Debugging is undoubtedly the hardest part of software engineering. Not writing code, not system design, not even getting your PR approved by that one guy who reviews everything like he's grading a thesis. It's debugging.
And often, the most painful bugs aren't even the complex ones. They're the ones where you just cannot get enough data to even formulate a hypothesis on what the actual issue is. You're staring at your screen, you know something is wrong, but you have no idea where to even start looking. The solution is always the same: gather more clues and context.
This is why we rely on developer tools. Postman, Chrome DevTools, even just console.log; these are all just ways to gather clues. And they work great when you're in a nice controlled environment or dealing with a bug you can reproduce reliably. But what happens when that's not true? What happens when the bug only shows up on certain devices, or only in production, or only when three things happen in the right sequence?
That's where it gets extremely painful. Guesswork and brute force become your best options. You've got four tools open, you're context switching between all of them constantly, manually piecing together clues from one tool to another, trying to hold this fragile mental model together in your head. It's incredibly slow and mentally taxing. And honestly? It feels like you're doing the computer's job for it.
As someone who works primarily in React Native, the debugging experience is especially rough. The tooling just isn't there the way it is for web. I tried everything out there, watched endless tutorials, experimented with every setup I could find. I even wondered if maybe I was the problem. Maybe I just wasn't good enough at debugging. Turns out no — debugging really is just that bad.
The core issue, the way I see it, is fragmentation. Your network requests are in one place. Your console logs are somewhere else. Your component re-renders, your state changes, your server response times, all living in different tools, different windows, different mental contexts. And YOU are the glue. You're the one manually connecting "oh this request came back slow" to "oh that triggered a re-render" to "oh that caused the UI to hang." That correlation work is what eats your time. Not the fix itself. The fix is usually a few lines of code. It's figuring out what to fix.
And here's what's been on my mind even more lately: we're in this era where AI coding assistants are genuinely useful. They can read your code, suggest fixes, even write whole features. But they're completely blind to what your code actually does at runtime. They can see the blueprint but they can't see the building. So when you ask your AI assistant "why is this request failing?" it's essentially guessing based on static code alone. It has no idea what actually happened when that code ran.
That gap feels like the biggest unlock waiting to happen in developer tooling. If you could capture what's actually happening at runtime. The full request lifecycle, the state changes, the timing, the cause and effect chains, and translating that into a format that both humans AND LLMs can actually reason about, debugging fundamentally changes. You go from guesswork to hypothesis. From "I have no idea" to "ok here's what happened, here's where it broke, here's what to look at."
The future of debugging isn't more tools. It's better context. It's closing the gap between what your code says and what your code does. And it's making that context accessible not just to you staring at a screen at 2am, but to the AI agents that are increasingly part of how we write and fix software.
I think whoever figures this out well is going to save engineers a stupid amount of time. Because the bottleneck was never writing the fix. It was always figuring out what needed fixing in the first place.
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