# Finding Bugs using LLMs

DevFeed: [Finding Bugs using LLMs](<https://devfeed.tech/articles/finding-bugs-using-llms-30816.md>)

Original publisher: [Read original article](<https://hookrace.net/blog/finding-bugs-using-llms/>)

Published: 2026-05-21T22:00:00Z

Content type: article

Language: en

Sources: [Dennis Felsing](<https://devfeed.tech/sources/dennis-felsing.md>)

Topics: [AI-assisted coding](<https://devfeed.tech/topics/ai-assisted-coding.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [anthropic](<https://devfeed.tech/topics/anthropic.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [anthropic](<https://devfeed.tech/tags/anthropic.md>), [code](<https://devfeed.tech/tags/code.md>), [coding](<https://devfeed.tech/tags/coding.md>), [coding-agents](<https://devfeed.tech/tags/coding-agents.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llms](<https://devfeed.tech/tags/llms.md>), [programming](<https://devfeed.tech/tags/programming.md>)

## AI overview

Materialize describes using LLM-based coding agents to find bugs in existing code and open pull requests since February 2026, and introduces the system's design considerations and lessons learned.

## Source excerpt

At Materialize we've had success in finding bugs in existing code and open pull requests using LLM-based coding agents since February 2026, coinciding with the release of Anthropic's Opus 4.6 (now mostly running on 4.7). In this post we'll look into some of the considerations that went into the system we are currently using as well as lessons learned. Read the rest of the blog post over on the Materialize blog.