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AI Agent Observability & Evaluation

Welcome to Bonus Unit 2! In this chapter, you’ll explore advanced strategies for observing, evaluating, and ultimately improving the performance of your agents.

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📚 When Should I Do This Bonus Unit?

This bonus unit is perfect if you:

- Develop and Deploy AI Agents: You want to ensure that your agents are performing reliably in production.
- Need Detailed Insights: You’re looking to diagnose issues, optimize performance, or understand the inner workings of your agent.
- Aim to Reduce Operational Overhead: By monitoring agent costs, latency, and execution details, you can efficiently manage resources.
- Seek Continuous Improvement: You’re interested in integrating both real-time user feedback and automated evaluation into your AI applications.

In short, for everyone who wants to bring their agents in front of users!

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🤓 What You’ll Learn

In this unit, you’ll learn:

- Instrument Your Agent: Learn how to integrate observability tools via OpenTelemetry with the smolagents framework.
- Monitor Metrics: Track performance indicators such as token usage (costs), latency, and error traces.
- Evaluate in Real-Time: Understand techniques for live evaluation, including gathering user feedback and leveraging an LLM-as-a-judge.
- Offline Analysis: Use benchmark datasets (e.g., GSM8K) to test and compare agent performance.

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🚀 Ready to Get Started?

In the next section, you’ll learn the basics of Agent Observability and Evaluation. After that, its time to see it in action!

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