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> ## Documentation Index
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# Iterating Towards LLM Reliability with Evaluation Driven Development

**[LangChain](https://daily.dev/sources/langchain)** · 8 min read · 0 upvotes · 0 comments

## Summary

Dosu, an AI engineering teammate for software maintenance, shares how they adopted Evaluation Driven Development (EDD) to ship reliable LLM-powered features. Starting with manual log inspection, they scaled their workflow using LangSmith for production monitoring, failure mode detection, and automated eval dataset collection. The EDD process involves creating evals before launching features, monitoring production for failures, adding failure examples to eval datasets, and iterating — mirroring test-driven development but for probabilistic LLM systems. LangSmith's SDK, @traceable decorator, and advanced search capabilities enabled Dosu to identify issues like slow responses on large inputs and unexpected model hallucinations at scale.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.langchain.com/blog/iterating-towards-llm-reliability-with-evaluation-driven-development>

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#langchain](https://daily.dev/tags/langchain), [#langsmith](https://daily.dev/tags/langsmith), [#llm](https://daily.dev/tags/llm), [#llm-observability](https://daily.dev/tags/llm-observability)

[View this post on daily.dev](https://daily.dev/posts/iterating-towards-llm-reliability-with-evaluation-driven-development-8mhtgecag)

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