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How to ThinkIn the Age of AI

Agent system review is essential maintenance, not optional…

Build feedback loops into agent systems through regular review asking whether agents fired, whether they produced intended outcomes, and whether conditions have changed, treating review as essential maintenance not optional improvement.

When This Fires

Common Failure Mode

Treating review as optional self-improvement that gets skipped when busy: "I'll do my agent review when things calm down." Things never calm down, and the review never happens. Meanwhile, agents are silently degrading. The review must be a non-negotiable scheduled event — an agent itself, with its own trigger, conditions, and success criteria.

The Protocol

(1) Schedule regular reviews: weekly for new agents (Review new agents weekly, established ones monthly…), monthly for established ones. The review itself is an agent with a time-based trigger. (2) For each agent, ask three questions: Did it fire? Check firing rate (Measure behavioral agent progress by displacement rate…, Define agent success as 80%+ firing rate, not subjective…). If below threshold → diagnose (Diagnose before redesigning — identify whether trigger…). Did it produce intended outcomes? Check whether the behavior is still serving its original purpose. If not → the schema may need updating (Name the schema before building the agent — a reliably…). Have conditions changed? Check whether the context the agent was designed for still exists. If not → redesign or retire. (3) Update agent documentation (Document every agent with five components) with review findings. (4) Retire agents that no longer serve a purpose — dead agents clutter your system and create false confidence about behavioral coverage.