Building AI Agents That Actually Work in Production

Why most agents fail

Prototype agents often look impressive in demos, but they break under real user input, inconsistent APIs, and noisy context. Production systems need strict boundaries, auditable state, and recovery behavior.

What works

The best agent systems combine tool selection rules, structured outputs, retries, observability, and a human override path. The goal is not autonomy at any cost; the goal is predictable value.

The product lens

If an AI agent cannot explain what it did, why it did it, and how to undo it, it is not ready for customer-facing workflows.