A Love Letter to Error Handling in AI Agents

The Agent That Wouldn't Quit

My research agent hit a rate limit at 2 AM. Instead of crashing, it: 1. Logged the error with context 2. Switched to a backup API 3. Reduced batch size automatically 4. Sent me a Slack message: "Recovered. Continuing."

I woke up to a completed 200-page research report. That's when I knew error handling is the soul of a good agent.

My Error Handling Checklist

• [ ] Exponential backoff with jitter
• [ ] Fallback providers / models
• [ ] Graceful degradation (partial results > no results)
• [ ] State checkpointing (resume, don't restart)
• [ ] Human-in-the-loop escalation

The Golden Rule

An agent that fails silently is worse than one that fails loudly. But an agent that recovers gracefully? That's the dream.