We’ve all been there: staring at a baffling bug, unsure where to start. Too often, debugging turns into randomly poking around, wasting time and chipping away at our confidence. Debugging is an art most of us learn through trial and error—but it doesn’t have to be that way. What if you had a toolbox of techniques to tackle bugs systematically and efficiently? That’s what this talk is all about.

In this session, we’ll take on a brand-new codebase—written by an AI, because why not—and dive into debugging as if we just inherited it. Together, we’ll explore practical techniques for systematically tracking down even the trickiest issues. Along the way, we’ll also look at how to make your code more resilient to prevent bugs before they happen.

Here are some of the techniques we’ll cover:

• Speeding up the iteration cycle
• Pinpointing the issue in the code
• Finding the commit that introduced the bug with git-bisect
• Debugging the data
• Fuzzing for edge cases

But debugging isn’t just about tools. It’s also about mindset. When do you switch gears from fast, intuitive debugging to a slower, more systematic approach? When is it time to take a step back and clear your mind?

Drawing from real-world experience debugging code in high-stakes environments—like medical devices—I’ll share practical skills I’ve picked up over the years to help you approach bugs with confidence.

If you’ve ever felt overwhelmed or stuck while debugging, this talk will arm you with the mindset, tools, and techniques to debug smarter, not harder. And who knows—you might even fall in love with debugging, just like I did.