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 8, 2026
Apple rented its brain
At his farewell keynote, Tim Cook showed a rebuilt Siri — running on a custom 1.2-trillion-parameter Google Gemini model Apple pays about a billion dollars a year to use. Sit with that. The company whose entire identity is owning every layer of its stack just decided the AI model is the one piece not worth building. That's the most credible verdict you'll ever get that the model is a commodity — and a clean lesson in what's actually worth owning.
- business
- ai-native
- architecture
June 8, 2026
When the government wants a piece of your AI lab
This week, US officials and OpenAI revisited a remarkable idea: the federal government taking an equity stake in the company. A senator went further, proposing a 50% government share in leading AI labs. Strip away the politics and a quieter shift is happening — AI is sliding from 'product' to 'national infrastructure,' something states treat like oil or the power grid and want to own. If the foundation you build on is becoming a strategic asset that governments fight over, 'it's just an API' is no longer a safe way to think about it.
- business
June 8, 2026
The cloud has a smokestack
We call it 'the cloud,' which makes AI sound weightless. It isn't. Every prompt runs through enormous buildings that burn real electricity and evaporate real water — and the buildout is now big enough to strain power grids, raise people's electric bills, and trigger more than 300 state bills in a single year. AI is quietly one of the most physical industries on earth, and that physical limit — not algorithms — is becoming the thing that decides how far it can go. Worth thinking about, even from a keyboard.
- business
June 8, 2026
The labs are going public, and the public isn't sold
Anthropic just filed to go public at a valuation near a trillion dollars, with OpenAI close behind. At the same time, 57% of Americans say AI's risks outweigh its benefits — while using it more every month. Two things worth thinking about: what happens to a company's 'safety-first' principles once a stock price depends on relentless growth, and what it means that the foundation you build on is now run for shareholders who priced in a future that hasn't arrived. This isn't market commentary. It's about the ground shifting under everyone building on these models.
- business
June 8, 2026
Your model has values baked in — and you inherit them
Anthropic refused to let the Pentagon use Claude for mass surveillance or autonomous weapons. The Defense Secretary called it 'arrogance' and an attempt to 'seize veto power' over the military, declared the company a supply-chain risk, and cut ties. Whatever you think of who's right, the fight exposes something every builder glosses over: a model isn't a neutral tool. It ships with refusals, limits, and a worldview its maker chose. Pick a model and you've quietly adopted its values — they become your product's values too.
- ai-native
- business
June 7, 2026
For long-running agents, cost-per-task is the only benchmark
NVIDIA's new Nemotron 3 Ultra isn't pitched on being the smartest model. It's pitched on being cheap to run for hours — built for agents that plan, call tools, and reason across hundreds of turns. That framing is the real story. When an agent runs long, the number that matters stops being the benchmark score or the per-token price and becomes dollars-per-finished-task. Two models at the same token price can differ 2x on a real job. Here's why the leaderboard is the wrong thing to shop on once your agent runs for more than a moment.
- ai-native
- business
- eval