PolicyAware Targets Runaway AI Agent Loops Before They Inflate Cloud Bills

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Autonomous AI agents can enter recursive loops where repeated LLM calls and tool invocations generate thousands of redundant API requests, potentially producing five-figure cloud bills before anyone notices. Traditional monitoring tools detect service load after the fact but cannot identify an AI agent as the source or intervene in time to prevent financial damage. PolicyAware is a governance tool designed to act as a control layer, enforcing spending, rate, and iteration limits on agentic workloads before costs compound. It includes a static scanner that integrates into CI/CD pipelines, flagging unbudgeted API routes, missing loop termination conditions, and unprotected tool definitions during code review. By blocking pull requests that fail critical policy checks, the tool aims to catch structural risks before they reach production environments.

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