Building an Observable AI Agent With an Open Source Stack

Learn to design and implement an observable AI agent from the ground up using a fully open source stack in this hands-on tutorial. Build a simple agent using LangChain for orchestration and tool integration, then enhance it with OpenTelemetry for distributed tracing and metrics. Integrate Langfuse to capture detailed LLM-level observability including prompts, responses, and evaluations. Discover how to test and improve the performance and answer quality of your AI agent using these open source tools. Master techniques for correlating AI behavior with broader system telemetry and develop patterns for monitoring quality, performance, and cost at scale. Walk away with a working example of an AI agent instrumented with production-grade observability and the knowledge to build, monitor, and continuously improve AI agents in real-world environments beyond simple demonstrations.