Article

What We Learned from a Year of Building with LLMs (Part II): Operations

Eugene Yan, Hamel Husain, et al. · oreilly.com

The operations chapter: daily habits of teams that keep LLM features healthy in production.

The question it answers

  1. My AI feature is live. How do I monitor it and make it better with real usage?

Read with it

  1. The leading open-source LLM observability platform: traces, costs, evals, and prompt management. langfuse.com Tool Langfuse Langfuse
  2. A jargon-free primer on what you should be recording and why. langfuse.com Article What is LLM Observability and Monitoring? Langfuse
  3. The managed alternative, strongest if you already build on LangChain. langchain.com Tool LangSmith Observability LangChain
  4. A follow-along tutorial that gets tracing live in your app quickly. towardsdatascience.com Guide LLM Monitoring and Observability: Hands-on with Langfuse Towards Data Science
  5. A current comparison so you choose once instead of migrating later. confident-ai.com Article Top 7 LLM Observability Tools Confident AI
  6. Explains traces, spans, and generations with the main tools side by side. langflow.org Article LLM Observability Explained (Langfuse, LangSmith, LangWatch) Langflow
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