Posts tagged LLM Observability — AI × software engineering, made practical.
You'll learn how prompt caching makes time-to-first-token depend on the order of your prompt, how to find the lines that break the cache in your agent harness, and how to order the prompt so the cache keeps hitting on every turn.
You'll learn how to log each model decision as a structured record (options, choice, stated intent, context refs and parent link) so you can trace a wrong output in a live LLM app or agent back to its root cause.