Notes
Short pieces about the methodology and architecture decisions behind the AI systems I ship — specs, evals, multi-agent orchestration, LLM integration, and the discipline of directing coding agents.
June 15, 2026
The boring AI win is paperwork
The NHS just signed a £120 million deal to give 505,000 staff an AI assistant. Not to diagnose disease — to do paperwork. In trials, the average person saved 43 minutes a day, and one ward cut its backlog of discharge letters by 62% in a month. That's the AI story nobody puts in a keynote: the durable, deployable value is usually the dull, high-volume admin work, not the dazzling demo. Here's why the boring use case is the one that actually pays, and why you should hunt for yours.
- business
- methodology
June 15, 2026
The Fed is watching AI now
In its May report, the Federal Reserve named AI one of the top risks to the financial system. A year ago, 9% of market contacts called AI a possible shock; this spring it was 50%. Big Tech is spending $725 billion on AI infrastructure in 2026, and the money has run ahead of the returns. When the Fed says 'bubble,' builders panic — but the bubble isn't your job to worry about. Buried in that same report is a risk that is yours: almost everyone now rents from the same handful of providers. Here's the part worth your attention.
- business
- architecture
June 15, 2026
The niche model beats the giant
The agent Salesforce just paid $3.6 billion for doesn't run on the biggest, smartest model money can buy. It runs on Apex — a smaller model built for one job, customer support, that Salesforce says beats the top frontier models at actually resolving tickets. That's the detail worth more than the price tag. For a narrow, well-defined task, a model trained specifically for it can beat a general giant that knows everything and masters nothing. Here's why reaching for the biggest model is usually the wrong reflex.
- ai-native
- business
June 15, 2026
The pilot was cheap. Production won't be.
Your AI pilot ran great and cost almost nothing. That number lied to you. When teams take an AI feature from pilot to production, infrastructure costs routinely run three to five times the original projection — and it's a big reason 95% of generative-AI pilots never turn into anything that shows up in the P&L. The pilot is cheap because it's small, watched, and runs on the easy cases. Production is none of those. Here's where the 3-to-5x hides, and how to price it before it ambushes you.
- architecture
- business
June 15, 2026
Your training data has a bill now
For years the working assumption in AI was simple: scrape whatever you can find and train on it. That assumption is dying in court. Music publishers are suing Anthropic for $3 billion, the AI music apps Suno and Udio have already settled and switched to licensed, paid models, and more rulings land this year. The free-data era is closing, and a price tag is going on the inputs. If you train or fine-tune on data, 'we'll just use whatever' is turning from a shortcut into a liability. Here's what changed and what to do about it.
- business
- architecture
June 14, 2026
AI agents just got your credit card
On June 10, 2026, Visa plugged its payment network straight into ChatGPT. An AI agent can now shop and pay at any Visa merchant on your behalf — pick the product, run the checkout, settle the bill — using a credential scoped to that agent with spending caps and merchant limits you set up front. McKinsey thinks agent-driven shopping could be a trillion dollars of U.S. retail by 2030. For two years agents could recommend; now they can spend. Here's what actually changes when software holds the card, and the one question to ask before you hand it over.
- business
- ai-native