The Journey

Seventeen finished pieces of work were invisible to my own tracking system, and the cause wasn't effort or memory. A Berkeley talk gave me the name for what fixed it: an ontology. Here's the version that fits a one-person company.

Last week I showed the demand numbers for AI consultancy are dire. This week a veteran operator explained the part I missed: the demand isn't dead, it's mute. Nobody buys AI. They buy outcomes, told concretely enough to defend to a board.

Swapping the two LLMs behind an autonomous trading bot from Opus 4.7 to 4.8, live, without it missing a beat. The trick was replaying 78 real prompts first.

The YC president gave a talk describing, almost item for item, the AI system I already run. The validation lasted about ten minutes. Then I noticed the word neither of us was saying.

I got phished from my own verified domain, using an API key I'd leaked myself: what actually leaked, how fast it happened, and what I changed.

A friend said it should be a business. I spent forty years around operations and resilience, so I assessed it honestly, decided it was not, and built it anyway, for free. Here is the reasoning, and why the map of your estate should be a file no company owns.

A $1,000-an-hour AI consultancy playbook is doing the rounds. The demand data, and a friend who sells everything except this, disagree.

Same spec, same model, two methods: a seven-part goal prompt against a full agent framework. The lean prompt tied on correctness and won on time, cost, and clutter. Here are the numbers.

Eleven days of unattended trading. Five losing trades, one winner covered them, +$132 net. What the system did right, what drifted, what I fixed on return.

AI can write working code in minutes. The hard part is trusting it without reading every line. Here's what actually makes AI-built code trustworthy.

An AI agent spent an afternoon optimising one of my apps. It tried a change, measured it, kept the one that was genuinely faster, reverted three that weren...

Six AIs told me Graphify uploads your code. I checked by running it, and the actual gotcha is smaller, quieter, and easy to miss.

Claude has a habit of collapsing an open conversation into three multiple-choice options, and once you see why it does it, you can stop it doing it to you.

A field note from researching Graphify: the real privacy model, the honest token numbers, and why I check the source before I publish.

Same code, same market, three time periods. One made $964, one lost $217, one's up $321. The difference wasn't the algorithm.

I built a second brain in 2020 and drowned it in my own output. PARA was the right answer to the wrong era. Here is the shape that fits this one.

How a trading agent reveals the game retail can actually win — by playing where the funds can't or won't go, and learning to love the play.

I checked the XML files BOS-AI used to store 'institutional memory' for thirty agents. Every tag was PLACEHOLDER_X. So I deleted all twelve.

Coinbase lists 15 perp markets. Most alts are leveraged BTC with noise. The case for staying with three, and the one coin I'd seriously paper-test.

I shipped v6 of agent-11 last month. The biggest single change was deletion. The deployed CLAUDE.md went from roughly 250 lines to under 80. The MCP prof...