Human In The Loop

You'll learn what an AI agent is as a loop of observe, decide, act and check, why mistakes compound inside that loop, what a useful hand-back to a human looks like, and why you should judge agents by the cost of the errors they miss rather than the number of tasks they finish.

You will learn how to treat the human in a multi-agent pipeline as a slow, rate-limited agent and build the protocol around those limits with escalation budgets, async queues, decision packets, timeout defaults and two metrics that show whether the setup is working.

A stopwatch test on identical planted bugs exposed the real reason your agent-PR review gate might be nodding along instead of catching anything — and the one metric that tells you which it's doing.