From Code to Human Code: An Engineer’s Journey to Superminds
This article was co-written with Claude AI for translation, reformulation, and structure. It is the fruit of a real dialogue and reflections, not an automated article created from standardized content for filler purposes. I wish everyone a good read.
The Young Engineer’s Disillusion
This is a story I want to tell today, aimed at engineers who fear entrepreneurship and organizational or management questions, and who, like I used to, see human frictions as obstacles to the rational beauty of engineering work.
I found myself in these situations, and it took me years to understand how to consciously integrate the practice of organization/management with that of engineering.
When I graduated from engineering school, with my degree in information systems from ENSTA (now Ensta ParisTech) and my degree in business strategy, I expected to encounter in my work an excitement to build great things, to construct grand systems, to face complexity together, to imagine, invent, create, model, test, to transcend our nature as individuals and our obstacles to make pyramids, great walls, immense factories, the Internet, electrical networks, logistics networks, trains, nuclear plants, fascinating algorithms.
I expected to find the same excitement, the same enthusiasm, the same underlying dream, in every colleague, every boss, every management team. Of course, not everyone was cut from this cloth, but in the companies I was targeting - tech consulting firms, software publishers, etc. - this is what I told myself.
By chance, these encounters and this connection to the “taste for systems” did happen with some people in some environments and teams. I remember a first internship supervisor who was always in this movement, very benevolent by the way, and my first team of geeks (we rarely said “nerd” at the time), even working with a colleague who went so far as to wear a Star Wars t-shirt at work while configuring an SVN production deployment. It was our team, and we were doing our part to build the world, it excited us…
… but I also encountered another facet of the working world, even in engineering: for a majority, I must admit I faced a shock. A good portion of people didn’t care about the joy of building all this. Their concerns were their vacation days, the weekend, what time they were going to leave and what movie they were going to watch as soon as they “got rid of” today’s work, the daily rate, the next position, the troubles, the gossip, the culture problems and resistance to change, the preservation or quest for power, the year-end bonus, etc.
I was amazed to discover that others weren’t dazzled by the beauty of what we were projecting, modeling, or building together - a beauty of construction, of a system, of a machine that could transcend human temporalities and scales of tasks, effort, difficulty that humans alone, however strong and powerful they might be, couldn’t envision.
I saw enormous waste when I was told that immense projects were slowed down by small-minded egos, corporate turf wars, bad days, conflicts and susceptibilities, opportunists who sold anything to get their bonus and leave afterward, people who wanted a career but not real constructions, just names on their CV, something to shine with at a cocktail party, to rest as much as possible and seek only pleasure, engineering being just an easy field where one could easily make money.
At the time, I perceived these management issues as “small affairs,” less noble than systems engineering, dumb frictions that parasitized the rational beauty of an engineering work.
The Flaw in Traditional Modeling
With the years, I began to question an assumption: what is the limit of a system?
In school, we learn what systems are. We often talk about a system as a set of devices, mechanical elements, informational elements (databases, flows, algorithms), physical elements (materials, etc.), but we don’t imagine that the boundaries we give in system modeling are often artificial.
The human factor is systematically excluded from these modelings, even though it determines the resilience, evolution, and adaptation of the system over time. We make a major design error: treating humans as “external users” rather than as full components of the system.
Because if you consider code, it’s language to operate machines, so you consider the question of how to keep these machines running in the long term. But if you count code variations and automated machine tasks, you extend the boundary not just to today’s state, but to the sum of tomorrow’s states.
What applies to code applies to general maintenance of all systems. If you design a seemingly perfect system (let’s say a nuclear power-plant) but do not design the human capabilities to repair it, manage it, even somehow improve it, your nuclear power-plant longevity is gone. If you do not design how to motivate humans into developing these maintenance capabilities, your maintenance system is lot. If you do not care about how these humans are managed, supported, trained, you let that maintenance system leave after a few years of wrong work experiences.
What applies to general maintenance also applies to continuous improvement, human monitoring, human in the loops, ethical design, etc.
The Revelation: Humans Also Have Code
The Fascination of Leadership as Programming
It’s by observing leaders that I had my first revolutionary intuition. How can a single human, simply by contracting their mouth and waving their hands, move millions of humans to wage war, follow a given set of guidelines, build cathedrals?
Human code: Leadership, sales, marketing, communication.
That’s why I study leadership, communication, on top of all other more technical topics (Python, Quantum Computing, AI, …), because it is code!
Let me break this down in programming terms:
- Leadership is calling methods of your choice on the “human” object - it’s a functional call
- Sales concern methods that trigger resource activation
- Marketing is parsing different agents and their code
- Communication is the protocol to access the vocal interface
I remember a joke I heard from a nerdy engineer saying “this guy only talks in specs, he does not have a vocal interface.” This joke actually revealed a profound truth: we all have interfaces, APIs, communication protocols.
Discovery Through Practice: From Scrum to Superminds
Phase 1: Scrum Master - Modeling Retrospectives
It took me 5 years of working - after some experiences in product management and application development - to discover these “formalized behavior” questions when I became a Scrum Master. I started modeling retrospectives to give humans similar (in part) and predictable behavior for a limited duration: the angles of view to analyze the past sprint, the order in which to think, etc. I used metaphors and symbols (by theming retrospectives) to access functions through “memetics.” I was essentially writing behavioral scripts that teams would execute predictably.
Phase 2: #OpenSeriousGame - Pedagogical Viruses
With #OpenSeriousGame and the modeling of active learning game experiences in general, I had to learn to better understand this human code, particularly the writing of new behavioral code via a pedagogical “virus” (each OpenSeriousGame): the repetition of a modeled behavior, which would be emergent because it was the only way to win or succeed under conditions constrained by the game.
For example, in a conflict game, starting to communicate more intelligently about one’s needs and oneself was the only way to win. The game narrative and instructions, along with the game repetition process and self-discovery, allowed each human agent to write this code within themselves, in addition to learning to play and transmit the virus to others.
Phase 3: Komyu - Organizational System Engineering
More recently, since Komyu, through modeling community behaviors, then cross-organizational decisions, I find myself integrating into organizational system designs not only classic workflow questions (for example, whether to ritualize meetings every X or Y time, the type of roadmap, etc.), but also more human questions of culture, emotional state, etc. We can engineer these too - (neuro)marketing already does this somewhere, and we can integrate these parameters into our more complex organizational systems.
The MIT Confirmation
During this Komyu phase, my MIT Sloan training in AI strategy was crucial. It didn’t teach me something entirely new, but rather confirmed my intuitions and gave me the words, additional concepts, and frameworks to articulate what I had discovered through practice. Leadership, far from being this mysterious and artisanal art that I had once despised, could indeed be modeled, structured, professionalized.
The frameworks and models I discovered gave me the conceptual tooling to understand behavioral patterns. I realized that what I had taken for human chaos was actually poorly documented code, poorly architected systems, but systems nonetheless.
I was doing Factorio but in human code.
Human Code: Non-Deterministic Pattern Accumulation
The most fascinating revelation came with the rise of LLMs. I realized that humans accumulate and combine patterns in a way very similar to the learning of large language models.
The difference with traditional software? Human code is less deterministic, more adaptive. Humans are continuously learning systems that update themselves through experience, accumulate emergent patterns, develop behaviors that are not explicitly programmed but emerge from the interaction of thousands of micro-patterns.
It’s exactly like LLM learning: an accumulation of patterns that, through emergence, produces complex and adaptive behaviors.
Interestingly, we mathematically have a near-certain chance of being in a simulation ourselves. According to Nick Bostrom’s foundational work and subsequent studies in the Royal Society, if advanced civilizations develop the ability to simulate conscious beings, the probability that we are simulated entities becomes overwhelmingly high. This gives a strange coherence to the whole picture: if we’re patterns in a simulation, no wonder we can be understood as code.
A Note on the “Human Code” Metaphor
I realize this formulation can send chills down the spine, seeming almost manipulative, reducing humans to some kind of programmable organic machine. I do not adhere to the connotations that go with this vision of human code. On the contrary, I find beauty in discovering that we can always understand more and, moreover, realize that it’s even deeper than we thought.
Even recently, in June-July 2025, we discovered with Centaur.ai that human decisions are predictable - researchers trained an AI model on millions of human decisions from psychological experiments, and it can now predict human choices with startling accuracy across tasks it has never seen before. Yet this doesn’t diminish the wonder of human cognition; it reveals new depths to explore.
The beauty lies not in reducing humans to machines, but in discovering that consciousness, creativity, and human connection operate through patterns we can gradually understand - patterns that are far more sophisticated and beautiful than any code we’ve written.
Entrepreneurship as Hybrid Engineering
Initially, I saw entrepreneurship mainly as an administrative format to do things rather than as an employee, to gain freedom. I opposed my “modeling work and applying models to leader decisions” part (my work as a cross-functional leader preparator for my clients) with the “administrative” part - configuration, etc. - which was very tedious.
With hindsight, the administrative work is a manual implementation of integrating my system into the “France” codebase. Configuration and management are the construction of production pipelines, continuous improvement, human well-being (which is also one of the outputs to be produced by the system, in addition to intelligent decisions).
This is ultimately why I reconciled entrepreneurship, engineering, and what we call “the humanities” - which can also be viewed in a certain way (not exclusively) as learning and practicing human coding: on oneself, on others, in reception too, and therefore with each other.
I no longer oppose my Python coding courses with my emotional intelligence courses. I no longer oppose team organization courses to optimize workflows with courses on workplace happiness. All of this can be seen as one great discipline.
What I really like about technological entrepreneurship, and innovation too, is this aspect: you have to go seek the shock with reality, the pressure testing. Not just complimenting each other with slides, or looking at your specs and systems, but also confronting them with usage conditions.
The engineer in the “society” execution environment: entrepreneur.
I understood that technological entrepreneurship is not about using humans to create a system, but that the system includes humans within it: the data they generate, the models we can apply to them, the interfaces through which we access them, the suggestions they propose, their revolutions, their adaptations.
Toward Supermind Engineering
Today, AI reveals what was there from the beginning: humans have always had code. This code accumulates, combines, evolves. Humans are components that generate data, models, suggestions, innovations.
AI is not there to replace this human code, but to reveal it, amplify it, optimize it. It allows us to see patterns that were invisible, to understand the social algorithms that govern us.
Supermind engineering - this hybrid organic/non-organic discipline - becomes the new frontier of engineering. We no longer build systems for humans; we build systems with humans, where the boundary between organic and non-organic becomes blurred.
It’s a fascinating field, where the rational elegance I was seeking since my engineering beginnings finally marries with the human complexity I once despised. Human code is not the enemy of systems engineering: it’s its next evolution.
Beyond Determinism: The Quantum Frontier
Yet I want to end by opening up ideas that move beyond this deterministic fear. I’m currently studying quantum computing and concepts like collapse, retrocausality, and the realization that even if it’s not very visible at our macro scales, we live in a dynamic, fractal world with causality questions that surpass the classical views of the programmable human I describe here.
Even if we can model human behavior with increasing precision, we exist in a universe where quantum effects, nonlinear dynamics, and emergent properties create genuine unpredictability. The patterns we discover don’t constrain us—they reveal the incredible sophistication of the system we’re part of.
This is a fascinating world, and our natural quest is to continue exploring. The more we understand about human code, the more we discover about the beautiful complexity that makes us who we are. We’re not just programmable entities; we’re conscious explorers in a universe that continues to surprise us.
Alexandre Quach - Founder of Komyu and the #OpenSeriousGames movement, executive preparator and specialist in AI-augmented collective intelligence