My day job: I lead the Public Sector business unit at Straive, and I'm CEO of Double Line — the company we built and sold, now a subsidiary there.
This site is about everything else. I take things apart to understand them — a retirement model, experiments with LLM internals, the Godot binary behind a game I was curious about. Most of it starts as a question I can't answer and ends as something that runs.
Lately the questions are all about AI, and overall my observation is: the people who understand how these models work have never run a business, and the people running businesses use these models daily without knowing how they work. I'd like to be a third thing. Writing down the attempt is what the Lab is for.
Case studies with the failures left in, the prompts themselves, and the paths I actually followed.
What persists between conversations and what doesn't, how tool use works, what RAG and embeddings are for, token economics, evaluation — the nuts and bolts that are too often glossed over. I'm not trying to fix the ML engineer - business gap, just wanting to not fall prey to it.
Handled
liveAudit‑grade time tracking for R&D tax credit documentation — built so CPA review is straightforward instead of a scramble at filing time.
Well Spent
liveRetirement tools model running out of money. Almost none model the more common ending: dying with a decade of unspent work in the account. This one leads with that number, if for no other reason than to add some weight to the underspending discussion.
The AI Alternatives Project
ongoingWhich SaaS categories AI can genuinely replace, and which ones only demo well. With a companion bounty board where developers submit their attempts and their Claude Code folders.