The gap between an impressive agent demo and a dependable production system is not model quality. It is everything around the model: retrieval boundaries, tool permissions, evaluation, and the operational contract with the team that owns the outcome.
Start with a narrow, high-frequency task with a clear definition of done. Agents that are asked to do everything fail everywhere. Agents that own one workflow end to end can be measured, tuned, and trusted.
Instrument before you scale. Every agent action should be logged with its inputs, retrieved context, tool calls, and cost. Without that trail, you cannot debug a regression or defend an outcome to an auditor.
Finally, treat evaluation as a product surface. A living test set drawn from real traffic, reviewed by the business owner, is the only thing that tells you whether last week's prompt change helped or quietly broke a critical path.
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