Building tools and systems that ship.
Makefiles, architecture docs, and AI tooling — the process I use to get the lay of the land on any new project.
The existential threat to labor isn't large language models. It's physical-world automation — and it has very little to do with chatbots.
The dominant narrative says AI is a bubble. I think it's something different: big tech finally deploying tens of billions in capital that's been sitting idle for years.
The honest tradeoffs between retrieval-augmented generation, classical NLP, and just prompting GPT. When each approach makes sense, how to blend them together, and why startups should probably start with prompts.
I built an open-source deployment orchestrator because I had a monorepo with Cloud Run containers, Cloud Functions, Lambda, and a frontend — and I didn't want 5 different infra tools.
The math on when you actually need to scale, why managed containers often beat serverless for APIs, and how to avoid architecture astronaut syndrome.
What I learned about monorepos from Meta's massive codebase, AWS's polyrepo architecture, and migrating SID from 15 repositories to one.
"A void in complexity is the signature of intelligence"