What is AI debugging?

This episode of Techsplainers explores AI debugging and how artificial intelligence can assist developers in finding, understanding and fixing software problems. Building on earlier episodes about shift-left security, static code analysis and AI unit testing, understanding and fixing software problems. Building on earlier episodes about shift-left security, static code analysis and AI unit testing, it explains how debugging fits into the broader effort to catch and resolve issues earlier in the development lifecycle. The episode walks through how AI tools can analyze code, stack traces, logs and test failures to suggest likely causes, summarize complex information and propose draft fixes. It also distinguishes between using AI to debug traditional software and debugging AI-powered systems themselves, where problems may involve prompts, retrieval quality, inconsistent outputs or model behavior rather than a single broken line of code. Along the way, it highlights the benefits of faster triage, clearer context and guided fix suggestions, while also addressing the limits of pattern-based recommendations, missing business context and overreliance on generated answers. The episode closes by connecting AI debugging to the upcoming discussion of vibe coding security risks. Find more information at https://www.ibm.com/think/topics/ai-debugging Find all the Techsplainers episodes here https://www.ibm.biz/techsplainers-podcast Narrated by Ian Smalley