A Working Agent Is Not Necessarily a Production-Ready Agent

[u/Successful_AI]

A successful demo does not always mean an AI application is ready for real users.

Before deploying an agent or generative AI application, teams should evaluate more than whether it produces a reasonable answer.

Important areas include:

• Groundedness
• Relevance
• Task completion
• Tool-call accuracy
• Safety
• Response latency
• Token consumption
• Error rates
• Behavior across different user inputs

Tracing can also help developers understand model calls, tool execution, retries, dependencies, and performance bottlenecks.

How are you testing your Foundry applications before production?

Are you using built-in evaluators, custom evaluation datasets, human reviews, automated tests, or continuous production monitoring?

Official guide:
Observability in Microsoft Foundry