// lab notes
Notes, deep-dives, and what we're learning while we build.
AI
Taking an AI agent to production requires treating it as a distributed system—with evals, observability, guardrails, and staged rollout—not just a better prompt.
AI
AI agent reliability in production is measured through task-completion rate, drift-adjusted accuracy, and recovery time from failure—not uptime alone.
AI
Reliable AI agents in production require layered observability, deterministic guardrails, human-in-the-loop escalation, and rigorous evaluation pipelines—not just a good prompt.