# How to evaluate LLMs before production

DevFeed: [How to evaluate LLMs before production](<https://devfeed.tech/articles/how-to-evaluate-llms-before-production-82.md>)

Original publisher: [Read original article](<https://github.blog/ai-and-ml/llms/how-to-evaluate-llms-before-production/>)

Author: Mariko Wakabayashi

Published: 2026-08-25T21:35:11Z

Content type: article

Language: en

Sources: [GitHub Engineering](<https://devfeed.tech/sources/github-engineering.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Secret Scanning](<https://devfeed.tech/topics/secret-scanning.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [Security](<https://devfeed.tech/topics/security.md>)

Tags: [ai-ml](<https://devfeed.tech/tags/ai-ml.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [code](<https://devfeed.tech/tags/code.md>), [developer-tools](<https://devfeed.tech/tags/developer-tools.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [github](<https://devfeed.tech/tags/github.md>), [llms](<https://devfeed.tech/tags/llms.md>), [secret-scanning](<https://devfeed.tech/tags/secret-scanning.md>), [security](<https://devfeed.tech/tags/security.md>)

## AI overview

This article explains how to evaluate LLM-based systems before moving them into production. Using GitHub secret scanning as an example, it emphasizes defining the product decision first, testing against realistic production conditions, accounting for ambiguity and edge cases, and balancing reduced false positives with sufficient recall.

## Source excerpt

These are the lessons we learned evaluating LLMs for real-world secret scanning. The post How to evaluate LLMs before production appeared first on The GitHub Blog.