Why Free AI Inference Endpoints Are Unsafe for Production Agent Workloads

Developers are increasingly running AI agent loops on free-tier model endpoints to avoid costs, but this practice carries serious risks when those agents can modify production systems or handle sensitive data. A structured refusal protocol — consisting of a job card, a preflight gate script, and mid-run exit criteria — can help teams decide which tasks are appropriate for free inference before any model is invoked. The protocol centers on a YAML job card that explicitly defines allowed tools, forbidden actions, data classes, and output sinks, acting as an operator-level contract rather than a model instruction. A companion Python script runs entirely offline to evaluate the job card and block any run that touches customer data, mutates external state, or targets a non-sandboxed output sink. The framework is vendor-agnostic and applies regardless of which free-tier provider hosts the endpoint, emphasizing that the gate inspects the job, not the platform.