Building a developer-friendly AI-assisted debugging workflow Building a developer-friendly AI-assisted debugging workflow Debugging is a core part of software development, but adding AI tools into the mix can feel overwhelming. This guide helps you design a practical, repeatable debugging workflow that leverages AI assistants while keeping humans in the loop. You’ll get concrete steps, tool recommendations, and example code to integrate AI into daily debugging without sacrificing reliability or traceability. Why a structured AI-assisted debugging workflow? AI can triage symptoms, suggest hypotheses, and draft fixes, but it can also hallucinate or miss context. A structured workflow ensures we benefit from AI while maintaining accountability. A well-defined process reduces context-switching, speeds up fault isolation, and improves collaboration across team members with different expertise. Core principles Clear problem framing: state the failure mode, observed symptoms, and expected behavior.…