AI Engineering/Phase 14/Lesson 24

Agent Observability: Langfuse, Phoenix, Opik

Three open-source agent observability platforms dominate 2026. Langfuse (MIT) — 6M+ installs/month, tracing + prompt management + evals + session replay. Arize Phoenix (Elastic 2.0) — deep agent-specific evals, RAG relevancy, OpenInference auto-instrumentation. Comet Opik (Apache 2.0) — automated prompt optimization, guardrails, LLM-judge hallucination detection.

Learn 45 min Python (stdlib)

Prerequisites: Phase 14 · 23 (OTel GenAI)

#Learning Objectives

Name the three top open-source agent observability platforms and their licenses.
Distinguish what each one is strongest at: Langfuse (prompt mgmt + sessions), Phoenix (RAG + auto-instrumentation), Opik (optimization + guardrails).
Explain why 89% of organizations report having agent observability in place by 2026.
Implement a stdlib trace-to-dashboard pipeline with LLM-judge evaluation.

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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.