A mental model and decision tree for building agent skills incrementally: start with intent, add deterministic tools, then use tests and AI evals to reduce drift and risk.
A pain-driven approach to AI evals: measure first, constrain risk, iterate fast, optimize last.
Turn pain points into repeatable questions and build a lightweight taxonomy of your world.
How chaining LLM calls compounds errors, and why replacing probabilistic steps with deterministic ones improves reliability.
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