labour.

And the marginal cost keeps approaching zero.

That is different.

Regulation Doesn’t Solve the Fundamental Problem

I’m not saying regulation is pointless. There are absolutely areas where governments should regulate how companies collect data, deploy AI, handle people’s likenesses, protect children, disclose synthetic media and use automated systems in high-risk environments. There should be consequences when people use these systems to commit crimes, and there should be responsibilities placed on corporations deploying powerful technology at enormous scale.

But regulation cannot make the capability disappear.

That’s the uncomfortable truth. The genie isn’t going back into the bottle.

We can regulate commercial nuclear reactors because building a nuclear reactor in your bedroom is somewhat inconvenient. AI doesn’t have that limitation. The hardware required to run increasingly capable models is becoming cheaper and more accessible. The models themselves can be copied infinitely. Knowledge spreads. Code spreads. Research spreads. Once a capability exists publicly, preventing determined malicious actors from accessing it becomes extraordinarily difficult.

Which means the safety question eventually moves beyond “How do we stop AI companies from doing bad things?” It becomes something far more difficult:

What happens when millions of individuals have access to capabilities that previously belonged to governments and enormous corporations?

I don’t think we’ve properly processed that yet.

This Is Why I’m Having an Existential Crisis

Because I build something cool, then discover somebody can use roughly the same thing for something horrible.

I build autonomous agents because I want software that can help operate my infrastructure. Someone else can build autonomous agents designed to attack infrastructure. I experiment with generative media because I want better creative pipelines. Someone else uses generative media to humiliate, exploit or deceive people. I use local models because I want privacy, independence and control over my own technology. Someone else wants local models because nobody can tell them no.

Am I the problem? Of course not. But that’s almost beside the point.

The barrier is simply becoming very low.

Someone could build autonomous malicious software. Someone could use unrestricted models to seek information mainstream systems deliberately refuse to provide. Someone could build an automated fake influencer, generate the photos, write the captions, manufacture the personality, generate videos, reply to messages and operate the account indefinitely.

Not because they’re some elite hacker sitting in a dark room surrounded by seventeen monitors, but because the components required to do these things are becoming increasingly accessible.

That is the scary part.

So What Exactly Are We Supposed to Do?

No idea. Excellent conclusion, I know.

I don’t think anyone really knows. We’re trying to build rules around something that is evolving faster than the rules can be written, and personally I’m stuck in this strange position where I don’t want to stop exploring the technology simply because other people can misuse it. That would be ridiculous. The same curiosity that led me into this existential crisis is also showing me ways of making systems safer.

Maybe that is actually where the responsibility sits. Not pretending the dangerous capabilities don’t exist, but understanding them. Testing them responsibly. Building defences. Creating better verification systems. Teaching people how synthetic media works. Hardening infrastructure. Making provenance easier to establish. Developing ethical norms around how these systems should be used.

And, importantly, maintaining some kind of moral framework when the technology itself doesn’t provide one.

Which brings me, somewhat predictably, back to Christianity.

Thank God I Have Some Kind of Moral Baseline

I don’t mean that as “Christians good, everyone else evil.” History would make that argument collapse almost immediately. I mean that personally, I’m increasingly grateful that I have something outside technology against which I can measure what I’m doing.

Because technological capability is a terrible moral framework.

“Can I build it?” is not the same question as “Should I build it?” “Can this be automated?” is not the same question as “Should this be automated?” And “Can this make money?” is definitely not the same question as “Should this exist?”

AI doesn’t solve those questions. If anything, it makes them considerably more important. When your capabilities increase, your responsibility increases with them.

Perhaps that is the part of the AI conversation we should be focusing on more. Not simply what the machine is capable of, but what we are capable of doing with it.

White Hat AI

So maybe that’s where I land: white hat AI.

I’m going to keep experimenting. I’m going to keep building AXIOM. I’m going to keep downloading models onto increasingly ridiculous computers. I’m going to keep experimenting with autonomous agents, local models, security systems, data analytics, computer vision, generative media and whatever other absurd technology appears next Tuesday.

And I’m going to see how far I can push it.

But there needs to be a line. Use offensive security knowledge to improve defensive security. Use autonomous agents to protect infrastructure rather than attack it. Use generative media to create rather than exploit. Use data to help businesses make better decisions rather than manipulate people. Understand the dangerous capabilities precisely because pretending they don’t exist leaves those capabilities exclusively to people who don’t care about the consequences.

Fight the depravity rather than contribute to it.

Because I don’t think we’re stopping this thing.

Five years from now? I have absolutely no idea what the world looks like. At the current rate, I’m not entirely confident what it looks like one year from now. That scares me, but it also fascinates me. Perhaps that’s the uncomfortable reality of living through a technological revolution: the same invention can make you incredibly hopeful and deeply concerned at exactly the same time.

AI isn’t God. It isn’t the devil either. It’s something much more uncomfortable.

It’s a tool that increasingly amplifies whatever the person holding it already intended to do.

And we’ve just handed that tool to humanity.

If you’ve met humanity, you’ll understand why I’m concerned.

Most Sundays at church I take notes. Sometimes they’re direct notes from the sermon, sometimes they’re Bible verses I want to come back to, and sometimes they’re just whatever thought has fired off in my brain while someone else is still talking.

And I’ve realised I actually get quite a lot out of going back through them.

So I thought: why not share them?

This isn’t going to be me pretending to be a theologian. It’s also not going to be a neat summary of the sermon every week. Think of it more like my notes from Sunday, expanded with my own thoughts, questions and occasional existential crisis attached.

I’m hoping that, firstly, writing these helps me properly process what I’ve heard rather than forgetting 90% of it by Monday morning.

But secondly, maybe sharing them helps someone else with their own faith journey too.

And if faith isn’t your thing, read it anyway lol. Might be exactly what you need.

This week, we’re in Mark 6.

When Jesus Goes Home

Mark 6 begins with Jesus returning to his hometown of Nazareth.

Which is already interesting when you think about who these people are.

They know Jesus.

Or at least, they think they know Jesus.

This is the town where Jesus grew up. These are people who would have known his family. Some of them presumably watched him grow from a child into a man. They knew Mary. They knew his brothers and sisters. They knew him as the carpenter.

Then Jesus comes back and begins teaching in the synagogue.

And they’re amazed.

“Where did this man get these things?”

That’s the question they ask.

They recognise that something extraordinary is happening. They hear his wisdom. They’ve heard about the miracles. Jesus has just come from places where incredible things are happening around him.

And yet something doesn’t compute.

Ralph made an interesting point about this: perhaps their vision of Jesus was simply too small.

They couldn’t separate the Jesus they remembered from the Jesus standing in front of them.

They had already decided who he was.

He’s the carpenter.

He’s Mary’s son.

We know his family.

We know where he came from.

So who does he think he is?

And I think there is something deeply uncomfortable in that because we can do exactly the same thing.

We Put God in a Box

Mark 6:3 ends with a surprisingly strong response:

“And they took offence at him.”

They weren’t merely confused by Jesus.

They were offended by him.

The Greek behind the idea of taking offence is where we get the idea of a scandal or stumbling block. Something about Jesus didn’t just challenge their understanding. It collided with it.

They had a box labelled JESUS.

Jesus had stopped fitting inside it.

And rather than making the box bigger, they rejected what was standing in front of them.

I think we do this constantly with God.

We domesticate God.

We turn him into something manageable. Something familiar. Something that fits comfortably alongside everything else we’ve already decided about life.

God can have Sunday morning.

God can help with my problems.

God can give me some guidance.

God can hopefully make me a slightly better person.

But then God disagrees with us.

And suddenly we’re offended.

Because somewhere along the way we stopped trying to become more like God and started trying to make God more like us.

We want a God who validates the life we’ve already chosen rather than one who might completely rearrange it.

That isn’t really surrender.

That’s asking God to become our consultant.

God Doesn’t Want to Improve Your Life

This is probably the part that hit me hardest.

Because Christianity isn’t ultimately about God helping me become a more successful version of myself.

God has no interest in merely helping me live my life better.

He wants my life.

Jesus says something brutally direct in Luke 14:

“Those of you who do not give up everything you have cannot be my disciples.”

Not exactly inspirational-coffee-mug Christianity.

Everything.

And this is something I struggle with.

I overthink worldly things constantly.

Where is my money coming from?

Where is it going?

What am I building?

What’s the next move?

What happens if this goes wrong?

How do I make sure that doesn’t happen?

How do I control the outcome?

And control becomes the problem.

Because if I genuinely believe my life belongs to God, then at some point I have to actually let it belong to God.

My money is God’s.

My work is God’s.

My plans are God’s.

My future is God’s.

My successes are God’s.

My failures are God’s.

That doesn’t mean becoming irresponsible and sitting around waiting for money to fall from heaven. It means recognising that ultimately I am a steward, not the owner.

There’s a massive difference.

Maybe a better prayer is:

Take everything from me, as long as you’re glorified through it.

And I don’t particularly enjoy writing that sentence because there is a difference between saying it and actually meaning it.

We Prefer the God We Already Know

There’s another problem hiding inside Nazareth.

Familiarity.

We tend to settle for what we’ve always known rather than make room for whatever new thing God might be doing.

Nazareth knew Jesus as the carpenter.

They couldn’t comprehend Jesus as anything greater.

And I wonder how often churches do exactly the same thing.

“This is how we’ve always done it.”

“This is what church looks like.”

“This is how worship works.”

“This is who belongs here.”

“This is what God does.”

We construct an image of God from our previous experiences of him, then accidentally use that image to restrict what we believe he can do next.

The vision God has is so much greater than what we can envisage.

It is greater than our institutions.

Greater than our traditions.

Greater than our plans.

Greater than the darkness around us.

Greater than our sin.

Greater than whatever comfortable little box we’ve managed to squeeze him into.

Maybe part of faith is having the humility to admit that God might be considerably bigger than our understanding of God.

A Prophet Without Honour

Jesus responds to Nazareth:

“A prophet is not without honour except in his own town, among his relatives and in his own home.”

What strikes me is that Jesus doesn’t throw a tantrum.

He isn’t offended because people haven’t recognised how important he is.

If anything, the passage feels sad.

He has come home carrying something extraordinary, and the people who should have welcomed him can’t see beyond the version of him they already know.

What should they have done?

Honoured him.

Welcomed him.

Made room for him.

Expected something.

Instead, Mark gives us one of the strangest verses in the passage:

“He could not do any miracles there, except lay his hands on a few sick people and heal them.”

Which is also an absolutely hilarious Biblical standard for “not many miracles.”

Oh, nothing much happened. He just healed a few sick people.

But compare Nazareth with everything happening around Jesus elsewhere.

Something is missing.

Mark tells us exactly what it is.

Faith.

God Will Not Force Himself on You

This is where the passage gets uncomfortable.

God will not dwell where God is not wanted.

That doesn’t mean God disappears from existence because someone doesn’t believe in him. It means God doesn’t force relationship upon us.

We have free will.

If you don’t want God, God isn’t going to kick the door down and force you to worship him.

You don’t want God?

Okay.

Deal with it.

(My words, not Ralph’s lol.)

But that principle becomes much more uncomfortable when applied to Christians.

Because it’s easy to point at the unbelieving world and say, “They don’t want God.”

What about us?

Do we?

Not theoretically.

Actually.

Do we want God when God disrupts our plans?

Do we want God when obedience costs us something?

Do we want God when he disagrees with us?

Do we want God when following him means giving something up?

Do we want God, or do we want the benefits we associate with having God nearby?

Those are two very different things.

Amazed by Jesus, Without Faith in Jesus

Mark 6:6 says:

“He was amazed at their lack of faith.”

Jesus was amazed.

That’s quite a sentence.

Especially because there is another moment in the Gospels where Jesus is amazed, except for the exact opposite reason.

A Roman centurion asks Jesus to heal his servant. Jesus offers to come to his home, but the centurion essentially says there is no need.

Just say the word.

That’s enough.

And Jesus marvels at his faith.

The contrast is brilliant.

Nazareth had every reason to believe.

They knew Jesus.

They heard him teach.

They were amazed by his wisdom.

They knew the stories.

And still they lacked faith.

The centurion simply believed that if Jesus spoke, it would happen.

Which leaves us with a pretty confronting possibility:

You can be impressed by Jesus and still have no faith in him.

You can enjoy the sermon.

You can like Christian ideas.

You can know Bible verses.

You can sing worship songs.

You can think Jesus was an extraordinary teacher.

You can even be amazed by him.

And still not actually trust him.

Faith isn’t admiration.

Faith requires something from us.

The Harvest Is Still Plentiful

This connects to another teaching of Jesus: the harvest is plentiful, but the workers are few.

There is so much to do.

And frankly, we don’t do enough.

I don’t mean that in the exhausting religious sense where everyone needs to add another seven church activities to their calendar.

I mean that if we genuinely believe what we say we believe, the scale of our vision should probably look different.

The vision is so much greater than what we can see.

God’s vision for a person is greater than their sin.

God’s vision for a church is greater than maintaining Sunday attendance.

God’s vision for a city is greater than keeping Christianity quietly contained inside church buildings.

But we have to remain hungry for it.

Because churches can lose that hunger.

Revelation’s warning to the church in Ephesus is confronting precisely because Ephesus wasn’t simply a useless church. It had works, endurance and discernment, yet Christ tells them they have abandoned their first love.

A church can remain busy while spiritually dying.

It can maintain programs.

Maintain buildings.

Maintain services.

Maintain traditions.

Maintain committees.

Maintain absolutely everything except the thing that gave it life in the first place.

And eventually you’re maintaining a corpse.

What Are We Actually Expecting?

Revival didn’t break out in Nazareth.

Not because Jesus wasn’t there.

Jesus was literally standing among them.

That’s what makes the story so strange.

They had the presence of Jesus and still missed what was possible.

Which makes me wonder what we actually expect when we gather as a church.

Do we expect God to do something?

Do we expect people to change?

Do we expect broken people to be restored?

Do we expect people who don’t know God to encounter him?

Do we expect our communities to change?

Do we expect revival?

Or do we expect a nice service that finishes roughly on time so everyone can go and get lunch?

Expectation doesn’t mean God becomes some cosmic vending machine where sufficient faith earns us miracles. That’s not the point.

But our hunger for God absolutely affects how much room we make for him.

How much of ourselves are we actually willing to surrender?

How much space have we made?

How much are we willing to risk?

How much do we actually want him?

Because maybe the question isn’t whether God is willing to move.

Maybe sometimes the question is whether we’ve left any room for him to move at all.

Stop Domesticating God

That’s probably my biggest takeaway from this Sunday.

Stop domesticating God.

Stop shrinking him until he comfortably fits inside the life we’ve already designed.

Stop treating Jesus like a familiar mate whose job is to agree with us.

Stop confusing admiration with faith.

Stop asking God to bless our plans without ever asking whether they’re his plans.

And stop assuming that because we’ve known God for years, we’ve somehow reached the boundaries of what God can do.

The people of Nazareth thought they knew Jesus.

That familiarity became the very thing preventing them from seeing him.

I don’t want that.

I don’t want a faith where Jesus becomes so familiar that I stop expecting anything from him.

I don’t want a church that talks endlessly about what God did while losing faith in what God can do.

And I definitely don’t want God reduced to a supporting character in the story of my own life.

The vision is bigger.

The harvest is bigger.

God is bigger.

And perhaps faith begins when we finally stop trying to make him smaller.

So, it’s been a hot minute.

Again.

I continue to be spectacularly bad at sticking to my usual attempt at publishing four articles every month. This month, you get two big ones instead.

Sorry, not sorry.

There is a good reason for that, though. I’ve been busy writing and building AXIOM.

I’ve also been working on 4671, but that is going to be a separate article because there is only so much sleep-deprived technical rambling I can reasonably fit into one post. Or, more accurately, only so much I should fit into one post.

This one is about AXIOM.

Or, more specifically, how a failed experiment involving a Mac mini slowly turned into the connective tissue for nearly everything I have spent the past year building.

Mission Failed

Remember AXIOM?

The story technically started with Claude Code, OpenClaw and a Mac mini.

I got a little overexcited, installed everything, connected it all together and managed to get the thing running. For a short and beautiful period, it appeared that I had created a useful little autonomous machine that could sit in the corner and do work for me.

Naturally, I wrote an article praising it.

The next day, it died in a ditch.

It stopped working. It stopped connecting. Nothing talked to anything properly. I spent an entirely reasonable amount of time cursing it, switched off the Mac mini and put it in a cupboard.

That is where it stayed for quite a while.

Mission failed.

Or so I thought.

My general worldview when it comes to technology is that if something is broken, badly designed or irritating enough, the obvious response is to build something better myself.

This is not necessarily a healthy worldview. It is, however, responsible for quite a lot of Tomedia.

So I eventually brought the Mac mini back out, mentally dusted off the AXIOM idea and started thinking about a problem I had needed to solve for a very long time.

The problem was not really OpenClaw.

The problem was me.

More specifically, the fact that I had somehow turned myself into the connective tissue between every system I had built.

Tomedia Had Plenty of Organs but No Nervous System

Tomedia is currently split into a growing collection of separate systems.

There is Scribe. There is Mule. There is Seer for large-scale research. There is Overwatch for proof, monitoring and reporting. There is Discover. There are internal CRM, creative and operational systems. There are website tools, deployment processes, client systems and a steadily expanding collection of models that do genuinely useful things.

They all exist.

Some of them are very good.

Some of them contain mathematical and strategic models that I have spent months building, testing and refining. They can implement repeatable strategies consistently, and I can see the impact of those strategies in client work.

The problem is that I am probably using most of them at about ten per cent of their full potential.

They have no connective tissue.

Each system understands its own part of the world, but there is no shared layer that understands why a piece of work exists, where its information came from, which client it relates to, what decision approved it, who or what is meant to carry it out, and whether the result actually worked.

That makes the whole business more convoluted to operate than it needs to be.

It also makes me quite sad, frankly. I have worked hard to build these systems, but the final step between “this is an impressive tool” and “this meaningfully changes how the company operates” has remained stubbornly manual.

At the same time, software engineering work has expanded into entire 30-hour weeks of big-data pipelines, integrated website systems and infrastructure work for one of my main clients.

That work is interesting and valuable, but it has stretched me thin.

Then there is Discover.

Discover gets new users every week, which should be exciting. The last count I saw was somewhere around 300 users, which is honestly not bad for something that only properly started around seven months ago and has changed substantially since then.

Unfortunately, I am not happy with it.

It is a buggy mess.

It does have an inbuilt error-finding system that tells me exactly what is going wrong on a daily basis, which is useful. The less useful part is that somebody still needs to fix those errors.

That somebody is me.

Assuming I have the time.

Free users also do not magically become paying users, especially when the platform they are being asked to pay for behaves like a bin fire with a login screen.

On top of that, there is Risen. CutCompass still needs to be finalised properly. Veritas needs cleaning up. Ephemera has only just reached the point where The Big Book of SEO is finished and available for sale.

There are client systems to maintain, internal products to finish, ideas to validate, reports to review, deployments to manage and bugs to fix.

I have been very busy.

Time has become the enemy of nearly every good thing I have built over the past six months to a year.

Which led me to a fairly obvious question.

What if there were a way to get some of that time back?

What if the menial coordination work could happen automatically, without handing complete control of the company to a chatbot with an API key and an unjustified amount of confidence?

That is where AXIOM comes in.

And, oh my, it is beautiful.

The First Control Plane

AXIOM did not originally begin as AXIOM.

The first practical version was called the AI Control Plane, which is functional but not exactly the sort of name that inspires mythology.

It lived inside Tomedia, and it had one job: use Codex to automate fixes for TomediaMain, the repository containing the main website.

TomediaMain already produced logs for every issue it found. Those errors were sent directly to me and saved into a bug-fix collection, ready for somebody to investigate.

The reporting part worked.

The fixing part still required manual effort.

I had to inspect the error, understand the relevant part of the codebase, create the task, implement the fix, test it, prepare the change and deploy it.

The Control Plane was designed to close that gap.

It would take a recorded error, turn it into a properly structured GitHub issue and move the proposed fix through a staged software-delivery process.

While building it, I finally accepted that it was probably time to set up proper GitHub Actions and deployment workers.

Until then, I had been doing a rather embarrassing amount of deployment work manually.

This did occasionally break things.

Whoops.

The new process added GitHub Actions, connected Codex through GitHub, generated fixes for me to review and returned them through pull requests.

And it worked.

It worked remarkably well.

The system could discover an issue, create the corresponding work and prepare a fix, sometimes within the first hour of the problem appearing.

Instead of an error sitting in a collection until I found time to deal with it, the first pass could already be waiting for review.

Bob’s your auntie Pat: the bug was identified, investigated and potentially fixed before it had time to become part of the furniture.

For Discover, that was ideal.

The product desperately needed a cleanup phase, and this gave me a credible way to perform one without sacrificing every other thing I was meant to be doing.

Perhaps, eventually, Discover could even earn some money.

It turns out people are more likely to pay for a platform when it is usable. Who knew?

Then I Made It Bigger

Naturally, I was not satisfied.

Fixing bugs automatically was useful, but I still had far too much to manage.

I wanted dedicated automation branches. I wanted release trees and separate pipelines for different areas of the platform. I wanted reports sent to me in a format I could approve while away from my desk. I wanted the whole process to be more visible, interactive and controllable.

So I introduced Slack.

Then I introduced more workers.

Then more routing.

Then more reporting.

Then all the other fun things that turn a small automation script into an infrastructure project.

I also did not want every piece of internal work to require paid access to Codex, OpenAI or whichever model happened to be fashionable that week.

So I built a model machine.

A couple of years ago, I built a fairly powerful computer. AXIOM gave it a new purpose: running local models, benchmarking them and allowing several models to compete or collaborate on internal reporting and analysis.

The machine is connected through Cloudflare Zero Trust, which means I can access it securely from elsewhere without opening the entire thing to the internet and hoping for the best.

More importantly, the worker framework is designed so that the machine itself is not special.

I can bring the Mac mini back out of its cupboard, connect it and assign it a different set of workers. I can add another Mac mini later. I can attach a Linux GPU machine. I can temporarily route approved work to a cloud model.

Each machine contributes capacity.

The framework decides what kind of work that machine is suitable for.

This first version reached the point where it was roughly 80 per cent complete. Complete enough that the core approach worked, but not fully switched on across everything.

Then I made the dangerous mistake of thinking:

What else could I do with this?

Introducing AXIOM v2

This is AXIOM v2.

Or possibly v3, depending on whether we count the original OpenClaw monstrosity.

AXIOM is my new magnum opus. It is designed to take control of the time I cannot manage manually, without taking control away from me.

It is a second brain without fully surrendering the first one.

It is a way to implement more rigorous, repeatable and evidence-driven work. More importantly, it is finally a way to connect nearly all of Tomedia’s existing optimisation systems into one coherent package.

The ultimate machine.

So, What Actually Is AXIOM v2?

The easiest mistake would be to describe AXIOM as another AI assistant with a lot of integrations attached to it.

It isn’t.

An assistant usually sits inside a chat window and waits for somebody to ask it a question. It receives a prompt, produces an answer and then forgets most of the operational reality surrounding that answer.

AXIOM is closer to an operating system for a small digital company.

Or, more accurately, it is an artificial ecology made up of specialised workers, departments, models, machines, memories and approval systems, all operating beneath one protected controller.

It is the connective tissue Tomedia has been missing.

Instead of Scribe, Mule, Overwatch, Seer, Discover, SiteOps, CRM, Creative and everything else existing as separate islands, AXIOM sits above them.

It connects the reason work exists, the research behind it, the person or machine performing it, the approval that permitted it, the result it produced and the evidence showing whether that result actually worked.

The current AXIOM core already handles jobs, workers, model routing, costs, risks, approvals, Slack requests, GitHub issues and software delivery.

V2 broadens that control plane into a system that can research, plan, delegate, compare different approaches, retain evidence, measure results and gradually improve the way work is performed.

The distinction between what exists and what is planned matters.

I am not claiming every named component below is secretly alive, fully autonomous and running the company while I sip something expensive on a beach.

Some parts are working now. Some are being connected. Others are mapped as later capability branches.

The spine, however, exists.

That is the important bit.

The Artificial Ecology

The ecology comparison is not just me being dramatic.

Although I am, obviously, also being dramatic.

AXIOM itself acts as the protected germline. It owns the rules, goals, budgets, permissions and ability to create workers.

The workers are temporary cells.

Each worker has a manifest that functions a little like DNA. The manifest defines which model the worker uses, which tools it can access, what data it is permitted to see, how much compute it can consume, how long it is allowed to remain active and under which conditions it must stop.

Tests, evidence and real outcomes create the selection pressure.

Useful workers and workflows can be retained and reused. Unreliable ones can be modified or retired. Time limits, permission revocation and rollback function as a form of programmed cell death.

It is reproduction, without worrying about it coming back to bite me.

A worker cannot decide to copy itself onto another machine. It cannot expand its own permissions, remove its expiry time or suddenly decide that it should have access to a client advertising account.

Only AXIOM can create another worker.

Every child worker inherits a narrower set of permissions than the controller or parent process that created it.

This is one of the fundamental rules of the system.

More machines increase capacity.

They do not increase authority.

That means I can connect the Windows model machine, wake the Mac mini back up, add another Mac mini later, attach a Linux GPU box or temporarily use an approved cloud model.

Each machine registers what it can actually do. It reports which models are available, what hardware it has, how heavily loaded it is, what privacy levels it supports and which classes of work it is allowed to receive.

AXIOM can then place each job on the most appropriate machine.

The Mac mini is no longer pretending to be the brain.

It is one organ in a larger system.

There Is No Main AI Model

There is no single “main AI model” sitting at the centre of AXIOM.

That is deliberate.

Different models are good at different things. Some are quick and efficient. Some are better at careful reasoning. Some write stronger code. Some extract structured information more reliably. Some are useful precisely because they disagree with the others.

AXIOM is designed to take advantage of that diversity rather than pretending one model should be trusted with everything.

For difficult jobs, it can run tournaments.

One worker might focus on finding information quickly. Another might perform deeper reasoning. A third might attack the underlying assumptions. Another might verify every factual claim. Another might inspect the technical feasibility. Another might write the code.

The workers operate independently enough that one answer does not simply contaminate all the others.

Their outputs can then be compared.

Weak claims are challenged. Contradictions are surfaced. Unsupported conclusions are rejected or sent back for more evidence. The final result is checked again rather than accepted because one model sounded especially confident.

The objective is not to create artificial consensus.

It is to create useful disagreement and then resolve it with evidence.

A hundred copies of the same model making the same mistake is not intelligence.

The useful part comes from genuine diversity, independent evaluation and a reliable way to determine which answer survives.

This is where the named AXIOM departments begin to appear, because apparently one acronym was not enough and I decided the system needed an entire mythology.

THEORIA: Research Before Action

THEORIA is the research and development branch.

Before a major Tomedia feature, client strategy or operational change becomes active work, THEORIA creates a proper research dossier.

The dossier describes what currently exists, what problem is actually being solved, what evidence supports that problem, which assumptions are being made, what alternatives are available and how we would know whether the chosen direction worked.

That last part is particularly important.

A surprising amount of work begins with a solution somebody finds exciting, followed by a frantic attempt to invent the problem it supposedly solves.

THEORIA is intended to reverse that process.

It is not allowed to approve its own conclusions.

It produces the research for me to read, question, challenge, narrow, reject or approve as a specific direction.

Under THEORIA are several more specialised roles.

ARGUS is the evidence scout. It gathers internal information, client data, market research, technical sources and other relevant evidence. It records where information came from, when it was captured, how fresh it is and whether different sources contradict one another.

DAEDALUS is the systems architect. It maps the infrastructure that already exists before proposing another shiny new subsystem.

This is especially important for Tomedia because I am extremely capable of building a new tool before remembering that I created 70 per cent of it somewhere else six months earlier.

SOCRATES is the deliberately annoying one.

Its job is to challenge the idea, identify the strongest argument against it, expose unsupported claims and ask what evidence would prove the preferred direction wrong.

For example, imagine I want to add a major new feature to Discover.

ARGUS can investigate user behaviour, error patterns, feedback and market evidence. DAEDALUS can inspect whether the necessary capability already exists elsewhere in Tomedia. SOCRATES can ask whether the proposed feature solves the real problem or merely creates another subsystem for me to maintain.

THEORIA then assembles those perspectives into one versioned document.

I can comment on individual sections, request more evidence, ask for another option or approve one exact revision.

That revision is frozen.

AXIOM cannot quietly rewrite the document later and pretend the new version was what I approved all along.

Approving a direction also does not approve every action that might follow from it.

A research approval does not automatically grant permission to publish something, spend advertising money, merge code, deploy to production, send a document to a client or mutate an external provider.

A strategic decision and an operational permission are not the same thing.

That boundary is essential.

HERMES: Turning Decisions Into Work

Once a direction has been approved, HERMES handles the handoff.

HERMES is the coordination layer between a decision and the systems that must act on it.

It converts an approved direction into properly scoped work for the correct Tomedia departments.

The handoff includes the client, objective, source evidence, approved revision, expected result, constraints and acceptance criteria.

The next worker is not given a vague prompt with half the context missing.

This solves one of the most persistent problems in both human and machine workflows: context evaporating between stages.

A research system understands why something matters. A project-management tool sees only a task title. A developer receives a ticket. A reporting system later sees a release. Somewhere between those points, the original reason for doing the work disappears.

HERMES carries that reason through the chain.

Every downstream job can be traced back to the approved evidence and decision that created it.

FORGE: From Recommendation to Software

Software work is sent to FORGE.

FORGE is the engineering collective.

It turns approved recommendations into GitHub issues, isolated branches, code changes, tests, draft pull requests and release evidence.

FORGE can build a change.

It can inspect the codebase, generate an implementation, run tests and prepare the proposed work for review.

What it cannot do is quietly alter the approved direction, review itself, merge itself or deploy itself to production.

Those are separate powers.

This separation is not there because I assume every model is secretly plotting a takeover.

It is there because the same process should not be responsible for proposing a change, implementing it, declaring it correct and releasing it into the real world.

Humans are bad enough at marking their own homework. Machines do not need the same opportunity.

FORGE can say, “Here is the implementation, here are the tests, here is the evidence and here are the remaining risks.”

Another system--or I--decides what happens next.

AXIOM Does Not Replace the Existing Tomedia Systems

Client work continues through the existing Tomedia departments.

Scribe remains responsible for content and search work.

Mule remains responsible for advertising strategy and reversible campaign changes.

Seer continues to support large-scale research and analytical work.

Overwatch remains the proof, health and reporting layer.

SiteOps and GitHub retain control over website and software delivery.

CRM, Creative and the other systems retain their own responsibilities, restrictions and action gates.

AXIOM coordinates them.

It does not replace everything with one enormous ai machine god.

The goal is not to throw that work away and ask one general model to improvise the company from scratch every morning.

The goal is to connect those systems so they can operate as parts of the same machine.

Memory Must Be More Than a Chat History

Behind all of this is the memory layer.

MySQL holds the current operational truth.

It records which jobs exist, what state they are in, who approved them, which worker has claimed them, which permissions apply and what is allowed to happen next.

It is the live state of the machine.

ClickHouse becomes the empirical memory.

It stores what evidence was used, which worker or model performed the task, how much the work cost, how long it took, which tests passed, what humans accepted or rejected, whether something was rolled back and what happened to the actual business result later.

The difference between those two forms of memory is incredibly important.

The system of record cannot just be a long conversation transcript.

AXIOM needs to know both what is true now and what happened historically.

Most AI systems effectively learn that “task completed” means success.

AXIOM is designed around the idea that completion and quality are not the same thing.

A beautifully written report can still be wrong.

A code change can pass one test and break something else.

A campaign recommendation can sound clever and lose money.

A page can increase clicks while making the website worse for everybody who arrives there.

A worker can technically complete every requested step and still produce something useless.

AXIOM’s long-term fitness measurements are therefore based on evidence, tests, human judgement, incidents, rollbacks and delayed outcomes.

Not merely whether a worker successfully produced some text.

This also allows the system to learn which models and workflows are actually useful for particular kinds of work.

The cheapest model is not always the most economical model if its output creates four hours of human rework.

The most sophisticated model is not always the best choice for a simple extraction task.

The fastest worker is not necessarily the most valuable if everything it produces needs to be checked twice.

The outcome data gives AXIOM a way to make those distinctions empirically.

Controlled Self-Improvement

The memory layer also creates a controlled path towards self-improvement.

Eventually, AXIOM will be able to propose changes to its prompts, workflows, routing rules, tools, worker manifests and selected pieces of worker code.

The important word is propose.

Those changes follow the same boring, beautiful software process as everything else.

Research.

An isolated branch.

Tests.

Independent evaluation.

A pull request.

Staging.

A limited canary release.

Then either promotion or rollback.

AXIOM can identify that a routing rule is performing badly. It can produce evidence showing that another model or workflow performs better. It can prepare the change and submit it for review.

It cannot approve its own evolution.

That gives the system room to improve without creating an environment where it can silently rewrite the rules governing its own behaviour.

Improvement is allowed.

Unsupervised authority expansion is not.

Seeing the Whole Machine

All of this needs to become visible through a new management layer.

The Founder Command Centre provides the “what needs me right now?” view across clients, approvals, incidents, costs, capacity, research and releases.

I do not need another dashboard showing me fifty green numbers.

I need to know where a decision is blocked, where something has gone wrong, where money is being wasted and which action genuinely requires human judgement.

Client Mission Control shows what has been promised to a client, what is being worked on, why that work exists, which research supports it, what is blocked, what has been delivered and whether it achieved anything.

The R&D Portfolio contains every active idea and dossier, the evidence behind it, the questions that remain unanswered and the exact decision being requested.

The Work Graph shows dependencies between research, jobs, departments, people and outcomes.

Instead of giving me twelve separate queues and expecting me to reconstruct the story in my head, it shows how the work fits together.

The Quality and Outcome Lab contains tournaments, tests, human reviews, rejected outputs, incidents, rollbacks and real-world results.

That is where AXIOM can prove whether it is becoming more useful rather than merely becoming busier.

The Worker Fleet and Model Registry shows every connected machine, available model, declared capability, benchmark, active queue, failure and piece of spare capacity.

Adding another Mac mini should eventually be as simple as enrolling it, benchmarking it and allowing AXIOM to assign appropriate work.

It should not require rewriting the routing system every time I find another computer in a cupboard.

The Other Organs

There are several other planned organs within the wider AXIOM ecology.

MNEMOSYNE is the semantic memory layer. It connects clients, companies, people, campaigns, code, claims, decisions and outcomes over time.

It allows AXIOM to understand that a client mentioned in a meeting, a campaign referenced in a report, a company stored in the CRM and a repository containing the client’s website all belong to the same wider context.

DIPLOMAT is the integration gateway. It provides one governed way to connect new tools, data sources and external systems without giving every worker unrestricted access to everything.

LANTERN handles observability. It allows a piece of work to be traced from its original goal through every worker, model, tool call, approval and result.

CUSTODIAN manages privacy, retention, consent and data boundaries.

ORACLE is the experimentation and causal-analysis branch. Its job is to help separate “this happened at the same time” from “this probably caused the result”.

SIMULACRUM is the scenario and digital-twin laboratory. It allows AXIOM to rehearse capacity, campaign, pricing and operational decisions before changing the real world.

LEDGER connects machine cost, model spend, human time, client value and available capacity.

Saving three pence on a model is not especially useful if the cheaper output creates four hours of rework.

Then there are assurance and commercial branches.

AEGIS focuses on security and resilience.

JUSTITIA handles obligations and compliance.

PROSPECTOR researches commercial opportunities.

STEWARD focuses on client success, value delivery and retention.

Not every one of these is fully alive yet.

Some already exist within the current infrastructure. Some are being wired together. Some remain mapped as later capability branches.

But the spine now exists.

That is the important bit.

A Second Brain Without Giving Up the First

AXIOM is not meant to replace my brain.

It is meant to stop my brain being used as the database, router, project manager, deployment checklist, error queue and connective tissue between every system I have built.

I do not want an autonomous machine making unreviewed decisions for clients, spending money because it feels optimistic or deploying changes because one model told another model that everything looked fine.

I want a system that gathers the evidence, preserves the context, coordinates the work, tests the output and presents the right decision to me at the right moment.

It gives me a second brain without requiring me to hand the first one over.

Instead of spending my time chasing broken deployments, copying context between tools, checking whether something was approved, manually reconstructing client work or noticing the same bug for the fifth time, I should be spending it on decisions, strategy, clients, ideas and the strange new things I apparently cannot stop building.

For the first time, all of Tomedia’s separate systems are starting to look like parts of the same machine.

Not a collection of disconnected tools.

Not a folder full of clever experiments.

A machine.

Now I just need to finish it before I get distracted by 4671.

Which, unfortunately for my sleep schedule, is going to be its own article.

It ends in a fight.

But we both drink whiskeys and smoke cigars, so it’s fine.

That is more or less the dynamic between me and one of my best friends. He is, lovingly, a hardcore socialist. I am a business owner. On paper, we should probably annoy each other to death. In reality, he is one of my favourite people in the world, and we spend a lot of time arguing about politics, economics, tax, fairness, business, workers, and whether society is broken or just badly managed.

And honestly, that is how it should be.

People are not meant to agree on everything. We are heterogeneous. We have different lives, different incentives, different risks, different fears and different ideas of what “fair” actually means. A healthy society is not one where everyone nods along to the same script. It is one where disagreement helps us build something that works for more than one type of person.

So this article is not me pretending I have solved tax. It is me asking a simpler question.

If we could invent a better tax system for Australia, what would it look like?

Not a perfect one. Perfect systems do not exist. But a better one. A tax system that is fairer to workers, less hostile to productive businesses, less obsessed with political villains, and more honest about where the money actually comes from.

The Easy Villain Problem

Right now, the political climate is full of easy villains.

Tax the gas companies. Tax the supermarkets. Tax the multinationals. Tax the banks. Tax the rich. Tax the landlords. Tax whoever the crowd is angry at this week.

Sometimes the anger is justified. There are bad actors. There are companies that play games. There are monopolies and duopolies. There are executives who earn absurd money while ordinary people cannot afford rent. There are multinational structures that make perfectly profitable-looking operations magically appear unprofitable in Australia.

But a villain is not the same as a solution.

That is the trap.

A politician can point at a big company and say, “They made billions and paid no tax,” and most people understandably get angry. But that headline often hides the actual mechanics. Company tax is not charged on revenue. It is charged on taxable income, which is broadly assessable income minus allowable deductions. Deductions include ordinary business expenses, depreciation, losses, and other rules designed to recognise that running a business costs money. The government’s own business guidance explains income tax for businesses this way: taxable income is calculated from assessable income less deductions. (business.gov.au)

That does not mean every zero-tax headline is innocent. It also does not mean every zero-tax headline is corruption.

Both things can be true.

The ATO’s corporate tax transparency report for 2023–24 found that 72% of entities in the corporate transparency population paid tax, while 28% did not. (Australian Taxation Office) Some of that is losses. Some of it is prior-year losses. Some of it is investment. Some of it is deductions. And yes, some of it can be aggressive tax planning that should be scrutinised hard.

The problem is that public debate usually skips the hard part. We go straight from “big number” to “evil company” to “new law,” and then everyone feels like something has been done.

But has anything actually improved?

That is the question we should be asking.

Business Tax Is Not as Simple as “Make Them Pay More”

My socialist friend would say companies need to pay their fair share.

I agree.

The argument is over what “fair share” actually means.

A company should not be able to extract money from Australia, use Australian workers, Australian customers, Australian infrastructure, Australian courts, Australian roads and Australian stability, and then contribute nothing back. That is not capitalism. That is freeloading.

But there is another side.

Do not bite the hand that feeds you is a crude phrase, but there is a truth in it. Private-sector jobs require viable private-sector businesses. Investment requires confidence. If you make Australia too hostile to investment, capital can go elsewhere. Not every business can leave overnight, of course. A gas field cannot be packed into a suitcase. But future investment, headquarters, intellectual property, skilled labour, expansion plans and risk capital can absolutely move.

Australia already has a two-tier company tax system. The full company tax rate is 30%, while the lower company tax rate is 25% for base rate entities, generally companies with aggregated turnover under $50 million and no more than 80% passive income. (business.gov.au) That is not nothing. Company tax is not “minuscule” either. In the 2026–27 Budget, company tax was estimated at $154 billion, compared with $382.4 billion from individuals and other withholding taxes and $103.2 billion from GST. (Australian Government Budget)

So company tax matters.

But personal income tax matters more.

That is where the public debate gets weird. We spend so much time yelling about companies that we miss the quiet machine taking more and more from workers every year.

That machine is bracket creep.

Bracket Creep: The Sneaky Tax Nobody Voted For

Before we talk about bracket creep, we need to talk about inflation.

Inflation is not the value of the dollar going up. It is the opposite. Prices rise, so the same dollar buys less. The RBA’s target is to keep annual consumer price inflation between 2% and 3%, because low and stable inflation helps people make decisions and avoids the damage caused when purchasing power gets eaten too quickly. (Reserve Bank of Australia)

A little inflation is normal in the system we have built. Too much inflation is painful. No inflation or negative inflation can also be a sign of a broken economy. The current issue is that inflation has been running above target. The ABS reported annual CPI inflation of 4.0% in the 12 months to May 2026, while wages rose 3.3% over the year to the March quarter 2026. (Australian Bureau of Statistics)

That means a lot of people are not imagining the squeeze. Prices have been rising faster than wages.

Now add tax.

If you earn $70,000 and get a 4% pay rise, you might feel like you should be keeping up with inflation. But if prices are also up around 4%, you are not really richer. You are just earning more dollars that are worth less.

But the tax system sees the higher number.

If tax brackets do not move with inflation, more of your income can be taxed at higher rates over time, even if your real purchasing power has not improved. That is bracket creep. The Parliamentary Budget Office describes bracket creep as rising incomes causing people to pay an increasing proportion of their income in tax even when tax settings have not changed. (Parliamentary Budget Office)

This is one of the most important fairness problems in the whole tax system.

It is not loud. It does not arrive as a new tax. Nobody announces it at a press conference. It just happens quietly in the background. You get a pay rise, the government gets a bigger cut, and then later politicians announce tax relief as if they are giving you a gift.

The government is currently reducing the 16% tax rate on income between $18,201 and $45,000 to 15% from 1 July 2026, then to 14% from 1 July 2027. Every taxpayer gets a tax cut of up to $268 from July 2026 and up to $536 from July 2027 compared with 2024–25 settings. (Australian Government Budget) That helps. I am not going to pretend money back in people’s pockets is bad.

But it does not fix the machine.

The machine remains: inflation pushes incomes up in dollar terms, brackets stay still, and workers gradually pay more.

The PBO has also pointed out that bracket creep has been a major reason personal income tax grows as a share of revenue. Personal tax has been the largest source of Australian Government revenue since 1942–43, and bracket creep increases reliance on it even further. (Parliamentary Budget Office)

That is why my first rule in a new tax system is simple.

No more bracket creep.

Index income tax thresholds to CPI automatically.

Not as a political promise. Not as a temporary election policy. Not as a one-off tax cut. Automatically.

If the government wants to raise more tax, fine. Make the case. Put the law forward. Vote on it. Defend it. But do not let inflation do the dirty work in silence.

The Funny Thing About Inflation and Fairness

Here is what makes this even more frustrating.

The government is already comfortable talking about inflation when it comes to capital gains. In the 2026–27 Budget, the government said it would replace the 50% capital gains tax discount with an inflation-based discount and introduce a minimum 30% tax on gains from 1 July 2027, with the stated logic that investors should only pay tax on real capital gains. (Australian Government Budget)

That principle is good.

But if we accept that investors should be taxed on real gains after inflation, then why should workers be taxed more heavily because their nominal wages rose with inflation?

That is the inconsistency.

If inflation matters when taxing assets, it should matter when taxing wages.

A fair system should distinguish between getting richer and merely needing more dollars to buy the same groceries.

Where the Money Actually Comes From

One of the best things we could do for public debate is force everyone to look at the tax split.

In 2026–27, the Budget estimated total taxation receipts of $737.1 billion. Of that, individuals and other withholding taxes were estimated at $382.4 billion, company tax at $154 billion, GST at $103.2 billion, superannuation fund taxes at $31.6 billion, and petroleum resource rent tax at $1.9 billion. (Australian Government Budget)

Put that into rough “per tax dollar” terms and the picture becomes clearer.

About 52 cents comes from individuals and withholding. About 21 cents comes from company tax. About 14 cents comes from GST. Around 4 cents comes from superannuation fund taxes. Petroleum resource rent tax is tiny in comparison.

That does not mean gas and resource tax should never be reformed. It does mean “tax the gas companies and everything will be fine” is not serious by itself.

Resource taxes can be smart. Economic rents should be taxed properly. If a company is making money from a resource that belongs to Australia, the public deserves a fair return. But pretending one villain tax will fix housing, wages, hospitals, roads, deficits and cost of living is just political theatre.

The budget is too big and the problems are too structural.

Tax Write-Offs Are Not Magic Free Money

As a business owner, I see this confusion all the time.

Someone hears “tax write-off” and thinks it means the government bought you something for free.

That is not how it works.

If a business buys a car, computer, server, camera, machine, tool or piece of equipment, that asset is used to generate income. It also wears out. It depreciates. The tax system recognises that because the business is not just sitting on pure profit. It is spending money to operate or grow.

Australia has specific small-business incentives for this. The 2026–27 Budget permanently extended the $20,000 instant asset write-off from 1 July 2026 for small businesses with turnover up to $10 million, allowing eligible assets costing less than $20,000 to be immediately deducted. (Australian Government Budget)

That is not a loophole.

The government wants businesses to invest. A business that buys productive equipment can make more money, hire people, serve customers, pay GST, pay wages, pay super, and eventually pay more tax.

Of course people abuse systems. Of course some deductions are questionable. Of course there should be enforcement. But the existence of deductions is not automatically proof of corruption. It is proof that profit is not the same thing as revenue.

The New Tax System I’d Invent

So here is my rough version of a better Australian tax system.

First, index personal income tax brackets to CPI every year. Also index the tax-free threshold, low-income offsets and relevant welfare thresholds properly. Stop pretending inflation-only wage rises are real wealth. If the government wants more revenue, make it ask openly.

Second, lower and simplify company tax for productive businesses, but get much tougher on economic rents and artificial profit shifting. I do not want a system that punishes a business for investing, hiring and growing. I do want a system that stops companies extracting monopoly profits, shifting profits offshore, abusing market power or using Australia as a customer base while pretending the profit happened somewhere else.

The Productivity Commission has been looking at this kind of trade-off. Its final corporate tax proposal involved lowering statutory company tax rates while introducing a net cashflow tax, with modelling suggesting it could increase investment, labour productivity and GDP while remaining revenue-neutral. (Productivity Commission) That is the type of thinking we need more of: not “companies good” or “companies evil,” but “how do we tax in a way that rewards productive investment and captures excess profits fairly?”

Third, make life easier for small businesses.

Right now, businesses generally need to register for GST once GST turnover reaches $75,000, and GST is 10% on most goods and services sold in Australia. (business.gov.au) That threshold is too low for the modern economy. It drags tiny operators into compliance systems before they are truly stable.

My aggressive pub-version policy would be no GST registration for businesses under $2 million in revenue.

The more realistic policy version would be: raise the GST threshold significantly, create a simplified GST option for growing small businesses, and remove as much BAS/admin pain as possible for businesses that are still owner-operated and cash-flow sensitive.

Yes, that would need modelling. Yes, it would create transition issues. Yes, you would need to stop businesses artificially splitting themselves to stay under the line.

But the principle is right.

Small business should not feel like it is being punched in the face every quarter just for trying to exist.

Fourth, stop taxing work like it is the easiest target in the room.

Work is productive. Wages are productive. Building a business is productive. Hiring someone is productive. Training someone is productive. Buying equipment is productive. Creating something useful is productive.

Our tax system should lean less on productive work and more on unproductive gains, economic rents, monopoly power, land scarcity and artificial structures that exist only to minimise tax.

That does not mean every asset owner is evil. It means the system should not punish the person working five days a week harder than the person who got rich because an asset inflated while they slept.

Fifth, give every taxpayer a receipt.

Not a vague pie chart hidden on a government website. A proper annual breakdown. You paid this much income tax. This much went to health. This much to aged care. This much to defence. This much to debt interest. This much to welfare. This much to infrastructure. This much to public servants. This much to states. This much was wasted, probably, but they will never admit that part.

The point is transparency.

People are less angry when they understand the trade-off. They are more angry when they feel robbed by a machine they cannot see.

The Real Fairness Test

The word “fair” gets abused in politics.

To government, fair often means stable revenue.

To workers, fair means being able to keep purchasing power.

To businesses, fair means being taxed on real profit without being punished for investing.

To my socialist friend, fair means companies and wealthy people contributing more so ordinary people are not crushed.

To me, fair means the system should reward productive behaviour, protect people from silent tax increases, and stop pretending that every problem can be solved by finding a villain.

So the fairness test should be brutally simple.

Does this tax change increase real wages, productivity, competition, supply, or household purchasing power?

Does it make the system simpler?

Does it make the government more honest?

Does it punish bad actors without damaging productive ones?

Does it raise revenue openly rather than by stealth?

If the answer is no, it is probably theatre.

And Australia has enough theatre.

The Point

The current Australian tax system is not completely broken. In a lot of ways, it works. We are not some failed state where nothing functions. We have institutions, watchdogs, rules, courts, auditors, tax enforcement and a mostly functioning public system.

But “mostly functioning” is not the same as fair.

Right now, workers are being squeezed by inflation, wages are struggling to keep up, and bracket creep quietly lets the government collect more without having to announce a tax rise. Businesses are told to invest, but also treated like enemies whenever politics needs a villain. Small businesses are buried in compliance. Big businesses can sometimes use complexity as a weapon. Politicians sell simple enemies because simple enemies are easier than structural reform.

So let’s invent something better.

Index tax brackets to inflation. Lower taxes on productive investment. Tax economic rents properly. Simplify GST and compliance for small business. Show taxpayers where the money goes. Stop using bracket creep as a stealth tax. Stop pretending company tax is either a magic solution or an evil burden. Stop writing laws for applause and start writing them for outcomes.

My socialist friend will probably disagree with half of this.

Good.

That is the point.

A better tax system will not be built by people who all think the same way. It will be built by people who can argue honestly, admit trade-offs, and still share a whiskey afterwards.

Because if we cannot even do that, we are not inventing a tax system.

We are just picking teams.

People are getting tired of certain types of writing.

Not just specific words. Not just individual phrases. Whole sentence structures. Whole rhythms. Whole little copywriting patterns that we have all become used to seeing online.

The kind of language that used to feel clear, polished, and professional now often feels strangely empty.

You read something and, before you even know why, your brain flags it.

It feels too smooth. Too familiar. Too neatly packaged. Too much like it has been passed through the same machine as everything else.

And the annoying part is that a lot of this language was never bad in the first place.

Most of these phrases became popular because they worked. They helped people structure ideas quickly. They made writing easier to scan. They gave online posts a nice rhythm. They helped writers create tension, move between points, and make ideas feel more digestible.

Then AI came along and swallowed the whole style.

Now the same phrases that once made writing feel sharp often make it feel stale.

The phrases were already everywhere

I am not separate from this either.

I have used these phrases forever. Most people who write online have.

“Game changer.”

“Let’s unpack this.”

“The future is here.”

“Move the needle.”

“This changes everything.”

“Here’s the thing.”

“But there’s a catch.”

These were not originally AI phrases. They were internet phrases. Marketing phrases. LinkedIn phrases. Newsletter phrases. Copywriting phrases. They were part of the language of online attention.

For years, people were taught to write in a way that was short, clean, and easy to skim. You had to hook people quickly. You had to make the point obvious. You had to create little moments of tension so people kept reading.

So these phrases became shortcuts.

They told the reader, “A point is coming.”

They told the reader, “This is the important part.”

They told the reader, “Here is the lesson.”

And for a while, they were useful.

The problem is that AI learned the same shortcuts.

It was trained on the writing that already existed online, and that writing was full of these patterns. Blog posts used them. Business articles used them. Brand websites used them. Startup founders used them. Marketers used them. Thought leaders used them. Everyone used them.

So when AI learned how to write in a way that sounded professional or persuasive, it naturally learned the phrases that had already been rewarded across the internet.

Then people started using AI to create more writing.

And AI kept reaching for the same familiar patterns.

Then those patterns became even more common.

Then they became exhausting.

AI did not invent bland writing

This is the important part, (See what I did there).

AI did not invent bad writing. Humans were already producing plenty of bland writing before ChatGPT showed up.

Corporate copy was already full of vague promises. LinkedIn was already full of dramatic hooks. Marketing websites were already telling every company they could “unlock growth” and “streamline workflows” and “drive meaningful impact.”

AI did not create that world. It just scaled it. That is why the fatigue feels so intense.

We are not just reacting to AI. We are reacting to the mass production of a writing style that was already becoming tired. Before AI, this kind of writing was annoying but manageable. You saw it in sales emails, business blogs, motivational posts, and startup landing pages.

Now it is everywhere.

It is in emails.

It is in captions.

It is in articles.

It is in job posts.

It is in product pages.

It is in internal updates.

It is in people’s personal brands.

It is in comments.

It is in places where nobody even needed polished writing in the first place.

The internet has always had a lot of filler. AI has just made the filler faster, cheaper, and more confident.

Why AI loves these phrases

AI is not using these phrases because it thinks they are beautiful. It is not sitting there with taste, intention, or judgment. It is predicting what usually comes next. And in a huge amount of online writing, what usually comes next is a familiar copywriting move.

A dramatic opener. A clean contrast. A neat transition. A confident takeaway. A tidy final line.

These patterns appear over and over because they have worked for humans before. They performed well. They sounded professional. They made posts more shareable. They helped people package ideas.

So AI treats them as safe options.

If you ask AI to write something “clear,” “professional,” “engaging,” or “thought leadership style,” it will often reach for the most statistically familiar version of that request.

That means you get the same phrases again and again.

Not because AI is trying to be annoying.

Because it has learned that this is what polished internet writing looks like.

The problem is that what looks polished to the model now feels overused to the reader.

There is a gap between what the machine predicts and what the human brain wants to feel. The machine is optimising for fluency. The human is looking for life.

The em dash became a victim

The em dash is a good example of this.

People now point to em dashes as if they are an obvious sign of AI writing.

Which is funny, because human writers have used em dashes forever.

They are useful. They create rhythm. They let you add an aside without fully starting a new sentence. They can make writing feel more conversational or more literary, depending on how they are used.

The em dash did nothing wrong.

But AI started using it constantly.

It likely picked it up because em dashes often appear in polished writing. Essays use them. Articles use them. Opinion pieces use them. Marketing copy uses them. Writers use them when they want to sound thoughtful, fluid, or slightly elevated.

So AI learned that em dashes are associated with “good writing.”

Then it started putting them everywhere.

Now, when people see too many of them in a short piece, they become suspicious.

The punctuation itself is not the issue. The overuse is the issue.

That is what has happened to a lot of phrases too.

A phrase can be useful once. It can be annoying when repeated too much.

And it can become unbearable when a machine starts injecting it into every possible context.

The brain gets tired

The reason this matters is because reading is not just about understanding words. It is also about feeling texture.

When every piece of writing has the same structure, the brain starts to disengage. It begins to recognise the pattern before it has processed the thought.

You see the hook coming. You see the contrast coming. You see the “takeaway” coming. You see the neat little closing line coming.

At that point, you are not really reading the idea anymore. You are reading the template. That is where the fatigue comes from.

It is not just that these phrases are overused. It is that they make the writing feel pre-decided. They make it feel like the conclusion existed before the thinking did.

And that is boring. Even when the content is technically correct, it can feel dead.

There might be a point in there somewhere, but it is buried under a layer of internet polish. The sentence is readable. The structure is clean. The grammar is fine. But the whole thing feels like it has no pulse.

The internet has developed an accent

There is now a kind of internet accent in writing.

You can hear it.

It starts with a punchy opening line. Then it gives you a short setup. Then it says something like, “But here’s the thing.” Then it adds contrast. Then it lands on a lesson. Then it ends with a sentence that sounds like it was designed to be screenshotted.

That structure is not always bad. Sometimes it is genuinely useful. There is nothing wrong with making writing clear or easy to follow.

The issue is that the accent has become too common. It is like stock music in YouTube videos. At first, you do not notice it. Then someone points it out. Then suddenly you hear it everywhere.

Once the pattern becomes visible, the effect is gone. The writing stops feeling like a person trying to communicate an idea. It starts feeling like a format trying to complete itself. That is what a lot of AI-assisted writing now feels like.

Not wrong. Not unreadable. Just strangely pre-chewed.

Writing differently is not a perfect escape

The obvious answer is to write differently.

Avoid the phrases. Break the patterns. Use stranger examples. Be more specific. Keep more of your actual voice in the piece.

That is all good advice. But there is a slightly cursed problem here.

As soon as enough people start writing differently, AI learns that too.

If everyone moves away from polished LinkedIn language and starts writing in a rougher, more casual, more obviously human style, the machine will absorb that style as well.

Then we will start seeing fake roughness.

Fake casualness. Fake personality. Fake typos. Fake “I just had this thought while walking my dog” energy.

That is the trap.

Style alone is not a permanent escape. AI can copy style. It can copy rhythm. It can copy roughness. It can copy the appearance of personality.

What is harder to copy is actual thinking.

Specific experience.

Real taste. A strange opinion. A personal frustration. A detail that could only come from someone who was actually there.

That is where the difference still lives.

The problem is not using AI

I use AI all the time.

Mostly for editing.

This article is a good example of how I think AI can be useful.

The raw version of this started as a messy thought. Basically a brain dump. It had typos, half-finished points, missing words, and the usual chaos that happens when the idea is moving faster than the typing.

That is normal.

A lot of good writing starts messy.

AI is helpful when it acts as an editor. It can help structure the mess. It can make sections clearer. It can smooth out a paragraph that is confusing. It can help turn a raw thought into something another person can actually read without having to decode your brain.

That is a win.

The thought is still yours. The angle is still yours. The frustration is still yours. The lived experience is still yours.

AI is just helping clean up the room.

The danger is when people skip the thinking part and ask AI to invent the whole thing from nothing.

That is when the writing starts to rot.

Empty prompts create empty writing

When you ask AI something broad like, “Write me an article about AI in business,” you are probably going to get a broad, generic answer.

That is not surprising.

There is no real point of view in the prompt. No specific experience. No tension. No argument. No personal observation. No reason for the article to exist.

So the model fills the space with the most available material.

And the most available material is generic internet language.

You get “AI is transforming the way businesses operate.”

You get “companies must adapt to stay competitive.”

You get “the future belongs to those who embrace innovation.”

You get all the usual filler.

Again, it is not technically wrong.

That is what makes it worse.

Bad writing that is obviously wrong is easy to reject.

Generic writing that is technically fine is harder to fight because it passes a basic quality check. It has a headline. It has sections. It has transitions. It has grammar. It has a conclusion.

But it does not really say anything.

It just performs the shape of saying something.

The junk drawer of thought leadership

This is why so much AI-generated business content feels empty.

It has all the signals of intelligence without much actual intelligence inside it.

There is structure.

There is confidence.

There is vocabulary.

There is a polished cadence.

But the piece often feels like it was assembled from the junk drawer of online business language.

A little bit of strategy.

A little bit of transformation.

A little bit of innovation.

A little bit of “fast-paced landscape.”

A little bit of “unlocking potential.”

A little bit of “the bottom line.”

And there you go.

You have an article.

Sort of.

The issue is that readers are getting better at sensing this. They may not be able to explain exactly why something feels AI-written, but they can feel the absence of a real person.

They can feel when the writing has no stakes. They can feel when the author is not risking an opinion. They can feel when there is no actual thought underneath the polish.

Some normal writing will get unfairly punished

The sad part is that a lot of normal human writing is going to get caught in the blast radius.

A human can use the phrase “game changer” sincerely. A human can write “the takeaway” because sometimes there really is a takeaway. A human can use an em dash because it fits the rhythm of the sentence.

Not every familiar phrase means something was generated by AI.

But the context has changed. Readers are more suspicious now.

Certain phrases carry baggage they did not carry before. They might still be useful, but they arrive with a little static around them.

That is what AI has changed. It has not made these words illegal. It has made them tired. And tired language is dangerous because it makes readers switch off before they have even reached the point.

The real fix is not avoiding every phrase

I do not think the answer is to make a giant banned list. That just creates a new kind of weird writing. You end up with people avoiding normal language so aggressively that the writing becomes awkward in a different way.

The goal is not to never use a familiar phrase again.

The goal is to know when you are using one because it is the right phrase, and when you are using one because you have stopped thinking.

That is the difference. Sometimes “the bottom line” is fine. Sometimes “here’s the thing” is fine. Sometimes a clean transition is useful. But if a piece is held together entirely by those phrases, there is probably not enough actual thought in it.

Write the messy version first

The better process is probably simple. Write the messy version first.

Get the actual thought out before you start polishing it. Do not begin with the template. Do not begin with the hook. Do not begin by asking AI to sound clever on your behalf.

Start with what you actually think. Start with the frustration. Start with the example. Start with the thing you noticed that made you want to write in the first place.

Then use AI after that if it helps.

Use it to organise. Use it to clean. Use it to make the argument easier to follow. Use it to find the section that is confusing. Use it to turn the raw material into something more readable. But do not let it replace the raw material.

That is the part people actually want.

AI can polish, but it cannot care

This is probably the real line.

AI can polish. It can structure. It can imitate. It can produce competent sentences forever.

But it does not care.

It does not get annoyed by overused phrases. It does not feel the boredom of reading the same hook for the thousandth time. It does not have taste in the human sense. It does not have that little internal reaction where you read a sentence and think, “Please, not this again.”

Humans do.

That irritation is a form of taste. And taste is becoming more important now, not less. Because when everyone has access to the same tools, the differentiator is not who can produce the most polished paragraph. The differentiator is who can tell when the polished paragraph is actually boring.

The copywriting shortcuts are cooked

So yes, the phrase fatigue is real.

The rot is real.

A lot of online writing now has a weird sameness to it, and AI has made that sameness much harder to escape.

But I do not think the answer is to panic every time we see an em dash or a familiar phrase.

The answer is to stop using these things as substitutes for thought.

A strong idea can survive a simple phrase.

A weak idea cannot be saved by a polished one.

That is the part worth remembering.

AI is useful when there is something real underneath it.

It is painful when there is not.

Use it to edit.

Use it to structure.

Use it to clean up the mess.

But make the mess yourself.

End of the day, write better.

Dakota and I went to see Disclosure Day, and I left the cinema with that very specific kind of irritation where you know the movie was not good, but also know the movie is not really what is bothering you.

The movie itself was dumb in that modern blockbuster way where everything is happening all the time, yet somehow nothing has time to breathe. It felt badly paced, overly serious, and weirdly convinced that if it kept sprinting, nobody would notice that the plan made no sense. Why would aliens need a human translator if they can alter a human being to translate for them anyway? Why go through all this trouble? Why is the giant alien physically compromised? Why does everyone accept the end of reality with the emotional depth of changing phone plans?

But this is not a movie review. Not really.

The movie annoyed me, sure. But what stayed with me was not the plot. It was the feeling around the plot. That strange, greasy sensation you get when fiction, politics, timing, media, and real-world events all start brushing up against each other in a way that makes you feel insane for even noticing.

The Weird Feeling

I want to talk about coincidences. Not because I think every coincidence is evidence of some master plan, and not because I want to become one of those people who sees a triangle in a movie poster and starts connecting it to the World Economic Forum, ancient Egypt, and his neighbour’s Wi-Fi password.

I mean the subtler kind of coincidence. The kind that does not prove anything, but still changes the atmosphere.

The timing around Disclosure Day felt weird. A big Spielberg alien disclosure movie arrives at roughly the same cultural moment as renewed public UFO/UAP disclosure language, government websites with alien branding, and official releases of UAP-related records. The U.S. Department of War’s PURSUE page says UAP records are being released in tranches, with releases in May and June 2026.

That does not mean the movie was planted. It does not mean Spielberg is doing predictive programming from a secret underground Amblin bunker. It just means the timing was strange enough to make the whole thing feel staged by reality itself.

And that is the part that gets under my skin.

Coincidence as a Mood

Some coincidences are just coincidences. Most of them, probably.

But coincidences do not have to be conspiracies to have an effect on people. They can still create a mood. They can still make the world feel scripted. They can still make you wonder whether you are reacting to reality itself or to a version of reality you have already been trained to recognise.

That, to me, is the interesting part.

We do not encounter major events as blank slates. We carry templates around with us. Pandemic. Alien invasion. Government cover-up. Nuclear standoff. Cyberattack. Civil unrest. Climate collapse. AI takeover. Each one already has a tone, a colour palette, a soundtrack, and a set of expected emotional reactions.

When something happens in real life, we do not process it raw. We instinctively ask, “What kind of movie is this?”

And once we know the genre, we know how to feel.

The Pandemic Example

COVID is the obvious example, because it is still recent enough that everyone remembers the weirdness of it, but far enough away that people are already reorganising their memories around whatever story suits them best.

Before COVID, there had already been years of public warnings about pandemics. Bill Gates gave a TED talk in March 2015 called “The next outbreak? We’re not ready,” arguing that the world needed to prepare for epidemics with better planning, research, and health systems. (TED) In October 2019, Johns Hopkins, the World Economic Forum, and the Bill & Melinda Gates Foundation hosted Event 201, a pandemic tabletop exercise based on a fictional scenario; Johns Hopkins described it as a training exercise for a hypothetical but scientifically plausible pandemic. (Johns Hopkins Center for Health Security)

Looking back, of course that feels eerie.

It does not mean those people caused COVID. Warning about a risk is not the same thing as creating it. Experts talk about pandemics because pandemics are real historical events and always have been. But emotionally, none of that fully removes the weirdness. When you remember seeing people talk about pathogens, preparedness, simulations, and global outbreak scenarios right before the real thing happened, it leaves a mark.

The rational part of your brain says, “That was public health forecasting.”

The paranoid part of your brain says, “That was a trailer.”

And even when the rational part wins, the paranoia does not fully shut up.

Preparation or Programming?

This is where the whole thing gets uncomfortable, because there is a difference between preparation and programming, but in practice they can look similar.

A society prepares for possible futures by imagining them. Governments run simulations. Experts model disasters. Filmmakers turn collective fears into stories. News outlets package uncertainty into repeatable images. Social media turns everything into memes before anyone has finished understanding it.

None of that requires a secret room full of people stroking cats and planning the next global plot twist. It can happen through culture alone.

But the effect is still real.

Media rehearses us. It gives us emotional muscle memory. It teaches us what the big event is supposed to look like before the big event happens. So when something does happen, part of us has already been there. We have seen the press conference. We have seen the panicked crowds. We have seen the lone whistleblower. We have seen the scientist ignored until it is too late. We have seen the government lie, then slowly admit a partial truth, then insist everyone stay calm.

By the time reality arrives, it is not unfamiliar. It is just the live-action version.

Real Life Does Not Imitate Art

That said, real life does not actually imitate art. Not properly.

Real life is much stupider.

Movies make mass revelation look clean. The truth drops, the world reacts, people cry, governments tremble, churches overflow, families embrace, humanity collectively stares into the sky and reconsiders its place in the universe.

In reality, half the population would not believe it, a quarter would make jokes, a chunk would immediately turn it into a partisan argument, and most people would still have to go to work the next morning.

That was one of the things that bothered me about Disclosure Day. Everyone folded way too quickly. The movie seemed to think that once the truth was revealed, people would naturally move into the correct emotional position. Shock, awe, fear, acceptance, unity. As if human beings have ever been that graceful.

We do not react to reality as one species. We react as tribes, fandoms, denominations, algorithms, markets, and comment sections.

If actual alien disclosure happened tomorrow, I do not think the world would become spiritually transformed. I think people would ask if the aliens were left-wing or right-wing. Someone would accuse them of being fake. Someone would try to sell alien protein powder. Someone would claim the Bible predicted it. Someone else would claim the aliens proved all religion false. A podcast would explain why the aliens were actually from Antarctica. The stock market would do something ridiculous.

And then, somehow, after three days, people would be bored.

The Religious Stuff

The religious element in the movie also annoyed me, because it felt like faith was being used as a shortcut rather than treated like something real people actually live inside.

A lot of alien stories do this. They treat religious people as fragile villagers whose entire worldview collapses the second something strange appears in the sky. It is such a lazy way to write belief. It assumes faith is just a lack of information, and that once a bigger piece of information arrives, faith automatically evaporates.

But that is not how religion works for most people.

A lot of religious traditions already contain enormous, non-human, cosmic categories. Angels. Demons. Principalities. Powers. Heavenly beings. Apocalyptic signs. Worlds seen and unseen. The idea that humanity is not the only intelligent life in existence is not automatically devastating to faith. For some people it might be. For others, it would be folded into an existing spiritual framework almost immediately.

That is what the movie missed. Faith does not always break under mystery. Sometimes mystery is the whole point.

The lazier version of the story is, “Aliens appear, religious people panic.” The more interesting version is, “Aliens appear, and every belief system on Earth tries to metabolise them.”

That would be much messier, and much more believable.

The Part That Actually Scares Me

The scary part is not aliens. It is not even government secrecy, although obviously that is its own bottomless pit.

The scary part is how easily perception can be softened in advance.

Not controlled completely. Not hypnotised. Just softened.

An idea starts as ridiculous. Then it becomes a movie. Then it becomes a news segment. Then it becomes a think-piece. Then it becomes a government phrase. Then it becomes a website. Then it becomes something your parents casually mention at dinner. Then, one day, it is just part of the background.

Nobody has to force you to accept it. They only have to make it familiar.

That is the machine I keep thinking about. The coincidence machine. The cultural process where the impossible becomes silly, then entertaining, then plausible, then bureaucratic, then normal.

By the time the event happens, you are not necessarily prepared in any meaningful moral or intellectual sense. You are just less surprised.

And maybe that is enough.

The Boring Explanation Is Still Weird

The boring explanation is that experts forecast risks, artists dramatise anxieties, governments use whatever language gets attention, and the public connects dots because human beings are meaning-making animals.

That explanation is probably true.

It is also still weird.

It is weird that pandemic exercises happened before a pandemic. It is weird that alien-disclosure entertainment arrives beside alien-disclosure politics. It is weird that media keeps giving us emotional rehearsals for disasters that later become real enough to make the rehearsals feel suspicious.

Again, not proof. Not a grand theory. Just weird.

And maybe that is the honest place to sit with it. Not in full conspiracy mode, but not in smug dismissal either. Because the people who dismiss everything as coincidence can be just as annoying as the people who think nothing is coincidence. Reality is usually more boring than conspiracy, but more suspicious than polite society wants to admit.

The Uneasy Middle

So no, I do not think every movie is a test balloon. I do not think Bill Gates caused COVID because he warned about pandemics. I do not think Spielberg made Disclosure Day because the government handed him a secret schedule of upcoming alien events.

But I do think powerful institutions, artists, experts, politicians, and media companies all swim in the same cultural water. They respond to the same fears. They anticipate the same crises. They borrow the same imagery. They turn the future into content before the future arrives.

Then, when the future does arrive, it feels like recognition.

Not because life imitates art.

Because art has already taught us how to recognise life.

That is the part I cannot shake. Not that fiction predicts reality perfectly. It clearly does not. Real people are too chaotic, stupid, funny, selfish, stubborn, faithful, cynical, and tired for that.

But fiction does give us the shape of events before we live through them. It hands us the symbols. It gives us the emotional presets. It tells us what kind of story we might be in.

And when the world starts using the same symbols back at us, it is hard not to feel like someone, somewhere, already saw the trailer.

My trusty old Honda Civic was falling apart in just about every visible way. The bumper was hanging off, there were mystery noises, and it had reached that stage where every new rattle made me wonder whether I should be concerned or just turn the music up.

But the engine still ran like a dream, so I could never quite bring myself to send it behind the barn.

Then, recently, I had an actual incentive to upgrade. Business tax, deductions, all the adult things that somehow make buying a car feel slightly less irresponsible. So off we went to explore car yards.

And honestly, the car shopping experience is an entire case study in sales psychology.

Car Salespeople Are a Different Breed

Car salespeople are a different breed.

Salespeople in general are, really.

I respect it, but I also dislike it, and I know I could never be that person. There is a particular confidence, persistence, and emotional stamina required to do that job well.

But the strategies they use, even when they are painfully obvious, are interesting. A lot of them translate directly into marketing, especially when you are dealing with high-value conversions where one sale can make the entire interaction worthwhile.

There were a couple of salespeople we met who seemed like they would rather have been on holiday. One or two even got a little frustrated with me and my dad for asking questions, looking around, and not immediately handing over a kidney as a deposit.

They were fine, but not exactly memorable for the right reasons.

The Very Salesy Car Yard

Then there was one car yard that was salesy.

Very salesy.

If you are on the Gold Coast, you probably know the one. It is the dealership that seems to be in every cinema ad before every movie. It has actually become a joke between me and Dakota, waiting for that specific ad to come on and mimicking the owner’s name before the movie starts.

Anyway, their process was fascinating.

First, find your prey.

The second you step onto the yard, someone appears and pulls you into conversation. Then they try to get your current car involved in the deal. One guy even tried to walk across the street to drive my car over to the dealership himself, which was both impressive and slightly alarming.

Then come the comfort plays.

Offer drinks. Make you feel welcome. Keep you there. Make the space feel less like a transaction and more like hospitality.

The Manager in the Back Room

After that, the negotiation starts around the high-ticket item.

The salesperson disappears, or pretends to disappear, to speak to the “manager.” Sometimes it is a phone call. Sometimes it is a quick walk away.

Suddenly, phrases start coming out like, “I think they’ll like that one,” or, “Let me see what I can do for you.”

The whole thing is designed to make you feel like they are fighting for you. Like you are not just being sold to, but advocated for. Like there is some hidden room in the back where deals are made, and your salesperson is bravely entering the battlefield on your behalf.

Then, if needed, the manager comes in.

That is when the question becomes, “What needs to happen for us to get this done today?”

And look, I get it.

This is the playbook. It exists because it works.

The Follow-Up Machine

But it does not end when you leave the yard.

If the trail goes cold, the follow-up begins. A text later that afternoon to keep the relationship warm. Usually something friendly, with a little hook.

Then a call two days later to “check in” and rekindle the conversation.

From a sales perspective, it is almost perfect.

For people who are swayed by constant communication, it works wonders. It creates the feeling that they care. It makes you think, “They remembered me. They are looking after me. They have my best interests at heart.”

Of course, they also want the sale.

That is not inherently evil. Businesses need to sell. Salespeople need to follow up. Marketing needs to bring people back to top of mind.

But the difference is in how it feels.

When the Tactic Backfires

For me, that approach did not work at all.

I did not answer the texts. I did not answer the calls. And honestly, I wished they would stop bothering me.

The whole experience left a bad taste in my mouth, especially because they had slightly bashed my old car in the process. I knew the Civic was not worth much. I was not delusional. But there is still a way to talk about someone’s car without making them feel stupid for owning it.

I left that dealership more frustrated than excited.

The Place That Actually Got the Sale

The place I actually bought from, GAC in Southport, handled it differently.

The salesperson was still a salesperson, of course. I am not pretending I wandered into a charity.

But he treated me like a human being.

He joked around. He let us drive the car without turning the process into a paperwork marathon. He made the experience feel easy, and most importantly, he made me feel like I had control over the final decision.

That matters.

By the end of it, I was happy. I was satisfied. I was excited to finally drive my new car, a Mazda 3 Touring, if anyone cares.

Same Goal, Different Experience

And that is the point.

Both sales approaches can work.

The aggressive follow-up, manager-in-the-back-room, “what can we do today” method works on some people. The relaxed, human, trust-building method works on others.

Neither is automatically wrong.

They are just built for different people, different demographics, and different buying behaviours.

What This Means for Marketing

That is where this translates into business and marketing.

Different markets need different strategies.

Texting and calling, with permission, can be incredibly effective. In health services, it makes sense. People need reminders. They need prompts to rebook. Sometimes the follow-up is genuinely beneficial for the client.

In agency work, constant communication is essential. Silence creates uncertainty.

A good CRM, a proper follow-up process, and a clear record of where each lead or client is at can be the difference between a lost opportunity and a closed deal.

Salespeople need their little Rolodex.

Or, more realistically, their CRM.

They need to know who is warm, who needs a reminder, who needs space, and who is ready to buy.

These things work.

Genuine Beats Salesy

But they work even better when they feel genuine.

And that is probably the crux of it.

Be genuine.

Not just “sales genuine,” where you learn someone’s name and repeat it back to them three times because a sales book told you to.

Actually genuine.

Care about the person. Care about the problem they are trying to solve. Care about whether the thing you are selling is actually right for them.

People can feel the difference.

The tactics might be the same on paper.

Follow up. Stay top of mind. Build rapport. Create comfort. Reduce friction. Ask for the sale.

But the delivery changes everything.

One version makes people feel like prey.

The other makes them feel looked after.

And in business, marketing, sales, or even just buying a Mazda on the Gold Coast, that difference is everything.

It is not a bad conundrum to be in. In fact, it is probably the best kind of business problem to have. The business is working. People want the work. Clients trust me. The projects are coming in. Most of the business has grown through word of mouth, reputation, portfolio work, and me selling myself as the person who can actually figure things out and get things done.

That is a good thing.

It means I have done something right.

It means people respect the work. It means people trust the thinking behind the work. It means I have become good enough at what I do that people seek me out as an individual, which is exactly what you want when you are building something from nothing.

But it also creates a very annoying problem.

At some point, being good at the work becomes the thing that traps you inside the work.

That is the stage I am sitting in now. I have enough work to keep everything ticking along. I have retainers. I have projects. I have development work. I have marketing work. I have enough happening that the business is not just some fragile little thing anymore. But the core problem is still there.

If I stop working, money slows down.

If I get sick, money slows down.

If I go on holiday, money slows down.

If I eventually want to retire, take a break, change direction, or simply not be glued to the machine every single day, the whole thing risks falling over because too much of it still depends on me personally doing the work.

That is not really a business.

That is a highly skilled job wearing a business costume.

And I do not mean that in a depressing way. There is nothing wrong with freelancing. There is nothing wrong with being a sought-after individual. There is nothing wrong with being the person clients trust. That is how Tomedia got here. That is how most good service businesses start. You become useful, then you become trusted, then people keep coming back.

But at some point you have to ask a different question.

How do I build something that does not collapse the second I step away from it?

That question has been sitting in the back of my head for years, but it has become much louder recently. I have been running Tomedia since 2019, which means I am now around seven years into this thing. That is still early, but it is also long enough to have experienced some patterns.

I have experienced what happens when I take a holiday and the business does not really make money while I am away. I have experienced what happens when I get sick and suddenly everything slows down because I am the person everything depends on. I have experienced the stress of knowing that the income is only stable while I am physically able to keep producing.

I do not want that forever.

I recently came back from Europe, and this trip was different. For the first time, I had enough retainer work in place that the business did not feel like it stopped the moment I left Australia. The retainers covered a good portion of the base costs. Project work could still continue. I could work while overseas when I needed to. It was not a perfect “proper holiday where I do absolutely nothing” situation, but it was a lot better than previous holidays.

That was a sign.

Not a complete solution, but a sign of what the solution could eventually look like.

The retainer side of the business is the easiest part to understand. Retainers are scalable in a way that project work is not always scalable. With retainers, I can be the authority. I can set the direction, explain the strategy, guide the marketing decisions, and decide why we are doing what we are doing. Then the actual implementation can be handed to someone else.

That is already starting to happen.

For SEO work, for example, I can own the thinking. I can say, “This is the strategy. This is why we are doing it. This is what matters.” Then someone else can help with the delivery. That works. That makes sense. That is scalable.

Not infinitely scalable, and definitely not cheaply scalable, but structurally scalable.

Eventually, the retainer side of Tomedia could have an account manager handling client communication, expectations, and relationships. Then underneath that, there could be skilled people handling the actual implementation: SEO, social media, ads, content, reporting, whatever else fits into the machine.

That version of the business makes sense to me.

The problem is getting there costs money.

If I had a proper team of four people working on retainers, that could easily cost somewhere around half a million dollars a year once you include wages, overhead, management, and breathing room. That means you need enough retainer revenue to justify it. You need enough clients. You need enough margin. You need enough stability that you are not hiring people off hope.

That is the difficult part.

The model is clear. The path is clear. The timing is not.

Then there is the software engineering side, which is a different beast entirely.

The software development work is highly profitable. It is also the work I trust the least to hand off.

That probably sounds bad, but it is the truth. I have tried outsourcing development before. I have paid junior developers. I have paid dev teams. I have spent a lot of money trying to get other people to build things properly, only to end up fixing the work myself anyway.

Bad code is expensive. Bad architecture is expensive. Poor thinking is expensive. Cowboy development is expensive.

And I have a deep distaste for cowboys in this industry.

The issue with development is that it is not enough for something to technically work. It has to be built in a way that makes sense. It has to be explainable. It has to be maintainable. It has to be something I can stand behind when a client asks how it works or why it was made that way.

That is hard to delegate.

I know it is possible. Eventually, software engineering can scale too. But I think it scales differently. External client development work is much harder to scale because every client has different requirements, different systems, different expectations, and different levels of chaos. Internal software development is much easier to scale because the team is working on the same product, the same codebase, and the same long-term objective.

That is where things get interesting for Tomedia.

Because I do not really want Tomedia to just become a big agency.

Big agencies are not always stable. Big agencies can become bloated. Big agencies can lose their quality. Big agencies can become machines that exist to feed themselves. In Australia especially, I do not think simply becoming a big agency is the dream. It might work for some people, but it is not the version of the future that feels right to me.

I want Tomedia to be more than an agency.

I want it to become infrastructure.

I want it to become a marketing authority. I want it to become a software company. I want it to become a publishing engine. I want it to become a place where internal products, client services, research, media, education, and tools all feed into each other.

That is the real shape of it.

The retainer side gives stability.

The development side gives high-value project work.

The software-as-a-service side gives scale.

The articles, books, zines, videos, and research give authority.

And the authority feeds everything else.

That is why Brainwaves matters. That is why the zines matter. That is why the Big Book of SEO matters. That is why writing articles matters. That is why building tools matters. At first glance, all of these things can look like random side projects, but they are not random. They are all part of the same long-term structure.

I am trying to build authority around myself and around Tomedia.

I need people to trust me online the same way they trust me in person. When people speak to me directly, they understand that I know what I am talking about. The challenge is expanding that trust beyond conversations, meetings, referrals, and existing clients.

Articles do that.

Books do that.

Videos do that.

Software does that.

Research does that.

Products do that.

They create proof. They create presence. They create ways for people to discover the thinking before they ever speak to me. And if that works, it can lead to more agency clients, more software users, more retainers, more product sales, and more opportunities that do not rely purely on me chasing work.

That is also where passive income enters the picture.

I do not think passive income is ever truly passive, at least not at the start. Everything requires work. Software requires building. Books require writing. Zines require production. Articles require editing. Products require marketing. Even a supposedly passive system needs maintenance, improvement, and attention.

But passive income, to me, is not really about doing nothing.

It is about building things where the money is not directly tied to the hour I just worked.

That is the goal.

If I write a book, it can keep selling after I finish writing it. If I build a software product, it can keep creating value after the first version is made. If I create a library of useful articles, they can keep attracting people long after the day I publish them. If I build a magazine or zine system, each issue becomes another asset in the ecosystem.

That matters.

The Big Book of SEO is a good example. It ended up being enormous. Around 400 pages. That is great because it means the thing has substance, but it also creates a practical problem: print-on-demand becomes expensive. A huge book costs a lot to print and ship. If the final price is too high, fewer people will buy it. So now there is another layer to figure out: pricing, markup, format, perceived value, and whether the book should exist as a premium physical object, a digital product, a smaller series, or all of the above.

That is the kind of problem I like, though.

It is a product problem.

It is not just “how do I get more client work?”

It is “how do I package what I know into something people can buy, use, learn from, and trust?”

That is a better problem.

The same thing applies to Brainwaves. I can talk endlessly. I can talk to a phone, a screen, a camera, or a microphone all day. This entire article started as a voice note. That is the easy part for me. The harder part is editing, packaging, distributing, and turning that thinking into something consistent.

That is why the video side has slowed down. I like making videos. I like talking. I do not like editing. Editing is the bottleneck. So eventually, that might be something I hand off. If I can talk and someone else can turn that into polished videos, then Brainwaves can become more than articles. It can become a YouTube channel, a podcast, a publication, a content engine, or whatever shape makes the most sense.

Again, the pattern is the same.

I own the thinking.

Someone else can help with the implementation.

That might be the actual business model hiding underneath everything.

Tomedia scales when I stop trying to personally do every task and instead build systems where my thinking guides the work.

That applies to retainers.

It applies to content.

It applies to publishing.

It applies to software.

It may eventually apply to development too, but only once the systems, standards, and internal quality control are strong enough that I can trust the output.

The long-term version of this is even more interesting.

In my head, the endgame is not just Tomedia serving external clients forever. The endgame is owning multiple businesses that all connect back into Tomedia. Those businesses generate their own revenue, then they use Tomedia for marketing, software, strategy, infrastructure, and growth.

The money starts flowing in a loop.

One business feeds another. Tomedia supports the businesses. The businesses fund Tomedia. The software supports the operations. The media builds the authority. The authority brings in more opportunities. The whole thing becomes less dependent on any one client, any one service, or any one version of me working nonstop.

That is the dream.

Not a giant agency.

Not a fragile freelance business.

An ecosystem.

A family-owned infrastructure company with media, software, services, products, and authority all supporting each other.

That will take time. Probably a lot of time. I know that. The retainer side needs more clients before it can support a proper team. The development side needs better internal systems before it can scale safely. The software-as-a-service side needs more marketing, and I need to get better at sales or eventually bring in someone who is good at sales.

That is another uncomfortable truth.

I am not naturally good at asking for money. I do not like sales. I do not like pushing. I do not like feeling like I am convincing someone to pay me, even when I know the work is valuable. I have undercharged in the past, and if I had not undercharged, I would probably be much further ahead than I am now.

But that is part of learning.

Pricing is a skill.

Sales is a skill.

Delegation is a skill.

Authority is a skill.

Building a business that does not depend entirely on you is also a skill.

That is where I am right now. I am not at the finished version of Tomedia. I am at the version where the shape is finally becoming clear.

The retainers are starting to show me what stability can look like.

The software projects are showing me where the high-value work is.

The publishing projects are showing me how much knowledge I have sitting in my head that can be turned into assets.

The zines, books, articles, and research are showing me how authority can be built slowly, one piece at a time.

And the holiday showed me what I want more of.

I want to be able to leave without the business collapsing.

I want to be able to get sick without everything stopping.

I want to be able to take a proper holiday eventually and know that money is still coming in, clients are still looked after, systems are still working, and the business is still alive without me having to manually hold every piece together.

Will I actually stop working one day?

Probably not.

I know myself well enough to know that I will likely be doing something until I die because I cannot sit still. I like building things. I like thinking through problems. I like making stuff. I like the chaos of it, even when it annoys me.

But I want the choice.

That is the real point.

I do not want to stop because I am forced to stop. I do not want to keep working because the entire structure collapses without me. I want to keep working because I enjoy it, because I am useful, because there are interesting things to build, and because Tomedia has become strong enough that my work is no longer the only thing holding it up.

That is the transition I am trying to make.

From worker to owner.

From freelancer to infrastructure.

From agency to ecosystem.

From “Tom does the work” to “Tomedia creates the machine that makes the work possible.”

And honestly, in theory, everything is going pretty well.

The zines are coming. The books are forming. The articles are continuing. The software is there. The retainers are becoming more stable. The bigger picture is starting to make sense.

Now I just have to keep building it.

One system at a time.

I was sitting in a kebab shop recently, thinking about something that the kebab shop itself probably does not care about.

Customer data.

Not in the creepy Silicon Valley sense. Not “let’s build a machine learning model to predict whether someone wants extra garlic sauce.” More basic than that. The kind of data a small food business already gets without even trying: a name on the order, a card payment, maybe the last four digits of the card, maybe a rough timestamp, maybe the items ordered.

That alone is enough to start asking interesting questions.

How many people come back? How often do they return? How much do they spend? Are they buying the same thing every time? Are the regulars keeping the business alive? Is the shop growing because of loyal customers, or is it surviving on random walk-ins?

For a kebab shop, repeat customers are probably one of the clearest signs that the product is good. If people keep coming back for the same kebab, same snack pack, same late-night feed, something is working. If nobody returns, that tells a very different story.

But then I had a second thought.

What happens when the person paying is not really “the customer”?

Say my girlfriend walks into the shop and buys kebabs for both of us using my card. The shop might see her name attached to the order, but the card details are mine. Or maybe I order, but she is the one who decided we were eating kebabs in the first place. Or maybe I pay, she chooses, and we both consume the product.

So who is the customer?

Me, because it was my card?

Her, because her name was on the order?

Both of us, because we made the decision together?

Or are we not two customers at all, but one tiny household unit showing up in the data as fragmented individual transactions?

The Problem With Individual Customer Tracking

This is where a simple kebab-shop thought becomes a much bigger marketing question: are businesses actually targeting the right person, or are they confusing the payer with the buyer, the buyer with the decision-maker, and the decision-maker with the user?

In marketing theory, these roles are often separated. The initiator is the person who first suggests the purchase. The influencer shapes the decision. The decider makes the final call. The buyer completes the transaction. The user consumes the product. Sometimes those are all the same person. In a family, couple, workplace, friendship group, or household, they are often different people.

That distinction matters because most customer data systems are built around individuals.

One email equals one customer. One phone number equals one customer. One card equals one customer. One account equals one customer.

But real life does not work like that.

Real life is messier. A family might share cards. A couple might alternate who pays. A parent might buy something because a child asked for it. A husband might pay for something his wife chose. A wife might pay for something her husband uses. A group of friends might have one person who always orders, even though the decision belongs to the group.

The transaction says one thing.

The household reality says another.

This is the hidden buying power of family units.

A business looking only at individual transactions might see three average customers. But underneath that, there might actually be one very valuable household. The husband buys lunch there on weekdays. The wife orders dinner there once a fortnight. The kids ask for it on weekends. The data may show three separate customers with average value, when the reality is one family unit with high lifetime value.

That creates a problem for marketing.

If the business only targets the person who paid, it might miss the person who influenced the purchase. If it only rewards the person whose card was used, it might undervalue the family unit. If it splits the value across too many individual profiles, it might underestimate the true loyalty of the household. But if it merges people too aggressively, it can become inaccurate, invasive, and just plain weird.

This is why the kebab shop example is funny, but also useful.

A kebab shop probably will not build a customer identity graph. It probably does not need to. But the same problem shows up everywhere once the product becomes more expensive, more emotional, or more tied to household decisions.

Cars. Holidays. Furniture. Insurance. Kids’ toys. Groceries. Restaurants. Streaming services. Education. Health products. Home improvement. Financial services.

In all of these categories, the person who pays is not always the person who decides.

Who Actually Makes Purchasing Decisions?

The gender dynamic makes this even more interesting, although it needs to be handled carefully. Historically, in many heterosexual households, men were more likely to be positioned as the primary income earner, while women often managed more of the household purchasing, planning, care work, and day-to-day family decision-making. That pattern is changing, but it has not disappeared.

Pew Research found that in the United States, 55% of marriages still have a husband as the primary or sole breadwinner, while 29% of marriages have both spouses earning roughly the same amount and 16% have a wife as the breadwinner. Fifty years earlier, husbands were the breadwinner in 85% of marriages, so the pattern has shifted dramatically, but the old model still exists in many households.

At the same time, women’s influence over purchasing is enormous. NielsenIQ reports that women control an estimated $31.8 trillion of worldwide spending, are projected to control 75% of discretionary spending in the next five years, and have 70–80% influence on all consumer spending. BCG similarly describes women as managing around $32 trillion in global spending and argues that many companies still fail to design products and services around women’s actual needs.

So the old lazy assumption of “market to the man because he pays” is not just outdated. It is commercially dangerous.

But the opposite assumption is also too simple. You cannot just say “market to women because women decide.” That still flattens the household into a stereotype. The smarter approach is to ask: what role does each person play in the purchase?

For a car, one person may care about price and finance. Another may care about safety, comfort, and practicality. The kids may influence the choice more than anyone wants to admit. For toys, the child may be the initiator and user, while the parent is the buyer, payer, and gatekeeper. For food, the decision might be driven by convenience, cravings, routine, budget, or who complained loudest that night.

Children are also not passive in household buying. Research reported by Marketing Charts, based on an NRF report, found that 87% of surveyed parents said their children influence purchase decisions. Almost half said children influence purchases specifically for the child, while more than one-third said children influence purchases for the whole household.

The Family Unit as an Economic Entity

That means “family purchasing power” is not just about couples. It is about households as decision-making ecosystems.

And this is where customer lifetime value becomes more complicated.

Normally, customer lifetime value is attached to an individual. How much does this customer spend over time? How often do they buy? How likely are they to return?

But in household-driven categories, individual CLV can lie.

Imagine a kebab shop has four customer records:

David: buys once a month.

Sarah: buys once a month.

Sarah using David’s card: appears as either Sarah or David depending on the system.

A family order: appears as whoever placed the order.

A basic report might say, “These are average customers.”

A household-level view might say, “This couple or household buys from us every week.”

That changes how valuable they are. It changes how you market to them. It changes whether you offer them a loyalty reward. It changes whether you should target them with individual meals, couple deals, family bundles, or catering offers.

The unit of value is not always the person.

Sometimes the unit of value is the household.

Two Customers in a Trench Coat

This is obvious in B2B. Companies do not usually treat every employee as a totally separate buyer. They understand the “account.” They know that a business customer has multiple stakeholders: the user, the buyer, the approver, the finance person, the executive sponsor.

But in consumer marketing, we often forget the same thing happens inside homes.

A household is basically a tiny buying committee.

The issue is that tracking this is hard.

The most basic idea is to use payment information. But even that has problems. A merchant should not be treating a visible card number as a customer identity system. PCI guidance recognises masking and truncation standards, with the first six and last four digits commonly accepted as the maximum display format across payment brands.

The last four digits alone are also a weak identifier. They can collide across different cards. Cards expire. Cards get replaced. People use Apple Pay, Google Pay, different accounts, business cards, partner cards, and shared cards. Payment tokenisation can help because it replaces sensitive card numbers with a unique token, but even then, a token usually tells you about a payment instrument, not the full human or household behind it.

So if a business wants to understand family-unit value, it needs to be careful.

There are a few possible models.

The first model is to keep everything individual. Whoever pays gets the value. This is simple, clean, and easy to report on. But it underestimates household behaviour. It might split one loyal family across multiple “average” customers.

The second model is to split value across known participants. If two people are known to be part of an order, each gets partial attribution. This can be more accurate, but it creates practical problems. What if I buy kebabs with my girlfriend today, alone tomorrow, and with a friend next week? What if the person I was with changes over time? What if the system keeps assigning influence to someone who is no longer part of my life?

The third model is to create a household or family unit above the individual customer profiles. This is probably the most useful for serious businesses. You still keep individuals separate, but you also recognise that some purchases belong to a shared unit. The household gets its own lifetime value, while each person keeps their own preferences, behaviour, and marketing profile.

That gives you three layers:

The individual.

The transaction.

The household.

This is much closer to reality.

But it only works if the data is collected ethically and transparently. In Australia, the Australian Privacy Principles govern the collection, use, and disclosure of personal information for organisations covered by the Privacy Act. The OAIC defines personal information broadly as information or an opinion about an identified or reasonably identifiable individual, and even inferred tastes and preferences from credit-card purchases or web browsing can be personal information.

In other words, “we are just doing analytics” is not a free pass.

The non-creepy version is not secretly guessing who lives with whom based on cards and order patterns. The non-creepy version is building systems where people willingly identify themselves because there is a clear benefit.

A restaurant might offer a family loyalty account.

A grocery app might let households share lists, points, and offers.

A streaming service might have profiles under one account.

A car brand might design messaging for different decision roles rather than assuming the man is the buyer and the woman is a passenger.

A toy brand might market fun to the child, trust to the parent, and value to the household.

A finance brand might stop only speaking to the “main account holder” and instead think about the couple or family making the decision together.

The strategic question becomes: who needs to believe in this purchase for it to happen?

Not just who pays.

Who initiates it?

Who researches it?

Who vetoes it?

Who uses it?

Who complains if it is wrong?

Who has to be emotionally comfortable before the purchase goes ahead?

That last one is underrated. In family purchases, the veto vote can matter more than the payment method. One person may technically be able to buy the thing, but if their partner hates the idea, the purchase dies. One person may not pay a cent, but their approval is essential.

That is why marketing to households requires more than demographic targeting. It requires role targeting.

A person is not valuable only because they spend money. They may be valuable because they unlock someone else’s spending. They may be the recommender. The organiser. The planner. The gatekeeper. The emotional decider. The person who turns “maybe” into “yes.”

Why This Matters More Than You Think

This is where businesses can make better decisions.

For low-cost, frequent purchases like kebabs, coffee, takeaway, or groceries, household tracking can reveal patterns around routine and occasion. A single person buying one kebab is different from a couple buying dinner every Friday. A family buying every Sunday night is different again. The marketing should reflect the occasion: solo convenience, couple treat, family meal, late-night craving, work lunch, post-gym meal.

For high-cost purchases like cars, appliances, renovations, or holidays, the business should assume multiple decision-makers until proven otherwise. The campaign should not only speak to the person with the card or the finance application. It should speak to the practical user, the emotional influencer, the safety-conscious parent, the budget keeper, and the person who needs to feel heard.

For child-related purchases, the user and buyer are usually different. That means the product needs two sales pitches at once. The child needs to want it. The parent needs to trust it. The household needs to justify it.

For subscriptions and recurring products, household identity can be the difference between misunderstanding churn and understanding value. One account might have multiple users. One cancellation might not mean one disappointed customer; it might mean a whole household has moved on.

The danger is that most reporting systems simplify all of this into clean but misleading numbers.

Customer A spent $400.

Customer B spent $180.

Customer C spent $90.

But what if A, B, and C are the same household?

What if B influenced most of A’s spending?

What if C is the child who determines where the family eats?

What if the person with the lowest direct spend is actually the most important person in the buying decision?

Data Is Fun. Reality Is Messy.

This is why data is fun.

It starts with a kebab shop and ends with the realisation that “customer” is not as obvious as it sounds.

A customer can be a person.

A customer can be a card.

A customer can be an account.

A customer can be a household.

A customer can be an invisible decision-making unit made up of people with different personalities, different motivations, different levels of influence, and different relationships to the final purchase.

The businesses that understand this will market better.

They will stop treating every payment as a single-person event. They will stop assuming the payer is the decision-maker. They will stop undervaluing the household member who influences but does not transact. They will build loyalty systems around real buying behaviour, not just clean database rows.

And maybe the kebab shop still will not care.

Fair enough.

But once you move beyond kebabs and into categories where the purchase is bigger, more emotional, more expensive, more shared, or more family-driven, this becomes extremely important.

Because sometimes your best customer is not one customer.

Sometimes it is two customers in a trench coat.

Sometimes it is a couple.

Sometimes it is a family.

Sometimes it is a household.

And if your data cannot see that, your marketing probably cannot either.

It is not the ambition that is confronting. Growth is part of leadership. What unsettles is the knowledge that if you do not succeed, your role disappears and with it, the team you built, the culture you repaired, and the trust you earned through consistency rather than rhetoric.

This is not just a professional moment; it is a deeply human one.

The Invisible Labour of Building Something That Works

Turning a low engagement, underperforming team into a highly functioning unit is not accidental. It takes time, emotional labour, courage, and an unrelenting commitment to people. It requires sitting in discomfort, having hard conversations, protecting staff when needed, holding them accountable when required, and slowly rebuilding belief.

When a successful team is viewed as something to be “restructured” without first being understood, it can feel as though the organisation values change over effectiveness, novelty over results.

There is a quiet grief in watching something that works be treated as though it is incomplete simply because it does not align with a new strategic narrative.

The Paradox of Strategy Without Context

Good business management demands evolution. Organisations must adapt, realign, and sometimes fundamentally re-strategise to survive. That is not the issue.

The tension arises when strategy is developed without context when decisions are made at a distance from the lived reality of the work. A role description created without deep operational understanding risks focusing on optics rather than outcomes, aspiration rather than execution.

Strategy without context can unintentionally erase value.

True business acumen asks harder questions:

• What is working, and why?

• What risks are we introducing by dismantling it?

• What is the cost not just financial, but cultural of destabilising a high-performing team?

Leadership Versus Authority

Good leadership is not defined by the power to redesign it is defined by the responsibility to listen.

Leadership recognises that people are not interchangeable parts in an organisational chart. Teams carry institutional memory, trust, and psychological safety that cannot be quickly rebuilt once broken.

As Simon Sinek reminds us, “A leader’s job is not to do the work for others, but to create an environment in which others can succeed.” When restructure becomes an end in itself, that environment can fracture.

Authority can mandate change. Leadership earns alignment.

When the Needs of the Team Are Outpaced by Transformation

There are moments when the needs of the organisation genuinely overtake the needs of the team. Markets shift. Funding models change. Scale demands different capabilities.

But those moments should be approached with clarity, honesty, and care not silence or surprise.

Good leadership acknowledges the human impact of transformation. It recognises that asking someone to compete for their own survival, while simultaneously disregarding the success they have delivered, creates moral injury not just professional disappointment.

The question is not whether organisations should change, but how they change.

The Quiet Test of Values

This experience becomes a test not just for the individual, but for the organisation.

Does success get recognised, or only reframed?
Is stability valued, or is disruption rewarded regardless of consequence?
Are people seen as assets to be developed, or obstacles to be redesigned?

For the leader applying for that next role, the reflection is sobering. You are asked to advocate for a future you may not shape, while standing on a past that seems suddenly invisible.

Yet there is strength in knowing what you have built. There is integrity in standing by a team that became successful because they were trusted, included, and led with intention.

And regardless of the outcome, that leadership does not disappear with a position description.

Because real leadership is not defined by title or structure it is defined by the people who would follow you again, without hesitation.

That is the clean version. The official version. The version that sounds neat when a central banker says it with a PowerPoint behind them. But the more I listened, the more I kept thinking that the actual problem is not whether the digital euro makes sense on paper. It does. The problem is whether normal people will care, trust it, or even understand why it exists.

The Bit Most People Don’t Think About: Bank Money Versus Public Money

Most people do not think about money as different types of money. Money is just money. You tap your card, the coffee appears, and you go on with your life. You do not stand at the register thinking about settlement rails, merchant fees, central bank liabilities, commercial bank deposits, or whether your payment is travelling through an American card network.

But there is a difference. Cash is public money. If you hold a €20 note, that is central bank money. It is money issued by the monetary authority. Your bank balance is different. If you have €20 in your bank account, that is commercial bank money. It is still money, but it exists as a claim on a private bank. For day-to-day life, that distinction does not really matter. For central bankers, it matters a lot.

This is the heart of the digital euro. Europe is looking at a world where cash is being used less, payments are becoming more digital, and private companies sit underneath more and more of the payment system. So the ECB is trying to answer a simple question: if cash is public money in the physical world, what is public money in the digital world?

That is actually a fair question. I do not think the question is stupid. If anything, it is probably overdue. The issue is that the answer they are building feels like one of those things that makes complete sense inside a policy room and then becomes a nightmare the second it has to explain itself to actual humans.

The Real Reason: Europe Does Not Want America Running Its Payments

The strongest argument for the digital euro has nothing to do with convenience. It is not really about making life easier for the person buying lunch. It is about sovereignty. Europe does not want to rely so heavily on Visa, Mastercard, PayPal, Apple Pay, Google Pay, and other non-European payment providers.

That sounds abstract until you look at the numbers. The ECB says card payments are the main electronic payment method in the EU, international card schemes accounted for about 61% of euro area card payments in 2022, and 13 euro area countries rely entirely on international card schemes for card transactions.

That is a real strategic weakness. If you are Europe, and a huge chunk of your payment infrastructure is dependent on American companies, that is not just a business problem. That is a power problem. Payment systems are not just pipes. They are control points. They are data points. They are leverage.

So I get why Europe is nervous. I get why they are looking at the current system and thinking, “Why do we not have a proper European alternative?” I get why the ECB keeps using words like resilience, autonomy, sovereignty, and public infrastructure. I just do not think those words are going to sell this to the average person.

Because the average person does not buy sovereignty. They buy convenience.

This Is Where The Sell Gets Weak

This is the annoying part, because I do understand the European argument. Visa and Mastercard have huge market power. Europe does not want private American payment systems becoming the default infrastructure for the European economy. In a world where geopolitics is getting nastier, that is not some paranoid fantasy. It is a real concern.

But now try explaining that to a normal person standing in a shop. They tap their card, it works, they leave. Their bank app works. Their phone works. Apple Pay works. Google Pay works. The card works. The merchant accepts it. The payment disappears into the background, which is exactly what good infrastructure is supposed to do.

So then Europe comes along and says, “We have created a digital form of central bank money to preserve monetary sovereignty in the euro area.” And the normal person hears, “The government has made another payment thing.”

That is the problem.

The digital euro might solve a real institutional problem, but it does not clearly solve a felt consumer problem. Those are not the same thing. Policymakers often forget that. A problem can be very real at the system level and still be completely invisible to the people expected to adopt the solution.

Australia Makes This Feel Even Stranger

This is where my Australian bias kicks in. In Australia, we already have a payment system that works pretty well from the consumer side. We have BSB and account numbers, PayID, Osko, card payments, instant-ish bank transfers, and a banking culture where sending money to another person is not some massive drama.

Australia’s New Payments Platform launched in 2018 as open-access infrastructure for fast payments, allowing households, businesses, and government agencies to make payments with near real-time funds availability on a 24/7 basis. PayID also lets people send and receive money using a mobile number, email address, ABN, or organisation identifier, which makes the whole thing feel normal rather than futuristic.

That is why, from an Australian mindset, a lot of this feels weird. If someone tried to sell Australians a digital Australian dollar directly connected to the Reserve Bank, with holding limits, no interest, merchant fees somewhere in the background, bank intermediaries, privacy assurances, and a government explanation about why this is good for the country, I think people would go ballistic.

The RBA and Treasury basically agree that Australia does not need this right now. Their 2024 report found there is no strong case for a retail central bank digital currency in Australia at this time, because Australia’s current payment system is working well and meeting people’s needs.

That is the sane answer. If the system already works for consumers, do not add a massive new layer unless the benefit is brutally obvious. And with the digital euro, I do not think the benefit is obvious to normal people yet.

To Be Fair, Europe Is Not Completely Behind

I was probably too harsh in my first instinct that Europe cannot do peer-to-peer payments properly. Europe does have instant payment systems, and the EU has been pushing instant credit transfers hard. The Instant Payments Regulation requires payment service providers that offer normal credit transfers to also offer instant credit transfers, and says the charges for instant transfers must not be higher than comparable ordinary transfers.

So the issue is not that Europe has no way to move money. The issue is fragmentation. Different countries have different systems, different banks have different experiences, and there is not one clean, universal, European-owned digital payment option that works everywhere in the euro area like cash is meant to.

Europe is not trying to invent “send money on a phone” from scratch. It is trying to create a universal public payment layer across a messy multi-country currency union. That is a much harder job than Australia’s situation, because Australia is one country, one currency, one banking system, one national payment infrastructure, and one population that already broadly understands how domestic bank transfers work.

So yes, I can see why Europe is trying to solve something bigger. But that also means the digital euro is not a simple consumer product. It is monetary plumbing. And monetary plumbing is almost impossible to make emotionally compelling unless the current plumbing breaks.

The €3,000 Limit Is Where It Starts To Feel Weird

One of the things mentioned was a €3,000 limit. The ECB tested hypothetical holding limits of up to €3,000 per person as part of technical analysis requested during the legislative process, but it specifically says this should not be treated as the ECB’s final position on the appropriate holding limit.

The digital euro would likely have holding limits. It would not pay interest. It would be linked to your bank account so that if you needed to pay more than you had in your digital euro wallet, the extra could be pulled from your commercial bank account. The ECB says these design choices are there to stop excessive deposit outflows from banks and preserve financial stability.

Again, I understand the logic. They do not want people pulling huge amounts of money out of commercial banks and parking it directly in central bank money, especially during a crisis. If everyone suddenly ran from bank deposits into digital euros, that could hurt banks, lending, and the broader financial system.

But from the layman’s perspective, this is where the whole thing starts to sound like a product designed by people who are trying to make it useful without making it too useful. You can have it, but not too much of it. You can use it, but it will not earn interest. It is like cash, but with limits. It is public money, but managed through private intermediaries. It is supposed to compete with private payment systems, but not so much that it threatens the banks.

That might be technically necessary. It still sounds ridiculous.

Free For Consumers Usually Means The Cost Is Hidden Somewhere Else

The digital euro is being pitched as free for basic use by individuals. That is important, because if you want consumers to adopt something, you cannot make them feel like they are paying for the privilege of using the government’s new money experiment.

But free for the consumer does not mean free. It means the cost moves somewhere else. The ECB says banks and payment service providers distributing the digital euro would be able to charge merchants, with price setting subject to a cap, while the Eurosystem would bear the cost of establishing the digital euro scheme and infrastructure.

That is the part I dislike. If merchants pay, the cost goes into prices. If banks pay, the cost comes out somewhere else. If the public sector pays, taxpayers eventually pay. Nothing is free. The only difference is whether the cost is visible.

And this is not a small infrastructure project. The ECB estimates total development costs of around €1.3 billion until first issuance, with annual operating costs projected at around €320 million from 2029. It also estimates the euro area banking sector would need to invest between €4 billion and €5.8 billion in total.

Maybe that is worth it. Maybe payment sovereignty is worth billions. But then say that honestly. Do not dress it up as if this is just a free little wallet that helps people pay for coffee. This is a political and monetary infrastructure project. It should be judged like one.

Why Not Just Build A European Visa?

The question that kept sitting in my head was this: if the actual problem is Visa and Mastercard, why is the solution a new form of digital central bank money?

Why not build or back a proper European card network? Why not create a cheaper, stronger, European-owned alternative that banks can plug into, merchants can accept, and consumers do not even need to think about? If the issue is the rail, fix the rail. If the issue is American dominance in payment infrastructure, build European payment infrastructure.

That feels cleaner to me. It does not require convincing the public to understand central bank money. It does not require a new wallet concept. It does not require turning monetary sovereignty into a consumer-facing brand campaign. It just gives the banks and merchants another option, hopefully cheaper and more sovereign than the existing ones.

Now, I know the ECB would probably say the digital euro can support private European payment systems rather than replace them. It talks about co-badging, existing wallets, and the digital euro acting as a fall-back that allows pan-European reach while preserving domestic and regional schemes.

That is fine in theory. But this is where the complexity starts eating the idea alive. The digital euro becomes a currency, a wallet, a payment rail, a public fallback, a sovereignty tool, a competition tool, a cash replacement that is definitely not a cash replacement, and an innovation platform all at once.

That might be brilliant architecture. It is a terrible story.

The Surveillance Fear Will Not Just Disappear

The ECB is very clear that the digital euro would not be programmable money. It says public authorities would not be able to limit where, when, or to whom people can pay, and that the Eurosystem would not identify people based on their payments. Offline payments are meant to have a more cash-like level of privacy, where only the payer and payee know the personal transaction details.

That is good. It matters. The lazy version of the argument is to just scream “China” at anything digital and government-backed, which is not useful. The European legal framework is not the Chinese state, and pretending they are the same thing is just bad analysis.

But trust is not built by saying, “Do not worry, we have designed it safely.” Governments everywhere have spent years training people to distrust digital systems. Digital identity. Tax portals. Health systems. Banking restrictions. Online speech laws. Surveillance powers. Emergency rules that somehow become permanent. People are not insane for being suspicious when the state says it wants a new digital layer sitting around money.

That does not mean the digital euro is secretly a control system. I am not saying that. I am saying the fear is predictable. If you build a complex government-backed digital money system that normal people do not understand, you create the perfect environment for suspicion. And once suspicion gets in, it does not matter how many technical papers you publish. The public argument has already moved somewhere else.

The Bigger Problem Is Complexity

This is the bit that keeps annoying me, because it is bigger than the digital euro. We keep building systems that are so complicated normal people cannot understand them, and then we act shocked when normal people either ignore them or become paranoid about them.

Money is complicated. Tax is complicated. Payments are complicated. Energy is complicated. Housing is complicated. Climate policy is complicated. Digital identity is complicated. Banking is complicated. Government is complicated. Every solution creates another layer, and then that layer creates new problems that require another solution.

Eventually, society becomes a giant machine that only specialists can understand. The average person is still expected to vote on it, trust it, comply with it, pay for it, and live under it. But they cannot actually understand the thing itself without dedicating years of their life to it.

That is not a healthy place for democracy to be. It creates two classes of people: the people who understand the machine, and the people who are trapped inside it. Then the people trapped inside it become angry, confused, cynical, or easy to manipulate. Then the experts call them stupid. Then the public stops trusting the experts. Then politics gets worse. Then the system becomes even more defensive and more complex.

That is the loop. We are living inside it.

I Understand The Digital Euro. That Is Why I’m Still Not Sold.

The frustrating part is that I cannot just say the digital euro is stupid. That would be easy, but it would be wrong. Europe has identified a real problem. Its payment system is too dependent on non-European providers. Cash is declining. Digital payments are becoming normal. Public money needs some kind of future in a digital economy. A universal euro-area payment option could genuinely improve resilience.

So yes, I understand the point. I understand the reason. I understand why central bankers care about this. I understand why Europe does not want American companies sitting underneath the everyday payment behaviour of hundreds of millions of people.

I just do not like the shape of the solution yet.

The best version of the digital euro is actually useful. It becomes digital cash. It works across Europe. It works online and offline. It protects privacy. It gives Europe a public fallback if private payment systems fail. It does not replace cash. It does not become programmable money. It does not punish merchants. It does not become another half-broken government tech project that everyone is forced to pretend works.

The worst version is also easy to imagine. Banks spend billions. Merchants get another thing to support. Consumers do not care. Politicians overpromise. Privacy fears explode. Adoption is weak. The public gets lectured about strategic autonomy while still just tapping their Visa card because it is easier.

That is the risk.

The Final Problem: Normal People Do Not Adopt Monetary Architecture

This is where I land. The digital euro might be necessary as infrastructure, but it is being talked about like a consumer product. That is the mismatch.

Normal people do not adopt monetary architecture. They adopt convenience. They use what is easy, what is trusted, what is already there, and what does not make their life harder. If the digital euro cannot beat that test, it will not matter how elegant the policy logic is.

Europe’s best argument is not that the digital euro is innovative. It is not that it is modern. It is not even that it is sovereign, because most people do not emotionally connect with that word.

The best argument is this: cash needs a digital equivalent, and Europe should not rely entirely on private foreign payment systems for everyday money movement.

That argument makes sense. I can respect that argument. I might even agree with it.

But if Europe wants people to use the digital euro, it needs to stop sounding like a central bank committee and start answering the only question normal people actually care about:

Why would I use this instead of what already works?

I’m currently studying in Europe, learning about the EU and how its systems work, sitting in a German classroom while an economist with a heavy accent talks through European Union policy.

And he said something that I think I have been ignoring for a while.

Not because it is unimportant, but because I dislike politics. I dislike polarisation. I dislike the noise. I dislike the way every political conversation now seems to turn into people yelling at each other from opposite ends of the room.

But there is something becoming pretty hard to ignore.

The political centre is dying.

It Is Not Just the Far Right

At first, I was thinking about this as a far-right thing.

Because, obviously, the far right is popping up everywhere. In Australia, that looks like Pauline Hanson’s One Nation, Katter’s Australian Party, and the Trumpet of Patriots/Australian Federation Party situation, or whatever old mate Clive Palmer’s political orbit is calling itself at the moment.

In Germany, it is the AfD, Alternative für Deutschland. And they are not some tiny fringe party sitting in the corner anymore. In the 2025 German federal election, the AfD came second nationally, winning 20.8 per cent of the second vote and 152 seats in the Bundestag. Die Linke, Germany’s major left-wing party, also increased its vote, winning 8.8 per cent and 64 seats. So the interesting thing is not just that the right is rising. It is that the edges are getting louder while the centre looks weaker.

That is the part I find more interesting.

Because it is not only the far right. The far left is loud too. Not always in the same way, and not always with the same level of electoral success, but culturally, socially, and politically, the extremes are much harder to ignore than they used to be.

The middle just feels tired.

When the Centre Starts Looking Nervous

In Germany, the current governing coalition is between the centre-right CDU/CSU and the centre-left SPD. The coalition agreement was formally signed in May 2025.

In rough Australian terms, it is not a perfect comparison, but it feels a bit like the Liberals and Labor having to work together while a One Nation-style party becomes too big to ignore.

That is wild.

When centre parties have to hold hands just to stop the edges from taking over, it probably means people are not exactly thrilled with the centre anymore. The old “normal” parties feel stale. They feel slow. They feel disconnected. They feel like they are still trying to solve today’s problems with yesterday’s language.

And people are getting sick of it.

The Centre Is Boring, and That Is Its Problem

The centre has one major issue: it is boring.

That is not always a bad thing. In fact, boring politics is probably what a healthy country should want most of the time. Roads get built. Budgets get managed. Schools stay open. Hospitals function. People argue about tax policy without wanting to destroy each other.

That sounds pretty good, honestly.

But boring politics does not work when people feel like their lives are getting worse.

When people feel ignored, broke, anxious, culturally displaced, or politically powerless, boring starts to feel like betrayal. The centre says, “Be patient.” The extremes say, “You are right to be angry.”

And anger is a lot more emotionally satisfying than patience.

The Globalisation Hangover

In my mind, a lot of this comes down to globalisation, and the ever-increasing connection between cultures, economies, values, and political systems that were never really designed to coexist this closely.

Globalisation made the world smaller. It made goods cheaper. It opened up opportunities. It let countries trade, cooperate, and grow.

But it also left a lot of people feeling like their own country was no longer being run for them.

That is just my opinion, obviously. I am a pretty isolationist sort of dude. I believe Australia should focus on itself before it focuses on everyone else. We have enough land, enough resources, and enough potential to support ourselves before constantly throwing ourselves into the global landscape.

Australia first. Industry here first. Build here first. Then worry about everything else.

Otherwise, how are we ever meant to grow?

Insert the irony of “the lucky country” here.

The Left and Right Are Angry About Different Things

The far right and far left are not angry about the same things, but they are both angry.

The far right tends to look at immigration, national identity, globalisation, crime, borders, culture, and sovereignty. It says the nation has been weakened, outsiders have been prioritised, and ordinary citizens have been forgotten.

The far left tends to look at capitalism, inequality, housing, climate, corporate power, billionaires, war, and exploitation. It says the system is rigged, the rich are protected, and ordinary people are being crushed.

Different enemies.

Same emotional engine.

Both sides tell people that the current system is broken. Both sides tell people that the centre has failed. Both sides tell people that compromise is weakness.

And that is where things start getting dangerous.

The Horseshoe Starts to Make Sense

This is where the horseshoe theory starts to make a bit more sense to me.

Not in the lazy way where people say, “the far left and far right are exactly the same,” because I do not think that is true. They are clearly different. They care about different things, use different language, blame different groups, and imagine very different futures.

But they are often staring at the same problems.

They are just standing on opposite sides of them.

Take globalisation, for example. To a lot of people on the right, globalisation is a national issue. It is about borders, sovereignty, immigration, local jobs, local industry, and whether a country still has control over its own future. From that angle, globalisation looks like a force that weakens the nation and makes ordinary citizens feel like they have been pushed to the side.

But to a lot of people on the left, globalisation is an economic issue. It is about inequality, billionaires, corporate power, outsourcing, wage pressure, housing, the cost of living, and the feeling that regular people are being crushed while the people at the top get richer.

Different language.

Same wound.

That is what I find interesting. I might look at globalisation and think about Australia losing industry, relying too heavily on imports, and forgetting how to build things for ourselves. That feels like a right-wing concern because it is about national self-reliance, industry, and putting Australia first.

But then the consequences of that feed directly into things the left talks about all the time. Fewer secure jobs. More pressure on wages. Higher costs. More power for massive corporations. More wealth being pulled upwards. More people feeling like they are working harder just to fall further behind.

So is that a right-wing issue or a left-wing issue?

Maybe it is just an issue.

That is the part we seem to forget. A lot of people are not actually as different as they think they are. Most people want a country that works. Most people want stable jobs, affordable housing, safe communities, decent healthcare, fair opportunity, and some sense that the future is not completely cooked.

The disagreement is not always about the problems.

It is about the diagnosis.

It is about who gets blamed.

It is about what kind of solution people are willing to accept.

The right might say the problem is that the nation has been weakened. The left might say the problem is that the economic system has been captured by the rich. But underneath both of those arguments is often the same basic feeling: ordinary people have lost control.

And maybe that is why the centre is struggling so badly.

Because the centre keeps trying to manage the system, while the edges are arguing that the system itself is broken. One side says the country has been sold out. The other says the working class has been sold out. And honestly, depending on how you look at it, both might be pointing at parts of the same thing.

That does not mean the far left and far right are equally correct. It does not mean their solutions are equally good. It definitely does not mean the consequences of those ideas are the same.

But it does mean we should probably stop pretending everyone on the other side is insane.

Because when you strip away the slogans, the flags, the hashtags, the culture war nonsense, and the constant screaming, a lot of people are just angry that life feels harder than it should.

And maybe we are not as different as we think.

Maybe we are just being trained to argue with each other instead of asking why so many people feel abandoned in the first place.

Everyone Is Getting Louder

The problem is that when the edges get louder, everyone else gets dragged into the noise too.

The far right gets louder.

The far left gets louder.

Then the centre-left and centre-right panic and start copying bits of their language to win voters back.

Then politics becomes less about solving problems and more about proving which side you are on.

Because the extremes are getting louder, everyone becomes more aggressive.

Because everyone becomes more aggressive, instability rises.

Because instability rises, people start looking for simple answers.

And simple answers are dangerous, because the world is not simple.

A World That Feels Like It Is Burning

Honestly, is any of this polarisation really that surprising?

We have wars and conflicts constantly appearing across the world, left, right, and centre. And it is not like that is new. Humans have always had war. We just choose to focus on the ones that make us feel powerful, suit an agenda, or fit neatly into the media cycle.

Then we ignore the ones we do not care about.

Ukraine is still at war, but for a lot of people it has already slipped into the background. Not because it stopped mattering, but because the next disaster came through and took the spotlight.

That seems to be how we work now.

Tragedy becomes content.

Conflict becomes a headline.

Then the world scrolls on.

We Are Terrible at Caring for Long

We are a pretty disappointing species sometimes.

Not because people are evil, necessarily. I do not think most people are. But we are selfish, distracted, emotional, tribal, and very good at convincing ourselves that the suffering we are not looking at does not really exist.

We care intensely for about five minutes.

Then the next thing happens.

Then the next thing.

Then the next thing.

And somewhere in the middle of all that, people start losing faith in the systems that are meant to hold everything together.

That is where the extremes thrive.

Why Extremes Start to Sound Attractive

Maybe that is the part that bothers me most.

It is not just that extreme politics are rising. It is that people seem to be losing the ability to sit with complexity. Everything has to be simple. Someone has to be blamed. Someone has to be the enemy. Someone has to be the reason life feels harder than it used to.

And when people are scared, tired, broke, angry, or ignored, simple answers become very attractive.

That is what I think is happening.

The world is changing faster than people can emotionally process. Countries feel less in control. People feel less secure. The old centre parties feel stale, slow, and disconnected. So voters start looking further left or further right for someone who sounds angry enough to do something.

Whether those people can actually fix anything is another question entirely.

The Death of the Middle

This is why I think the real story is not just the rise of the far right.

It is not even just the rise of the far left.

It is the death of the middle.

The centre used to be where politics went to calm down. Now it feels like where politics goes to die. It looks too slow for people who want change, too weak for people who want control, too compromised for people who want purity, and too polite for people who want a fight.

So the edges grow.

Not necessarily because they have better answers, but because they sound like they actually believe what they are saying.

That matters more than people want to admit.

But Anyway, Germany Is Beautiful

And yet, here I am.

Sitting in Germany, learning about the EU, thinking about global instability, the rise of the far right, the loudness of the far left, war, polarisation, and the general moral failure of the human race.

But Germany is beautiful.

And for the first time in a while, I am enjoying sitting back, relaxing, and watching the world from somewhere else.

Maybe that distance is what makes all of this feel clearer.

Or maybe it just makes the world look even stranger.

I’ve been building a Bible app for the past couple of weeks as a hobby project, call it a calling. Somewhere between code, theology, and curiosity, I stumbled into something I genuinely wasn’t expecting. I was working through a dataset called BibleData, building out a “laws toolkit”, something that lets you explore biblical laws, their verses, and how those laws are interpreted. Clean, structured, almost mechanical.

And then I hit something that didn’t feel mechanical at all.

One verse. Two laws.

Same Hebrew. Same Greek. Same source text. But two completely different commands.

That alone was enough to make me stop. So I dug.

The Verse That Started It

Leviticus 25:14 reads simply enough: “If you make a sale… you shall not wrong one another.” On face value, it’s straightforward. Be fair. Don’t rip people off. Move on.

But Jewish interpretation doesn’t stop at face value. It pulls Scripture apart, examines it, and asks what is being said beneath what is being said.

From that one line, two commandments are drawn. One is a positive command, to conduct business fairly and rightly. The other is a negative command, not to exploit or distort value in a transaction.

Same verse. Two directions.

Not just “don’t do wrong,” but “actively do right.”

Where It Got Personal

That’s where it stopped being theoretical.

Because I run a business. And like a lot of founders, I don’t overcharge. If anything, I undercharge. I’ve always framed it as strategy, positioning, relationship-building, getting ahead by being more accessible than competitors.

But I’ll be honest. There was a moment where I paused and asked a question I’ve never really asked before.

Am I doing something wrong?

Not in a dramatic, “I’m going to hell” sense. But in a quieter, more uncomfortable way. The kind of question that doesn’t accuse you, but doesn’t let you move on either.

The Problem With Surface-Level Thinking

The easy reading of that verse is about avoiding obvious wrongdoing. Don’t scam people. Don’t manipulate pricing. Don’t exploit someone who doesn’t know better.

But the deeper reading isn’t just about behaviour, it’s about alignment.

Because “wronging someone” isn’t limited to overcharging. It’s about distorting what is true in a transaction. It’s about misrepresenting value, whether that distortion moves upward or downward.

We’re very comfortable calling out overcharging. It’s visible, aggressive, easy to label. But undercharging tends to slip through unnoticed because it feels virtuous. It looks like generosity. It looks like humility.

But that doesn’t automatically make it truthful.

The Other Side of the Coin

If overcharging is a distortion of value upward, then undercharging can be a distortion downward.

Both move away from what is real.

That’s the part that hit me. Not as a condemnation, but as a correction. Because when you strip away the surface-level framing, undercharging isn’t always about kindness. Sometimes it’s about avoidance. Sometimes it’s about not wanting to justify your worth. Sometimes it’s about protecting yourself from rejection.

It’s easier to be accepted when you’re cheaper.

And that’s not a pricing strategy.

What the Standard Actually Is

The biblical framework isn’t built around being cheap or expensive. It’s built around being truthful.

Throughout Scripture, especially in the Old Testament, there’s a repeated emphasis on honest weights and measures. That wasn’t just about physical scales, it was about integrity in exchange. What is presented should match what is real.

In a modern context, we don’t use scales. We use branding, positioning, perceived value, and pricing models. But the principle hasn’t changed.

The question isn’t whether you’re charging more or less than someone else. The question is whether your pricing reflects truth, or whether it’s shaped by something else entirely.

A More Uncomfortable Realisation

If I’m being completely honest, not all of my undercharging has been strategic.

Some of it has been fear. Fear of losing the deal. Fear of being questioned. Fear of not being “worth it.” And fear has a way of disguising itself as wisdom if you let it.

That doesn’t mean every discounted price is wrong. Strategy is real. Market positioning is real. There are valid reasons to adjust pricing.

But when the underlying driver is misalignment, when you know the value and choose to present something else, that’s where it starts to drift.

Not into obvious wrongdoing, but into something quieter. Something slightly off.

The Quiet Conclusion

I didn’t walk away from this thinking I’d been sinning in some overt, measurable way. But I also didn’t walk away unchanged.

What shifted wasn’t my pricing model. It was my awareness.

Because the verse doesn’t just sit there as an ancient rule about transactions. It asks something much sharper. It asks whether what you present to the world is aligned with what is actually true.

And that applies far beyond business.

Final Thought

We tend to measure ourselves against obvious failures. We avoid the big, visible mistakes and assume that means we’re on the right track.

But Scripture has a way of cutting deeper than that. It doesn’t just deal with what is clearly wrong. It deals with what is subtly misaligned.

And sometimes the difference between the two isn’t loud.

It’s just honest.

It’s not.

Because if you dropped most CEOs into a different system with different incentives, they’d behave differently overnight.

The system is doing exactly what it was designed to do.

And right now, it’s designed for the short term.

We Reward Short-Term Thinking — Then Act Surprised When We Get It

Executives are measured on:

• 12-month performance

• 2–3 year contracts

• Annual bonuses tied to financial outcomes

• Share price movements reacting in real time

And somehow we expect them to think in decades?

That’s not leadership failure.

That’s incentive alignment.

As Harvard Business Review has consistently pointed out, short-termism isn’t accidental it’s structurally embedded in how modern corporations operate.

So let’s call it what it is:

We built a system that rewards short-term wins and punishes long-term thinking.

Meanwhile, the Real Problems Are Just Being Deferred

If you’ve ever worked in asset-heavy environments, you already know how this plays out.

• Maintenance gets pushed

• Lifecycle plans get watered down

• Capital programs get delayed

• Risk gets “managed” on paper

Until one day it isn’t.

The International Organization for Standardization through ISO 55000 is very clear:

You must balance cost, risk, and performance over the long term.

But in practice?

We optimise for this year’s numbers and let the future absorb the impact.

We’re not removing risk.
We’re just moving it forward.

Ownership Has Drifted So Has Accountability

There was a time when the people making decisions were the same people who lived with the consequences.

That’s not the world we operate in anymore.

Ownership now sits with:

• Super funds

• Institutions

• Passive investors

Executives rotate through.

Boards change composition.

And the organisation keeps moving often without true long-term accountability.

The Organisation for Economic Co-operation and Development has flagged this exact issue in modern governance structures:

When ownership is dispersed, long-term accountability weakens.

And when accountability weakens, short-term thinking fills the gap.

We Celebrate the Wrong Things

In Australia, we celebrate:

• Fast growth

• Turnarounds

• Cost-cutting

• “Transformation” in 18 months

We don’t celebrate:

• 15-year capital discipline

• Infrastructure resilience

• Quiet, consistent stewardship

No one writes headlines about:

“Organisation Avoids Major Failure Due to Boring, Well-Planned Asset Strategy.”

But that’s exactly what good looks like.

The Bit That Actually Matters And No One Talks About

This isn’t just a boardroom problem.

It’s a people problem.

Because I’ve watched high-performing teams go from fully engaged to completely disconnected.

Not slowly.

Instantly.

The moment they realise:

• Strategy has no continuity

• Long-term work is being undone

• Decisions are being made for optics, not outcomes

You don’t lose talent because people can’t do the work.

You lose them because:

They stop believing the work means anything.

Even Good Leaders Get Trapped

Here’s the uncomfortable truth.

Even leaders who want to do the right thing get boxed in.

Because:

• They won’t be there in 5–10 years

• They won’t see the payoff

• The next leader might scrap it anyway

So they optimise for what they can control.

And the cycle continues.

So What Actually Fixes It?

Not more leadership training.

Not another strategy workshop.

Governance fixes this.

Boards need to stop asking:

“How did we perform this year?”

And start asking:

• What does this look like in 10 years?

• What risk are we pushing forward?

• What are we deliberately not funding right now?

• Are we building something that survives leadership turnover?

Frameworks like ISO 55000 already exist.

The problem isn’t knowledge.

It’s enforcement.

Final Thought

The most dangerous organisations aren’t the ones that fail.

They’re the ones who

look successful while slowly building problems they can’t see yet.

Because short-term thinking feels like success.

Right up until it doesn’t.

The Question That Actually Matters

Before we question leadership capability, we should be asking:

What time horizon are we rewarding them to operate within?

Because until that changes, nothing else will.

It’s not.

It’s almost always a leadership problem.

I’ve seen highly engaged, high-performing teams that have delivered exceptional results for 3, 5, even 10 years shift almost overnight into something unrecognisable.

Not because the people changed.

Because the leadership did.

The moment everything starts to fracture

A new executive comes in.

That’s normal. That should bring fresh thinking, new direction, and momentum.

But when that leader:

• doesn’t take the time to understand what already works

• overrides without context

• issues direction without sharing the “why”

…it creates something far more damaging than poor communication.

It creates disconnection.

The silent message being sent

When past success is ignored or dismissed, the message to the team is clear:

“What you built doesn’t matter.”

Not explicitly.

But operationally, that’s exactly how it feels.

And that hits harder than most leaders realise.

Because teams don’t just deliver outcomes, they build:

• systems

• standards

• identity

• pride

Remove recognition of that, and you don’t just lose engagement.

You lose belief.

What disengagement actually looks like

It’s not loud.

It’s not people pushing back or causing issues.

It’s much quieter than that.

It looks like:

• people working independently instead of as a team

• no input into strategy

• no challenge, no ideas, no initiative

• “Just tell me what to do”

From the outside, it can look like compliance.

From the inside, it’s detachment.

The dangerous shift: from ownership to instruction

High-performing teams operate on ownership.

They think, challenge, improve, and build.

But when leadership removes visibility of vision and direction, people stop owning outcomes and start executing tasks.

They go from:

“How do we make this better?”

to:

“What’s the next thing you want done?”

And once that shift happens, performance may hold for a while—but culture is already gone.

The emotional reality leaders often miss

No one says it out loud, but it’s there:

• Was everything we did wrong?

• Why wasn’t what we built valued?

• Why should I care if it can be dismissed overnight?

That’s the moment engagement doesn’t just drop—it switches off.

Why teams become disjointed

Without a shared vision, teams don’t stay aligned.

They fragment.

Everyone defaults to their own understanding of “what matters,” because nothing has been clearly defined from above.

And the result is predictable:

• silos

• inconsistent standards

• loss of cohesion

• decline in trust

Not because people don’t care.

Because they no longer know what to care about.

A reality check for leaders

You cannot expect engagement when:

• vision isn’t shared

• context isn’t provided

• past success isn’t acknowledged

• and teams are removed from the strategy

Engagement isn’t built through directives.

It’s built through clarity, trust, and connection to purpose.

The uncomfortable truth

A single executive—no matter how capable—can undo years of engagement in a matter of months if they disconnect people from their sense of

meaning.

Not through bad intent.

Through lack of awareness.

Final thought

If your team has gone quiet, stopped contributing, and is simply executing tasks…

Don’t ask:

“Why aren’t they engaged?”

Ask:

“What have we done to disconnect them from the vision?”

Because engagement doesn’t disappear on its own.

It’s removed.

Have you seen this happen in your organisation when leadership changed?

Most organisations think they’re doing the former. Very few are doing the latter well.

Over the course of my career—most recently overseeing 230 buildings and a fleet of 130 vehicles in a shared services model I’ve learned that asset governance is not a system, not a register, and not a report.

It’s a discipline.

And if you get it wrong early, you spend years paying for it later.

1. Asset Audits: Decide What Actually Matters (Early)

One of the first and most critical governance decisions is deceptively simple:

What are we actually auditing?

Capital assets only?
Or everything ncluding FFE (Furniture, Fixtures & Equipment)?

I’ve seen organisations try to “capture everything” without understanding the operational burden that comes with it. The result is predictable:

• bloated asset registers

• poor data quality

• systems nobody trusts

On the other hand, I’ve also seen the opposite where FFE is ignored entirely, and suddenly millions of dollars of distributed assets have:

• no ownership

• no lifecycle tracking

• no accountability

The key lesson:

Scope is a governance decision, not a data exercise.

And just as important:

Every asset must have an owner.

Not a department.
Not a cost centre.

A person accountable for its performance, cost, and risk.

Without this, your asset register is just a spreadsheet with no consequences.

2. Lifecycle Planning: Strategy vs Reality

I’ve delivered full lifecycle models, 10-year capital plans, and end-of-life forecasting across multiple portfolios.

On paper, most organisations say they want this.

In practice, very few are actually committed to it.

Because lifecycle planning exposes uncomfortable truths:

• assets that should already be replaced

• underfunded maintenance

• deferred capital that is quietly building risk

And here’s where governance either holds… or collapses.

If your executive team is only focused on:

• 2–5 year financial optics

• short-term EBITDA improvements

• bonus-driven outcomes

then your lifecycle plan becomes a document that gets acknowledged… and ignored.

ISO 55000 is very clear on this:

Asset management must align with organisational objectives and deliver long-term value.

That means:

You cannot claim asset maturity if your decisions are short-term.

The real question is not:
“Do we have a lifecycle plan?”

It’s:
“Are we willing to follow it when it impacts the bottom line?”

3. Infrastructure Risk: What Are You Actually Managing?

When people talk about asset risk, they often default to condition.

But condition is only one piece.

From my experience, infrastructure risk sits across three real dimensions:

1. People Risk

• Do you have the capability to maintain the asset?

• Are your contractors competent?

• Is knowledge locked in individuals?

2. Financial Risk

• Are you underfunding lifecycle replacement?

• Are you deferring maintenance to protect short-term budgets?

• Are you accurately forecasting cost-to-serve?

3. Safety Risk

• Are assets compliant today not just on paper?

• Are inspections meaningful or just procedural?

• Do you truly understand critical failure points?

Most organisations over-index on compliance reporting and under-index on real risk visibility.

The result:

They feel safe right up until they’re not.

4. Portfolio Oversight: Do You Actually Know What You Own?

This sounds basic.

It isn’t.

Across large portfolios, I’ve consistently found:

• duplicate assets

• missing assets

• inconsistent classifications

• no clear linkage between assets and financial systems

Before you can optimise a portfolio, you need to answer a simple question:

“What do we actually have?”

When I completed full asset audits across national portfolios, the biggest value wasn’t the data itself.

It was the clarity.

Clarity that enabled:

• accurate capital forecasting

• standardised maintenance models

• better procurement decisions

• informed acquisition strategies

In one case, this clarity supported a strategic shift from a leased to an owned model—unlocking long-term cost efficiency and balance sheet strength.

Because governance is not just about control.

It’s about enabling better decisions.

5. Governance Is a Leadership Issue, Not a Systems Issue

You can implement:

• CMMS platforms

• asset registers

• lifecycle models

• dashboards

…and still fail at asset governance.

Because governance is ultimately driven by:

• leadership discipline

• organisational alignment

• willingness to make long-term decisions

I’ve seen high-performing asset environments with simple systems.

And I’ve seen failing environments with world-class technology.

The difference is always the same:

Leadership intent.

Final Thought: Asset Governance Is a Board-Level Responsibility

After managing assets across hundreds and in some cases thousands of sites, one thing is clear:

Asset governance should not sit buried in operations.

It belongs at the board and executive level.

Because the consequences of getting it wrong are not operational.

They are:

• financial

• reputational

• safety-related

And often, they’re irreversible.

The Question Every Organisation Should Ask

Before investing in another system, another audit, or another consultant, ask:

Do we actually have the discipline to govern our assets properly?

Because if the answer is no—

no framework, not even ISO 55000, will save you.

What has been getting under my skin lately is not just war itself, although that is bad enough. It is the way religion keeps getting dragged into it, twisted into a political weapon, and then presented as if God somehow signed off on the whole thing.

That is what I cannot stand.

There is something especially revolting about watching human beings take something that is meant to orient people toward meaning, humility, repentance, mercy, reverence, love, and peace, and then refashion it into a banner for vengeance, conquest, domination, and bloodshed. It is not just cynical. It is blasphemous. It is Heresy.

And this is not confined to one side, one country, or one religion. That is part of what makes it so infuriating. Bad actors do this everywhere. Political leaders do it. Extremists do it. Opportunists do it. Entire movements do it. They reach for faith because faith is powerful, and powerful things are always the first things corrupted by people who want control.

That is the pattern. Not holiness, but manipulation.

The Problem Is Not Faith. It Is What People Do With It

One of the most frustrating things about all of this is the lazy conclusion people jump to afterwards. They see violence committed in the name of religion, and their answer is that religion itself must be the disease.

I do not buy that.

The problem is not that faith exists. The problem is that people lie, people crave power, people want justification, and people are perfectly willing to mangle good things in order to sanctify their worst instincts. Religion is one of the tools they use because religion reaches deep into identity, morality, destiny, and community. If you can hijack that, you can move masses of people.

That does not mean the faith itself is identical to the corruption done in its name.

There will always be bad actors. There will always be people who know how to manipulate symbols, institutions, language, and sacred ideas in order to sway the population or excuse their own brutality. Sometimes they use religion. Sometimes they use education. Sometimes they use nationalism. Sometimes they use liberation language. Sometimes they use morality itself. The object changes. The tactic does not.

That is why I get so irritated when people act as if the answer is simply to blame the underlying belief system in its pure form. No. The rot is older than that. The rot is human.

The Shared Roots, and the Shared Vulnerability

Part of what makes this so tragic is that the major Abrahamic religions are not alien to one another in the way people often pretend they are. Judaism, Christianity, and Islam all emerge from related theological soil. They are not identical, and their doctrinal differences matter, but they are connected traditions with overlapping histories, prophets, texts, and moral language.

That shared heritage should, in theory, make humility easier. It should make people slower to dehumanise each other. It should make the possibility of reverence, moral seriousness, and self-critique more available.

Instead, what we keep seeing is that the same sacred inheritance can be seized and turned into fuel for tribalism and apocalyptic thinking.

That is the real horror for me. Not that religion exists, but that something rooted in the search for God can be dragged downward so easily by human pride.

Christianity, Schism, and the Corruption of Institutions

Within Christianity, this is not exactly new. The tradition has its own long history of fracture, power struggles, institutional failure, reform, counter-reform, and theological conflict. Anyone with even a passing knowledge of church history knows that the Church has never been immune to politics, ego, or corruption.

That is part of the background to why so many people, myself included, get suspicious when institutional religion starts acting like empire. Historically, Christian communities split for serious reasons, including doctrinal disputes, political pressures, and disgust with abuses of power. The Great Schism divided East and West. The Protestant Reformation did not emerge from nowhere either. It came out of deep objections to how church authority was being exercised, how spiritual life was being administered, and how power had become entangled with things it should never have been entangled with.

That does not mean every criticism made by every reformer was right, and it does not mean every branch that later emerged represented a healthy correction. It means the suspicion itself has a history. When people look at large religious institutions and feel that they have drifted from humility into machinery, they are not imagining that tension out of thin air.

And in the modern world, that tension has not disappeared. In some places it has become even uglier.

When the Church Becomes a Brand

One of the clearest examples is the rise of religious spectacle. Faith gets packaged, marketed, monetised, and sold back to people as identity performance. Churches become brands. Pastors become celebrities. Theology becomes a product line. Conviction becomes optics. Reverence becomes theatre.

And once that happens, it becomes very easy for religion to serve power instead of confronting it.

That is why I have such a problem with modern political Christianity when it starts sounding less like the Gospels and more like a war room. Once the church becomes obsessed with size, influence, optics, and dominance, it stops looking like a body of believers and starts looking like just another institution trying to secure market share and power. At that point, do not be surprised when it ends up blessing things Christ would have rebuked.

What Christianity Actually Demands

I am speaking most directly here as a Christian, because that is the tradition I know from the inside.

Christianity is not a religion of domination. It is not a religion of state violence dressed up as righteousness. It is not a religion of chest-beating cruelty, nationalist idolatry, or sanctified hatred. Christ did not come here to teach people how to baptise their resentment. He came proclaiming repentance, mercy, forgiveness, humility, sacrificial love, and the radical dignity of people society despised.

That matters.

Jesus did not reserve compassion for the respectable. He moved toward the people everyone else wanted to condemn. He shattered the fantasy that holiness belongs only to the clean, the powerful, the socially approved, or the ideologically useful. He told people to love their enemies, to care for the poor, to forgive, to serve, and to stop mistaking public religiosity for actual righteousness.

So when someone invokes Christianity to justify hatred, cruelty, or war fever, I do not see a stronger version of the faith. I see a betrayal of it.

That is the bit that truly angers me. Not because I expect the world to behave perfectly, but because this is such a grotesque inversion of what the faith actually teaches. It is a desecration wearing religious language like a costume.

Holy War Rhetoric Is a Sign of Decay

The moment political leaders, extremists, propagandists, or ideological movements start invoking religion as a framework for war, alarm bells should go off. It does not matter whether the language is Christian, Muslim, Jewish, or anything else. The mechanism is the same. Sacred meaning gets fused with political violence, and suddenly ordinary people are told that destruction has a divine mandate.

That is a profoundly dangerous move.

It hardens conflicts that are already combustible. It makes compromise feel like betrayal. It turns political disputes into cosmic struggles. It grants leaders the kind of moral cover they do not deserve. It also poisons the public imagination, because people stop seeing war as a tragic failure of humanity and start seeing it as spiritually meaningful.

That is how you radicalise populations. That is how you produce fanaticism. That is how you make every casualty easier to excuse.

And once religion is successfully welded to violence, everyone loses. Believers lose because their faith gets dragged through mud. Non-believers lose because they are handed a cartoon version of religion as proof that all faith is insane. Wider society loses because nuance gets obliterated. And the people caught in the actual conflict lose most of all.

The End Times Obsession

What also disturbs me is the way apocalyptic thinking keeps creeping into geopolitics. Whenever people start treating war, territorial conflict, or destruction of sacred sites as steps toward some prophetic climax, the situation becomes even more deranged.

At that point, peace is no longer just politically inconvenient. It becomes spiritually undesirable to the people caught up in that mindset.

That is terrifying.

Any theology that starts hungering for catastrophe in order to force history toward a desired ending has already lost the plot. It stops being reverence and starts becoming theatre for people who want divine significance attached to their brutality or their fantasies of control. Whether that language is framed in messianic, prophetic, or eschatological terms, the effect is the same. Human suffering becomes instrumental. Bloodshed becomes symbolic capital.

Nothing about that is holy.

Why This Actually Gets to Me

This is not abstract for me, and that is probably why I am writing this with so much heat.

Faith has mattered enormously in my own life. I know what it has done for me. I know what Christ has done for me. I know the way grace can reorder a person, steady a person, rescue a person, and pull them toward something better than their own instincts would have produced. I would not be where I am without that.

So yes, it angers me when I see the name of God used like a weapon.

It angers me when Christ is invoked to excuse things that spit in the face of his teaching. It angers me when religion becomes a prop for cruelty. It angers me when the sacred is reduced to propaganda. And it angers me when people then turn around and blame the faith itself, as if the corruption and the source were the same thing.

They are not the same thing.

The distortion is real. The betrayal is real. The hypocrisy is real. But precisely because those things are real, it becomes even more important to say clearly that the abuse of a thing is not the definition of it.

The Real Enemy

The real enemy here is not sincere belief. It is the human tendency to corrupt whatever it touches.

People do this to religion because religion is powerful. They also do it to law, education, politics, family, science, media, and morality. Anything with authority, meaning, or emotional force is vulnerable to capture by people who want to rule, justify themselves, or avoid accountability.

That is why vigilance matters.

It is not enough to say, “That person is religious, therefore they must be right.” It is also not enough to say, “That atrocity was done in the name of religion, therefore religion must be the problem.” Both responses are intellectually lazy. Both ignore the harder truth, which is that human beings are fully capable of dressing up vice as virtue and calling it holy.

That is the actual scandal.

Final Thought

I do not have a neat solution to this. I do not think there is one.

I just know that I am sick of watching faith be mutilated by people who want to use it as cover for domination, violence, and hate. I am sick of watching religion turned into a stage prop for political insanity. I am sick of seeing the sacred hollowed out and then marched into war as if God should be grateful for the association.

Religion, at its best, should call people to humility, repentance, peace, and love. The moment it is used to inflame bloodlust or sanctify cruelty, something has gone badly wrong.

And I am not interested in pretending otherwise.

Most boards are well-equipped with:

• Lawyers to manage legal risk

• Accountants to oversee financial performance

• Consultants to guide strategy

But there’s a critical gap that is consistently overlooked:

Very few boards include directors who truly understand physical assets.

The Governance Gap No One Talks About

Asset-heavy organisations whether in property, infrastructure, healthcare, education, or government are fundamentally built on physical assets.

Buildings. Equipment. Infrastructure. Vehicles. Systems.

Yet governance conversations often reduce these to:

• depreciation schedules

• capital expenditure line items

• reactive maintenance budgets

This is not asset management.
This is financial abstraction of operational reality.

Leading asset management frameworks such as ISO 55000 emphasise that assets are not just financial entries, they are value-generating systems requiring lifecycle thinking, risk modelling, and long-term planning.

Without this lens at the board level, decisions become disconnected from reality.

What Happens When Boards Lack Asset Expertise

From both industry research and real-world experience, the consequences are consistent:

1. Short-term decision making
Boards prioritise cost reduction over lifecycle value deferring maintenance, underinvesting in renewal, and creating hidden liabilities.

2. Poor capital allocation
Without understanding asset condition, utilisation, and risk, capital is often deployed reactively rather than strategically.

3. Increased operational risk
Critical failures whether compliance, safety, or service delivery are often the result of under-informed governance.

4. Misalignment between strategy and execution
Strategies look sound in board papers but fail in operations because they don’t reflect how assets actually perform on the ground.

The Missing Voice at the Table

This is where asset management expertise becomes essential.

A director with deep experience in physical assets brings a fundamentally different perspective:

• Lifecycle thinking understanding total cost of ownership, not just upfront spend

• Operational realism knowing what works in practice, not just in theory

• Risk visibility identifying hidden failures before they surface

• Capital discipline aligning investment with long-term asset performance

This is not a “nice to have.”
It is core governance capability in asset-intensive organisations.

From Theory to Practice: What Good Looks Like

Boards should be asking:

• Do we have a 10-year asset plan backed by real data?

• Are we forecasting end-of-life risk and replacement cycles?

• Is our maintenance strategy proactive or reactive?

• Do we understand the true cost to maintain service levels?

• Are asset decisions aligned with organisational strategy and demand?

These are not operational questions. They are governance questions.

Why This Matters Now More Than Ever

Across Australia, organisations are facing:

• ageing infrastructure

• rising maintenance costs

• increased compliance and safety obligations

• pressure on capital budgets

At the same time, boards are being held to higher standards of accountability.

This creates a clear reality:

You cannot govern what you do not understand.

The Future of Board Composition

The next evolution of high-performing boards will include:

• Financial expertise

• Legal expertise

• Strategic capability

And critically asset management expertise.

Because in asset-intensive organisations:

The balance sheet tells you what you own.
But only asset expertise tells you what it’s actually worth and what it will cost you next.

Final Thought

Boards don’t fail because they lack intelligence.

They fail because they lack visibility into the systems that actually drive performance.

Physical assets are one of those systems.

And the boards that recognise this and bring the right expertise to the table will be the ones that deliver sustainable, long-term value.

Not ego. Not titles. Not LinkedIn bios.

Just survival.

Will I have work next week?
Will the pay hit the account?
Do I stay loyal?
Or is it time to go?

I find myself here again. Not for the first time. And certainly not for the last.

Three and a half years in my current role a record for me and now new management is shifting the ground beneath our feet. Strategies rewritten. Assumptions overturned. The quiet whisper of “restructure.” The word redundancy floating just close enough to feel real.

This isn’t new. Thousands of people live here every day.

But when you land here, it forces reflection.

What was fun?
What mattered?
What do I actually want?

Because here’s the hard truth:

We spend half our waking lives at work.

Half.

If you don’t enjoy what you do… why are you doing it?

That question hits differently when you blink and your kids are suddenly in their twenties. When you’ve been married nearly thirty years. When retirement is no longer theoretical.

Life is short. Too short for a joyless grind.

And yet most of us forget that work can and should be fun.

The Best Jobs I Ever Had

Some of my best job memories weren’t about promotions or pay rises.

They were about adventure. About stories I can reflect back on.

About the kind of days that make you sit back and say, this is unreal and I’m being paid for it.

Darwin to Groote Eylandt

As a facility manager inspecting remote sites, work meant distance. Real distance.

Six-hundred-kilometre road trips across the Northern Territory. Darwin to Groote Eylandt. Gove to Mount Isa and back again. Red dirt highways stretching beyond the horizon. The kind of isolation that resets your perspective.

You don’t just inspect buildings in places like that.

You meet people living their best lives on the road contractors camped in caravans, mechanics who know every corrugation in the track, sparkies who’ve raised families between projects. People away from loved ones in the name of work, but building something, fixing something, keeping something running.

There’s pride in that.

There’s purpose.

Chasing Crocodiles on the Booroloola River

Then there were the moments no one believes.

Chasing crocodiles down the Booroloola River.

Not because I’m a wildlife ranger. Because site access sometimes means navigating real terrain. Real risk. Real country. When you work remote Australia, nature doesn’t move for you. You adapt.

And there’s something alive about that kind of work. It sharpens you.

Flying into Victoria River Cattle Station

Flooded roads cut off all access — so we took to the air. A helicopter into Victoria River Cattle Station. Because the job still had to get done.

You don’t forget the sound of rotors cutting through hot NT air. The view of endless red plains below you. The absurd realisation that “office work” has taken a strange turn.

That’s fun. Not because it’s glamorous. Because it’s alive.

Big Red, Birdsville and My Dad

One trip to Birdsville, I convinced my father to come along.

We rented a 4x4. Took it up Big Red in the Simpson Desert. Only to be gently told by locals we probably shouldn’t be taking a rental off gazetted roads.

All in the name of work. But really — in the name of life.

Dad and I bouncing over dunes, laughing like idiots, pretending we knew what we were doing. Work gave me that memory. Tell me that’s not worth something.

Survival Mode vs Fun Mode

Right now, I’m in evaluation mode. Stay or go?

Do I cling to what I’ve built for three and a half years?
Do I fight for relevance under new management?
Or do I step into uncertainty again?

The survival instinct says:
Take the safe 9–5. Keep your head down. Make ends meet.

But something in me resists that.

No way. Life’s too short.

And here’s the deeper truth: Fun doesn’t mean easy.

Fun means:

• Work that stretches you

• Work that lets you travel

• Work that allows mentoring

• Work with purpose

• Work that leaves a legacy

Maybe one of those. Maybe all. But fun isn’t frivolous. Fun is alignment.

Am I Too Old for a Fun Job?

I’ve asked myself this. Am I too old to chase something different?
Should I finally accept the reality of the grind? But when did we decide that responsibility and joy were mutually exclusive? Experience should widen options, not shrink them.

If anything, I now know what fun looks like. I know what purpose feels like. I know what good teams are. I know the kind of leader I want to follow and the kind I refuse to become.

And I know this:

If you don’t include fun, you burn out.

If you don’t build teams that laugh, they disengage.

If you don’t create purpose, people drift.

What Job Hunting Really Is

Job hunting isn’t just survival. It’s recalibration.

It’s taking stock:

• What were my best days?

• What environments brought out my best?

• Where did I feel alive?

• What kind of people do I want to build with?

Sometimes we stay because it’s comfortable Sometimes we go because it’s necessary.

Sometimes we’re pushed and that push becomes the best thing that ever happened to us.

Make Work Fun

Here’s the challenge:

Whatever you do — make it fun.

Be fun to be around.

Build teams that want to follow you.

Mentor someone younger.

Take the long road occasionally.

Say yes to the helicopter.

Bring your dad on the trip.

Because one day you’ll blink and decades will have passed.

Your kids will be grown.

Your career will be nearly done.

And you’ll either have stories…

Or spreadsheets.

Work is survival. Work is accomplishment. Work is the next step.

But it should also be joy. I don’t know yet whether I’m staying or going.

But I know this much: Wherever I land next, it must be fun.

Because life is too short for anything less.