How teams stop AI agents from burning API budgets
A production-focused thread asks how teams guard against runaway LLM spend when retry bugs or stuck loops flood the API. The consensus forming in the replies favors per-run spending caps over daily limits, kill-and-alert rules when a run exceeds multiples of its median cost, and mandatory human approval before retry loops repeat. The takeaway: most surprise bills come from missing stop conditions, not from model pricing.