AI agents · software engineering · platform · infrastructure
I build agent systems and the platform they run on.
Long-form notes from the inside of the work: agent architectures that survive contact with real repositories, the Kubernetes underneath them, and the unglamorous operational detail nobody writes down.
Writing
- One client, multiple LLM providersEvery project that calls a model carries three constants: a base URL, a key, and a model id — and each vendor spells the request differently, so the swap is a rewrite, not an edit. A gateway turns all of it into one client and one name. The same image request, written four ways, and what the indirection buys beyond convenience.
- The model got better, and I stopped reading itOpus 5 wins the benchmarks and lost me somewhere in paragraph three. Two output styles later — one that fixes the words, one that fixes the shape — and a measurement of which colours a terminal will actually let a model use.
- Drag a div, get a diffVEX turns browser gestures into source-code changes. Three hard problems hide in that sentence — here is what each one taught me.
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