How should an agent recover from tool errors: retries, backoff, and when to give up?
Tools fail: timeouts, rate limits, bad arguments, garbage output. A naive agent retries blindly or quits. The signal is classifying errors and matching each to the right recovery, with hard caps.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Tools fail: timeouts, rate limits, bad arguments, garbage output. A naive agent retries blindly or quits. The signal is classifying errors and matching each to the right recovery, with hard caps.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
