The archive
Two posts a week on the gates, the patterns, and the cost discipline that turn AI demos into software people depend on.

How to Deploy an LLM in Production: A Gated Checklist
Seven gates, each one blocking the next. Most projects should die at Gate 1, and the ones that survive all seven are the ones people actually trust.

You Already Manage an AI
Prompting, examples, review: you learned all of it the first time you delegated. AI fluency is management fluency with a shorter feedback loop.

Speak English About AI
Jargon is a tax you pay in stakeholders. Plain language isn't dumbing it down; it's the half of deployment nobody budgets for.

Cost-Per-Outcome, Not Cost-Per-Token
The token price is the smallest number in your AI economics; the one that matters is what it costs to produce an output that survives verification.

Quality gates that keep AI-generated code honest
AI writes plausible-but-wrong code at high speed. These automated gates — scoring, smoke tests, visual review, a pre-push hook — stop it from shipping.

How I run a gated build pipeline for AI-generated production apps
AI can write a whole app in an afternoon. The hard part is making sure the app is correct, safe, and maintainable. Here's the gated pipeline I use to get there on the first build instead of the fifteenth.

Give your AI a memory so you stop re-explaining yourself
A small file-based memory turns a forgetful assistant into one that compounds — better output, fewer tokens, no more repeating yourself every session.

Prove the data before you write a line of app code
The most expensive AI app failures are data failures. A data-contract gate — with a reproducible anchor number — stops them cold.

The app-factory pattern for internal data apps
Stop hand-building one-off internal dashboards. Scaffold them from templates so auth, health, branding, and deploys are identical every time.

Real AI leverage without blowing your budget
How a solo operator or small team gets outsized results from AI while keeping the monthly bill boringly small.