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 14, 2026
The AI coding speedup is smaller than it feels
In a controlled study, experienced developers using AI on their own codebases were measurably slower on complex tasks — and felt 20% faster the whole time. A 2026 follow-up with better methodology landed near a small positive, not a big one. Meanwhile ~93% of developers use AI tools and headline productivity has barely moved. None of this says AI coding is fake. It says the feeling of speed and the fact of speed have come apart, and if you manage by feel you'll manage wrong. Here's how to tell the difference.
- methodology
- careers
June 14, 2026
The AI rules that change three times a year
Colorado passed a landmark AI law against algorithmic discrimination. It was set to take effect February 2026, then pushed to June 30. In December the federal government signed an order to preempt state AI laws and named Colorado's directly. Then in May 2026 Colorado delayed its own law to January 2027 and scaled it way back. If you were building to that rulebook, your target moved three times in a year. You cannot build to a law that won't sit still — but you can build to the principle underneath it, which barely moves at all. Here's how.
- business
- security
June 14, 2026
The AI that hunts its own bugs
Anthropic's Claude Mythos found thousands of zero-day vulnerabilities across every major operating system and browser — including a 27-year-old bug in OpenBSD and a 16-year-old flaw in FFmpeg — and wrote a working exploit on the first try in over 83% of cases. It was deemed too dangerous to release publicly; instead a handful of giants got early access under Project Glasswing. This is the clearest look yet at AI's double edge: the same tool that finds your bugs before attackers do is the one that finds them faster for attackers too. Here's how to think about it.
- security
June 14, 2026
The fast model just got smart
For two years you made a trade every time you picked a model: fast and cheap, or smart and slow. Gemini 3.5 Flash just broke it. The 'Flash' tier — the cheap, quick one — now scores 55 on the Artificial Analysis Intelligence Index, ahead of Grok 4.3 and Claude Sonnet 4.6, while running over 280 tokens a second. The fast model is no longer the dumb model. That should make you re-open a decision most teams quietly froze a year ago: which model is your default, and is it still the right one? Here's how to think about it — including the catch.
- ai-native
- business
June 14, 2026
The AI layoff that comes back cheaper
Forrester predicts that half of the jobs cut in the name of AI will be quietly refilled — offshore, or at meaningfully lower pay. 55% of employers already regret their AI layoffs. And in plenty of cases the AI never replaced anyone: the work got shipped overseas and called automation. Amazon's cashierless 'Just Walk Out' stores turned out to lean on remote workers in India watching the cameras. If you're a worker or an honest builder, the lesson is the same: 'we cut staff because of AI' is often a story about cost, wearing AI as a costume. Here's how to read it.
- business
- careers
June 14, 2026
You're running twelve agents. Half work alone.
The average company now runs about 12 AI agents, on the way to 20 by next year — and half of them operate entirely on their own, not talking to any of the others. We rushed to add agents faster than we wired them together, so most enterprises have a drawer full of clever tools that each see a sliver of the work and none of the whole. The value was never in having more agents. It's in the connections between them, and that's the part almost nobody built. Here's why the gap opened and how to close it.
- agents
- business