I used to believe serious building required serious sitting. The desk, the monitor, the four-hour uninterrupted block. Then I spent a week failing to find any of those things.
I'm in Panama City one day, a coffee shop in a city I barely know the next, always between meetings or waiting for flights. For months I treated this as a building problem. I wasn't productive because I didn't have the right setup. I was waiting for conditions that never came.
That was the wrong diagnosis.
The taxi ride that changed how I build
Last week I was stuck in Panama City traffic. I had an idea for a feature. Normally I would've made a note and hoped I'd remember the context later, which I never did.
Instead, I opened my phone and started a conversation with Claude. Not to write code, which sounds terrible on a phone. To think through the problem with a partner who could keep up.
I described what I was thinking in the messy way you'd talk to a coworker you trust. By the time the taxi arrived, we'd sketched out the entire approach. The agent helped me think through edge cases I hadn't considered. It suggested implementation patterns I'd forgotten existed. It asked clarifying questions that sharpened my thinking.
I didn't write a single line of code in that taxi, but the building happened anyway.
What AI-augmented building actually means
This isn't about coding on your phone. It's about keeping building momentum alive regardless of where you are.
The agents I work with handle the parts that used to require me at my computer. They can draft code, research technical approaches, debug issues, refactor entire modules. What they can't do is understand what I'm actually trying to build and why.
That's still on me. And that's the work I can do anywhere.
I've started structuring projects differently because of this. I think in conversations now instead of thinking in files. When I'm walking to lunch, I might dictate thoughts about architecture decisions. When I'm waiting for someone, I might review code the agent generated based on our last discussion and provide feedback.
The agent remembers everything. It knows the context of our last seventeen conversations about this project. It knows the patterns I prefer, the trade-offs I care about, the constraints I'm working within. I don't have to rebuild that context every time. I just pick up where we left off.
The unexpected benefits of building in fragments
This actually makes me a better builder.
I'm thinking about problems in smaller, more frequent sessions. Instead of waiting for mythical four-hour blocks of deep work, my subconscious gets more chances to process. I catch issues earlier. I explore more alternatives.
And here's something I didn't expect: building this way feels more human, not less.
I'm having conversations about my work. I'm explaining my reasoning, questioning assumptions, iterating on ideas. That's how humans have always collaborated on complex problems. The difference is that my collaborator is an AI agent that never gets tired, never forgets context, and can instantly generate working code based on our discussions.
But the thinking, the deciding, the creative work, that's still happening in my very human brain.
Traditional building isn't dead
I'm not saying this replaces sitting at your desk and diving deep into code. When I'm back at my computer, I still do that. But now that's just one mode of building instead of the only mode.
That shift has made me productive as a solo founder who's constantly on the move. I'm not fighting my circumstances anymore. I'm building with them.
The future of building isn't about finding more time to sit at your computer. It's about having partners, AI partners, who can build with you wherever you are, however you work, whenever inspiration strikes.
For me, that's been completely transformative. And I think we're just getting started.
FAQ
Q: Isn't this just glorified note-taking with extra steps?
No. Note-taking captures ideas for later. This is thinking through problems in real-time with a partner that can generate working implementations, suggest patterns, and maintain full context across weeks of conversations. The output isn't a note, it's architectural decisions, debugged logic, refactored code. You're building, just not typing.
Q: How do you prevent the AI from going off in wrong directions when you're not at your computer to course-correct quickly?
I don't ask it to build entire features autonomously. I'm having a conversation, which means I'm there, providing direction in real-time. The agent suggests an approach, I question it, we iterate. It's collaborative, not delegated. The difference from being at my desk is I'm speaking instead of typing, and I'm reviewing thinking instead of immediately writing code.
Q: Does this actually work for complex technical problems or just simple features?
I've used this approach for everything from edge case debugging to architecture redesigns. Complexity isn't the limiting factor, clarity is. If you can explain the problem clearly, an agent can help you think through it clearly. What doesn't work is vague handwaving. But vague handwaving doesn't work at your desk either.