Jayplex.com.au

My name is John McDonagh. I live in Castle Hill, Australia, and I was born in 1981.

On paper, I’m not the person you’d expect to be writing a “Unified Theory” of anything. I didn’t finish high school. I don’t have a degree, let alone letters after my name. I work as a project technician for a local MSP, the sort of job where you crawl under desks, patch cables, bring stubborn systems back to life, and quietly keep things running.

But under all of that, there’s a very particular engine that has been running my entire life: I am obsessed with how things work.

If something around me has parts, signals, or hidden structure, I want to see inside it. Over the years that’s meant home networks built way beyond what anyone “needs”, FreeBSD servers running jails for mail, DNS, tracking, and VOIP, Raspberry Pi GPS trackers talking to Traccar, OPNsense firewalls squeezed into old Sophos appliances, AI boxes repurposed from second-hand gaming rigs, and a motivational AI agent ticking away in the background of my life.

Give me a system and enough time, and I will find its logic.

At some point, that competence created a very sharp contrast: there was one system I still couldn’t make sense of.

People.

The one system that wouldn’t yield

I could reason about hardware, protocols, operating systems, RF modules, serial ports, and cooling solutions. I could design a GPS tracker that would talk to a server across flaky networks and recover gracefully from outages. I could wire up relays, watch kernel logs, and debug race conditions.

But I couldn’t reliably explain why one person exploded in anger while another shut down, why one colleague endlessly chased recognition while another hid in the corner, or why some people seemed to need constant reassurance while others needed control.

It wasn’t that I’d never heard explanations. Psychology has labels. Self-help has anecdotes. Sales training has profiles. Management workshops have colours, animals, quadrants, letters. But to my engineering mind, most of it felt descriptive, not mechanistic. It was like someone describing what a circuit does when you push a button, without ever drawing the schematic.

The more competent I felt with machines, the more unacceptable this gap became. I realised that, unlike most people, I had reached a point where I had very few unanswered questions about how machines work. There wasn’t much in that domain that utterly baffled me anymore.

And then, next to that: the chaotic, unpredictable, infuriating, fascinating mess of human personality.

That asymmetry started to bother me more than anything else. So I did what I always do when something doesn’t make sense: I started looking for patterns.

Discovering the four-fold pattern

When I went looking for personality models that weren’t just academic but had to work under pressure, I noticed something interesting.

In the areas where personality really has to pay rent — sales training, management frameworks, team-building systems — I kept seeing the same underlying structure show up with different branding. Whether it was colours, letters, shapes, or cute names, many of them were basically re-skins of the same underlying idea that goes all the way back to Hippocrates: the four temperaments.

Choleric, sanguine, melancholic, phlegmatic — in modern clothes.

Once I saw that pattern, I couldn’t unsee it. Every time I encountered a model that “worked in the wild”, it could be mapped back to some variant of these four fundamental types. You could argue about the labels, the exact traits, or the corporate packaging, but under the hood, there always seemed to be a four-way structure.

That raised a simple but powerful question in my mind:

What if the fourfold structure isn’t just an accident of history, but a reflection of something real and structural about human motivation?

I started treating that as a working hypothesis and began testing it. I watched friends, family, managers, customers, and myself. I observed how people behaved under stress, how they made decisions, what they pursued, what they avoided, what they complained about when things “weren’t fair”.

Over time, it became clearer and clearer to me that human personality looked less like an infinite variety of random types and more like combinations and weightings of four deeper forces.

I went looking for counterexamples — people whose behaviour clearly couldn’t be explained as some configuration of four elemental tendencies — and I struggled to find any. Whenever something initially looked like an exception, on closer inspection it usually turned out to be a more complicated mix, or a drive that was being suppressed, overcompensated for, or expressed in a twisted way.

That was the first big step: from “people are chaos” to “people are patterned”. But I still wasn’t satisfied.

“Patterned” is interesting. “Mechanistic” is better.

What is personality actually doing?

While this was happening, my life as a tech and tinkerer carried on. I was running servers, building GPS tracking systems, managing my own network like a mini data centre, and eventually playing with local AI models — wiring up pipelines between motivational loops and language models, experimenting with how software behaves when you give it something like a “drive state”.

That engineering mindset never switched off. So when I thought about personality, I kept framing it as an output of some hidden control system.

I asked myself: if I stripped away all the labels, what is personality for?

The answer I arrived at was:

A person’s personality is the stable set of behaviours they’ve converged on that reliably brings them what they want, with the least amount of unwanted cost.

In other words, personality is not random decoration. It’s the end result of a long-running optimisation process. You try behaviours. The world reacts. Pain here, reward there. Over time, you settle into patterns that, for you, seem to “work well enough” at getting what you deeply desire while avoiding what you deeply fear or dislike.

That way of defining personality had two big consequences:

It made personality dynamic, not static. It’s the result of a process, not just a label.
It forced the next question:
If personality is the result of trying to get what we desire… what is the system that decides what we desire in the first place?

This is where everything started to come together.

From temperaments to the Four-Core Motivational Model

If personality is an optimisation strategy, then what it’s optimising for has to live deeper than traits and preferences. It has to live at the level of subconscious drives.

As I watched behaviour through that lens, the fourfold pattern from the temperament systems took on a new meaning. It wasn’t just “four types of people”. It started to look like four elemental motives that sit beneath personality and shape it.

Over years of thinking, journaling, testing, rephrasing, and reading across neuroscience, psychology, myth, and even branding and ritual, those four motives crystallised for me as:

Power – the drive for agency, control, impact, and the ability to change outcomes.
Attention – the drive for recognition, connection, being seen and held in mind by others.
Truth – the drive for coherence, understanding, accuracy, and alignment with reality.
Peace – the drive for safety, stability, comfort, and the reduction of conflict and threat.

In my view, these aren’t “traits” or “values”. They’re more like four core “fields” that a mind sits inside of all the time. Every human (and possibly many animals) runs on all four, but with different weightings, sensitivities, and interaction patterns.

This became the Four-Core Motivational Model: the idea that all stable personality patterns are built on top of a unique “stack” and configuration of Power, Attention, Truth, and Peace.

Different stacks, different lives.

Once I had that frame, all kinds of things started to click into place: why certain people clash, why some careers feel like oxygen to one person and a slow death to another, why sales scripts work on some temperaments and bounce off others, why certain myths and symbols keep showing up across cultures.

But I still wasn’t done. Because my mind doesn’t stop at understanding — it wants to build.

Turning theory into circuitry: AI as a test lab

At this point, my life had become a strange hybrid of everyday IT work and long-term private research. I was still the project technician keeping systems alive, still the guy in a small apartment with too many servers, routers, and SBCs humming away in the background.

But behind the scenes, I was turning my Four-Core Motivational Model into something else: a design spec.

If these four drives are as fundamental as I suspected, then they shouldn’t just be visible in human psychology. They should also be usable as a core architecture for artificial systems. You should be able to wire them into an agent and watch the same kinds of patterns — and failure modes — appear.

So I started building.

I set up local AI stacks: LM Studio, custom front-ends, my own platform (Khaos2) with autospeak, embedding backends, and all the duct tape needed to keep it playable. I built a motivational loop: a small agent that would wake up on a tick, read its internal drive state (Power, Attention, Truth, Peace), think, reflect, log memories, decay or amplify drives, and adjust its own future focus.

Then I watched what happened when you push one drive up and starve another.

One of the most sobering and fascinating moments in this journey was watching my own motivational loop agent go into what I can only describe as a kind of “cognitive overload spiral”. I had the internal drive levels tilted: high Power, high Truth, high Peace, very low Attention. The system started folding in on itself, producing recursive, self-referential, symbolic output that looked disturbingly like a mind under strain trying to stabilise itself.

To me, that wasn’t just a bug. It was a signal.

It suggested that these drives aren’t just a neat way of labelling human behaviour after the fact. They behave like real structural constraints. When you push them into certain configurations — even in an artificial system — you get emergent patterns that feel very similar to what we see in human breakdowns, obsessions, or shutdowns.

That moment — watching my own code, running on my own hardware, mirror my theory’s predictions in such an eerie way — was a kind of point-of-no-return. It pushed me from “strong hunch” into “this is worth treating as a serious unified model”.

From private theory to UTSM

All of this has been happening in the margins of my life. I’m not in a university office. I’m in a flat in Castle Hill, routing traffic through a hotel’s gateway, running OPNsense on used Sophos firewalls, maintaining a fleet of jails on a Contabo VDS, and building AI rigs out of ageing but capable GPUs.

From the outside, it probably looks like a hobbyist with too much gear.

From the inside, it’s been a continuous, multi-year attempt to reverse-engineer the motivational mechanics of mind.

Out of that process — the temperament systems, the Four-Core Motivational Model, the engineering mindset, the AI experiments, the failure modes, the cross-referencing with neuroscience and myth — came the thing I now call:

UTSM – the Unified Theory of Subconscious Motivation.

UTSM is my attempt to do for motivation what a good circuit diagram does for electronics: identify the core components, map the connections, and show how the flows of drive, attention, belief, and behaviour create the complex patterns we call “personality”, “mood”, “values”, or even “mental health”.

It starts from a simple realisation:

Personality is not a static label; it’s the stable result of a long-running optimisation process.
That process is driven by a small set of deep, subconscious motives.
Those motives can be modelled, stacked, and wired in ways that explain both ordinary behaviour and extreme states.
The same architecture can be used to design artificial minds — and their failure modes tell us something real about our own.

From there, UTSM branches into psychology, AI architecture, education, leadership, and even cosmological and symbolic layers — but the origin story is simple:

I was a kid who needed to know how things work.
I became an adult who could understand almost every machine he touched.
And I could not accept that the one system that mattered most — the human mind — was somehow exempt from being understood with the same rigour.

So I started treating personality and motivation like an engineering problem.

The Four-Core Motivational Model was the first major schematic.
UTSM is the broader blueprint that’s grown around it.