From 0 to Dev in One Day: What a Real Coding Harness Actually Looks Like
A summer manual for the curious non-developer who keeps seeing people build apps out of thin air and wondering: could I actually do that?
Everything I have published: essays and manuals from From Lab to Life, research papers, and the archive. Each work tells you where you can read it.

Start here
A summer manual for the curious non-developer who keeps seeing people build apps out of thin air and wondering: could I actually do that?
How Claude Code plus Playwright via MCP became an autonomous testing loop in early 2025, before "loop engineering" had a name.
Inside the machinery that powers modern AI development, and why understanding it matters even if you never write a line of code
A practitioner's comparison of three coding-agent philosophies.
Two years ago, I started an experiment. I wanted to know whether I could build production-grade software products without writing most of the code myself. Not because I was lazy. Because I had thirty years of product ideas and not nearly enough development hours to explore them.
Five days testing Augment Code's Intent orchestration tool on the production Lumina platform (building Lumina Pro).
New essays from From Lab to Life arrive on Substack before they reach this library.
How Augment Code’s Intent Just Changed Everything — Again
The Lumina Widget build story: a 30-day sprint from concept to production on a budget of about $100 in AI credits, using Augment Code with Claude Haiku 4.5.
How the first version of Lumina was prototyped in Google AI Studio and taken to production on Firebase in 48 hours.
A Two-Year Journey From Fiction to Reality (and the Creativity Blockers Still Holding Us Back)
What happens when you give an entry-level AI model the right tools and see if it can build complex software? That’s exactly what I tested in my latest research, and the results reveal something fascinating about the path toward Artificial General Intelligence (AGI).
The Claude Desktop coding-agent experiment. Documents the real productivity gains alongside the quality constraints: what worked in conversational programming, where human oversight was still required, and why context management was the deciding factor.