The Journey
Field reports from building with AI in public. What's working, what isn't, and what it cost me. Open numbers, the failures before the wins.
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I built the same tool two ways to settle an argument
Spec-first or goal-first? I didn't believe either side, so I built the same tool both ways with one spec and one model. Both worked. The bill didn't tie.
Eleven days I didn't touch it
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.
How to trust AI-written code you didn't read line by line
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.
Everyone's selling autonomous AI agents. I built one, and the real lesson was 20 years old.
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...
I Ran Graphify. The Privacy Trap Is Real, Just Not the One Everyone Warned Me About
Six AIs told me Graphify uploads your code. I checked by running it, and the actual gotcha is smaller, quieter, and easy to miss.
The Three Options Trap: Why Claude Keeps Killing the Good Bit
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.
I Almost Told You a Lie. Six AIs Handed It to Me, in Unison.
A field note from researching Graphify: the real privacy model, the honest token numbers, and why I check the source before I publish.
Same system, three different traders
Same code, same market, three time periods. One made $964, one lost $217, one's up $321. The difference wasn't the algorithm.
The Prodigal Second Brain
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.
Building David, Not a Smaller Goliath
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.
BOS-AI had twelve XML files holding nothing
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.
I trade three coins, not fifteen
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.
Half of agent-11 was scaffolding the platform now provides
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...
Now the Real Data Starts
Seven months of building bought me a system that finally tells the truth about itself. The data those seven months produced is mostly unreadable. The clock just started, and not a moment too soon.
What Building a Trading Bot Taught Me About Building Trading Bots
Across 200 trades, the bot was rarely wrong about the market. It was wrong about itself. The dominant failure mode wasn't strategy. It was a system lying to itself about what it was doing.
The House Always Wins. But Retail Can Still Play.
The first move is to see the game. The second is to refuse to play it on the funds' terms — and find the one you can actually win.
The House Always Wins: Why Retail Crypto Trading Is About to Get a Lot Harder
Three forces are converging on retail crypto traders, and none of them favour the small player. The edge isn't intelligence anymore. It's owning the table.
Ten days of letting the check do the work
April 23rd I shipped a blog post about how I'd nearly shipped a fix that referenced three database fields that didn't exist. Author-reviewer collapse. I'd ...
I wrote the rule. Then I skipped it.
Four days ago I published a blog about a bug I'd nearly shipped. The spec referenced two database fields that did not exist — trade.risk_amount and `trad...