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2 posts
Inside the AI agent backend: LangGraph runtimes cached on a 16-part key, progressive skill disclosure with a 128-tool cap, compare-and-swap settings mirrors, and a feedback pipeline that groups meetings by red flags.
How the team scaled LLM-assisted development with specialized agents, an adversarial test-triage workflow, and hooks executed by the harness — the layer that instructions cannot override.
1 post
The first post in my Techstack Challenges series, about a client engagement where the coding standards were not a wiki page but executable files in the repo, loaded by both humans and coding agents before every change.