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# Behind the Scenes: Accelerating the AI Agent DevOps Lifecycle with End-to-End | LIVE159

**[Microsoft Developer](https://daily.dev/sources/microsoftdeveloper)** · 8 min read · 1 upvotes · 0 comments

## Summary

A conference session panel discussing the challenges of building and optimizing AI agents in production. The speakers cover why agents are harder to test than regular software due to their non-deterministic, stateful, and long-horizon nature. They introduce Microsoft Azure AI Foundry's approach to agent observability and evaluation, including eval rubrics for multi-dimensional agent assessment, golden datasets for regression testing, and the Foundry Agent Optimizer for continuous improvement. The session also touches on single-turn and multi-turn conversation evaluation, trace replace functionality, and the concept of evaluation-driven development as the new TDD for AI agents.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=gFTjd-rqssA>

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---

Tags: [#devops](https://daily.dev/tags/devops), [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#observability](https://daily.dev/tags/observability)

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