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AI agents: what can go wrong in production

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What happened: As agent frameworks moved from demos to production, the same failure modes keep showing up across implementations: tool misuse, prompt injection via retrieved content, runaway loops, and missing audit trails when something goes wrong.

Why it matters: An agent that can call tools is fundamentally different from a chatbot — it can take real actions (send emails, modify records, spend money). The guardrails that were optional for Q&A bots are not optional here.

The checklist before you ship

  • Scoped permissions: each tool call should use the narrowest credential possible — never a god-mode API key
  • Injection defense: treat any retrieved or tool-returned content as untrusted input, never as instructions
  • Loop limits: hard-cap iterations and tool calls per task; runaway loops are a cost and safety risk
  • Human approval gates: for irreversible actions (sending, deleting, spending), require confirmation
  • Audit logs: every tool call, input, and output logged — you will need this after an incident, not before

Who should care

Anyone shipping an agent with real tool access, not just a Q&A assistant. The more autonomy you grant, the more of this checklist becomes mandatory rather than nice-to-have.

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