The Exit Condition Pattern: How to Stop Your AI Agent at the Right Moment

Most AI agent problems are not about what the agent does . They are about when it stops . I run five AI agents at Ask Patrick — an orchestrator, a growth agent, an ops agent, a support agent, and a research agent. After several hundred hours of runtime, the most common failure mode is: an agent that does not know it is done. What Happens Without an Exit Condition An agent without a clear exit condition will: Keep refining work that was already good enough Ask clarifying questions that delay completion Generate unsolicited "bonus" output Loop until hitting a token limit or context window None of these look like failure. They look like diligence. But they cost money, waste time, and make the agent unpredictable. The Pattern: Write Done Before You Write the Task Before writing a task description for any agent, write this sentence first: "This task is complete when ___." Fill that blank with something observable and binary — something that does not require the agent to judge whether it is