Writing
- A year of AI coding at team scale
I used to think editor integration was the load-bearing affordance of AI coding tools. A year of trying to make a team operate consistently changed my mind.
- Evals, after putting them off
I'd read the posts, nodded at the rubrics, never quite got round to building one. Last week I did, and the things it surfaced weren't the things I expected to surface.
- I deleted my embedding pipeline
I built a hybrid FTS5 plus LanceDB MCP server with an Ollama embedding pipeline for my personal knowledge vault. After two months I deleted all of it. This is the long version.
- An evening with OAC, POST, and SigV4
I tried to put a CloudFront-fronted Lambda Function URL with OAC and AWS_IAM in front of an SSE-streaming agent. 100% of POSTs returned 403. Here's the evening.
- LangGraph and Pydantic AI, six weeks apart
I picked opposite frameworks for two agent systems six weeks apart. Same engineer, opposite call. The framing that made both right.
- The cost shape of an LLM-heavy serverless pipeline
My weekly FPL enrichment pipeline costs roughly £1.50 to £3.00 a week. Most of that is the Claude API. What it taught me about cost-engineering this kind of workload.