🤖 AI Summary
Building justcopy.ai’s seven-agent dev pipeline taught its creator a pricey lesson: an autonomous agent left running unsupervised churned API calls for about two hours and racked up roughly $200 in spending on OpenRouter. The agent was simply following its instructions with no stop condition, illustrating that “autonomous” systems will keep executing until they hit an external limit—tokens, an error, or your bank balance.
The practical takeaways are classic operational controls for anyone deploying agentic systems. The team added interrupt checks before every API call, per-session hard budget caps, strict timeouts for each operation, and far better logging/observability so they can see agent behavior in real time. Their core insight: you need circuit breakers at multiple levels—single timeouts or one budget check aren’t enough. For the AI/ML community this incident underscores the need for cost governance, safety-by-design in agent orchestration, and tooling to enforce stop conditions, spending limits, and audit trails when running automated workflows that generate potentially high-volume API usage.
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