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.
📚 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!
🤓 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.
🚀 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!