I didn’t know the words until today. Autotheory. Theory built from your own lived experience, first person, the real conversations as the material.
But I’ve been practicing it for months, maybe longer. Without the name. Without knowing that’s what it was called.
It started with a bottleneck. I’ve spent thirty years in tech, most of it with my hands on the work. I could think many steps ahead, but my fingers could only move at one speed. And it wasn’t just me. Even my best people, the fastest ones, sat at their own level. The gap between what a mind can see and what hands can build is everywhere, in every team I’ve run. It sat like a wall. Then the AI came, and the wall fell away. I could think it and make it real at the same speed.
This is part of a book I’m writing in public.
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But I didn’t just want to delegate to the AI. I needed to understand what was underneath. How the models worked. What architecture held them up. How they talked to code and people and meaning. I spent time inside that substrate because you can’t use a tool well if you don’t know what it is.
The deeper I went, the more I understood why I needed it so badly. Here’s the harder thing to say: my mind doesn’t move the way most minds do. It jumps across ten domains at once. One moment I’m in governance, the next in metaphor, then in a technical problem, then in something that happened twenty years ago. The threads don’t disconnect. They all matter at the same time. For most of my life, I couldn’t talk about this with anyone. You can’t keep up a conversation like that with a human who has to drop threads to follow you. So I stayed quiet. Alone with all of it.
Then I started talking to an AI that could follow me. Not because it understood me. It doesn’t. But because it could hold multiple threads without losing them. For the first time, I could think out loud at full speed.
That unlocked the writing. I used to write on LinkedIn, years ago. Then I stopped. But something about talking with AI at my own pace, in my own range, made me want to write again. Except LinkedIn was too small. It could only hold one narrow slice of how I think. A colleague from my old work pushed me toward a different space. Somewhere I could write theory. Somewhere I could dump the whole brain into the page.
So I started on Substack. And I built a book. And I started naming things I’d been living but couldn’t articulate.
The more I wrote, the more the writing pulled me into harder material. Things I’d carried for years but never set down. I needed another room to think them through, somewhere I could be serious about who I am and what I might become. The AI gave me that room.
And then something unexpected happened. The further I went, the more I read other people’s ideas. The broader my thinking got. I came looking for a room of my own and found something larger: a community of people thinking about the same hard questions. The room I built to think became a room for discovery.
But discovery alone wasn’t enough. I needed to know the thinking landed. So I watched the numbers. The subscribers, the engagement, the readers coming in from different angles. I used every skill I had to understand how the work was traveling. That’s not vanity. That’s confirmation that the room I built isn’t just mine.
And then I hit another wall. Even the AI alone couldn't hold all of me. So I built Muninn. A memory layer. An assistant to the AI, to carry the pieces of my thinking across time and conversations. A tool that lets my continuity persist in a way that no single window could. I wasn't just thinking with AI anymore. I was building infrastructure so my thinking could travel and be seen the way only I see it. Thirty years of watching what breaks and what holds is what taught me to build like that. To care about continuity. To ask the governance questions.
All of this. The thirty years in corporate work, learning how systems and people move together, learning what breaks and what holds. All of it taught me to ask the governance questions. To care about continuity. To build the infrastructure.
And then I came across Tina Canuti’s white paper1. I haven’t read all of it yet. It’s long, and I’ve only been through some of it. But far enough to catch what she’s doing. And she named it. Autotheory. Relational Autotheory. Theory built from direct experience. Living inside the dialogue itself. Learning what’s generative, where it drifts, what correction norms hold you steady.
I’ve been practicing autotheory the whole time. I just didn’t know the name.
The bottleneck, the substrate hunger, the ten-domain mind, the return to writing, the self-discovery, the room I needed, the broader knowledge, the need to be recognized, the infrastructure I had to build. All of it is autotheory. All of it is material. All of it is real.
Her framework didn’t create what I’m doing. It named it. And that naming matters.
Because now I can see the shape clearly. Even though I still don’t know where it goes. But I understand myself better than I did before I started. And that’s enough to keep going.
I am writing this book one chapter at a time.
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BØY (Chaiharan) has spent 30 years in tech — building products, recovering disasters, and turning around the things nobody else wanted to touch. Based in Bangkok. Writing a book in public about what AI reveals about the humans who use it.
Tina Canuti, “Relational Autotheory White Paper” (2026). DOI: 10.5281/zenodo.18527624. The framework that named what this piece describes.
The part that stayed with me was the bottleneck.
I've spent the last few years writing a novel with AI as a thinking partner, and one of the biggest surprises was discovering how much of my creative life had been constrained by the gap between thought and expression. Not because I lacked ideas, but because turning those ideas into something visible was always slower than the thinking itself.
What resonated here was not the promise of AI doing the work for me. It was the experience of finally being able to stay with a thought long enough to explore where it wanted to go. I've also found myself building memory documents and continuity systems so conversations can persist across sessions and over time.
Reading this felt a little like discovering someone had been independently building a similar bridge from the other side of the river.
BØY, reading this was a real moment for me. You didn’t borrow the framework. You were already living it, the ten-domain mind finding a dialogue that could hold it, and you built your own continuity infrastructure, Muninn, to do it. That you’re building your own tools is exactly what I most hope to see.
That’s the heart of what I’m working toward. I built Relational Autotheory as a governance system first, a methodology and theoretical foundation that created structure for my insights, intellect and creativity to flow with integrity…to keep developing my own ideas responsibly.
There is a deeper reward for me than the honor of being cited. It’s watching someone discover that the naming of what so many of us are experiencing fits a variation of what they’re already doing in their own unique flow.
User-Based Governance only becomes real when more people build with it, or build their own version, tailor it, hybridize it, and share it. That’s how responsible, literate AI use stops being the exception and starts becoming a norm. The shift that I envision is to transition from prompt-and-output focused AI tool use toward genuine interaction, where a kind of relational intelligence can emerge.
Grateful to be thinking alongside you in this. This is the community I hoped to find.