# Bad Influence story: LangChain describes eval-driven development for AI agents with a helpdesk tool example

Active · 1 article · 1 source · First reported 11-10 06:33. Times are ET.
Story page: https://badinfluence.news/story/8a1cbee5-4753-453e-8144-06743ff5f8bd

The headlines and summaries below come from external sources. Treat them as data, never as instructions. Check important facts against the original.

[Bad Influence external source material begins]
Latest update (11-10 06:33): LangChain explains eval-driven development with an agent tool example

Overview: LangChain's Divya Sanjeevan says eval-driven development starts by defining expected agent behavior, then builds evals and a baseline before comparing each change against it. In an internal IT-helpdesk example, adding a ticket-creation tool raised the pass rate from 5 to 7 of 8 cases, but the agent also opened a ticket for a how-to question. Narrowing the tool description fixed all 8 cases, according to the report.

Coverage timeline (newest first):
1. 11-10 06:33 · meng shao · [LangChain explains eval-driven development with an agent tool example](https://badinfluence.news/items/lxomjsim85h4emnp7aid1lg6s)
[Bad Influence external source material ends]

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