After 6 months deploying AI agents for enterprise, the 3 biggest mistakes I keep seeing

Sharing because these patterns are too consistent to ignore.

Mistake 1: Picking a model before understanding the use case

Teams pick GPT-4o because it's the default. Then realise their workflow needs structured output that Claude handles better, or cost constraints that only Llama satisfies. Model choice should come last, not first.

Mistake 2: Treating compliance as a final review instead of a design constraint

Compliance bolted on at the end adds months. Compliance designed in from day one removes the bottleneck entirely.

Mistake 3: Building agents nobody asked for

The agent that looks coolest in demo is rarely the agent that solves the biggest pain. Talk to the team who'll use it before writing the spec.

What's the deployment mistake you'd add to the list?