--- title: "How to Debug & Evaluate AI Agents with Observability — LangChain Guide" url: https://daily.dev/posts/how-to-debug-evaluate-ai-agents-with-observability-langchain-guide-1vosugi2o source_url: https://www.langchain.com/blog/agent-observability-powers-agent-evaluation type: article source: "LangChain" published: 2026-07-08T19:22:56.653Z updated: 2026-07-08T19:23:47.497Z tags: ["llm", "ai-agents", "observability", "langchain", "langsmith"] reading_time: 16 upvotes: 0 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # How to Debug & Evaluate AI Agents with Observability — LangChain Guide **[LangChain](https://daily.dev/sources/langchain)** · 16 min read · 0 upvotes · 0 comments ## Summary AI agents require fundamentally different observability and evaluation approaches than traditional software because their behavior is non-deterministic and only emerges at runtime. Three core observability primitives are introduced: runs (single LLM call captures), traces (complete agent execution trajectories), and threads (multi-turn conversation sessions). Evaluation maps directly to these primitives at three granularities: single-step (unit tests for individual decisions), full-turn (end-to-end trajectory assessment), and multi-turn (context persistence across conversations). Production traces serve triple duty as debugging tools, offline evaluation datasets, and continuous online evaluation inputs. The key insight is that tracing and evaluation are inseparable for agents — production is not just where you catch bugs, but where you discover what to test for. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Agent Observability Powers Agent Evaluation](https://daily.dev/posts/agent-observability-powers-agent-evaluation-zmcjiu8ai) · LangChain · 34 upvotes · 1 comments - [AI Agent Observability 2026: Debug Production Agents](https://daily.dev/posts/ai-agent-observability-2026-debug-production-agents-sxo8wyw1v) · Alex CloudStar · 0 upvotes · 0 comments - [You can’t debug what you can’t see — Observability for AI Agents](https://daily.dev/posts/you-can-t-debug-what-you-can-t-see-observability-for-ai-agents-8yaiqpabv) · CNCF · 1 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#observability](https://daily.dev/tags/observability), [#langchain](https://daily.dev/tags/langchain), [#langsmith](https://daily.dev/tags/langsmith) [View this post on daily.dev](https://daily.dev/posts/how-to-debug-evaluate-ai-agents-with-observability-langchain-guide-1vosugi2o)