The Four Year Bug
Apparently, two hours is too short for a “hard bug”.
I recently shared a story about an AI-induced crash in my code, which I labeled as the hairiest bug I’ve had to deal with in 2024. The top comments on the Reddit thread of the post, however, took a different view.
Instead of discussing the bug itself, the top comments landed on a conclusion: maybe developers like me—solving “easy” bugs – are exactly the kind of people AI could replace. The thread wasn’t a debate—it had already made up its mind. Spending two hours on a debugging session? That’s amateur hour:
But what if it isn’t? What if spending weeks—or even months—on a bug is the real mark of amateur hour? If the goal is to debug faster, maybe it’s worth questioning whether long debugging sessions are really a sign of expertise, or just a sign of something broken.
Maybe, instead of accepting long debugging sessions as inevitable, we should question whether there’s something to learn from the frustrations voiced in the comments.
What are some of the factors that make debugging hard, and how can we address them?
Microservices and Distributed Architectures
One of the first comments highlights the challenges of debugging distributed systems:
Well, we traced the error to this failed request to this API [..] garbage data in this esoteric queue
The mention of an “API” points to a microservices or distributed architecture, where independent services communicate over a network. Sure, it might offer scalability, but it also brings headaches. Debugging across multiple services is slow, messy, and often feels like untangling a web of invisible threads.
And yet, this complexity is treated as inevitable. But is it really? If you’re not running at global scale, maybe it’s worth asking whether these trade-offs are actually helping or just making life harder. At the very least, when such a systems causes month-long debugging sessions, this should be seen as a red flag against the complexity of the system rather than a badge of honor.
People problems
Another part of the same comment hints at non-technical aspects of debugging:
[..] API we don’t own. Let me go check their logs. wtf does this error mean? Better reach out to their team. 2 days later when they answer [..]
When debugging involves multiple teams, progress slows. Priorities don’t align, communication takes days, and the bug drags on while everyone waits for someone else to act. At some point, this feels like an unavoidable part of working in distributed systems.
But it doesn’t have to be. When a problem spans multiple systems, the simplest solution is often to get everyone involved in a (virtual) room and fix it together. Anything else is just delaying the inevitable.
Side-note: I might be cheating here: I work alone. There’s no waiting on other teams, no priorities to misalign, and no endless back-and-forth emails. If something’s broken, I just fix it.
But that’s not just a luxury – it’s something you can aim for, too. The fewer people involved in building and maintaining software, the fewer opportunities there are for communication breakdowns. And: if your technical boundaries are misaligned with your organizational ones, you’re in for a world of pain.
Dependencies
Unlike the previous sections, this one doesn’t come from a specific Reddit comment. Instead, it’s a well-known source of debugging headaches: dependencies. The more libraries you pull in, the more opportunities there are for things to break: conflicts, hidden assumptions, or even outright bugs in the packages themselves.
The real pain starts when you’re forced to dig through someone else’s code. Debugging stops being about your own work and turns into spelunking through a maze of abstractions, hoping to find the one line of code that’s causing everything to collapse.
Every dependency adds complexity. And while it’s easy to treat these as harmless shortcuts, when a problem arises, you’re not just debugging your code – you’re debugging theirs, too.
Lack of observability
Here’s another quote from the Reddit thread:
Long long ago I had a bug that happened intermittently, with no known reproduction steps, apparently only on live servers, and that we had no way of detecting. [..] From beginning to end, it took four years to solve.
This anecdote highlights what happens when observability is missing. Without even basic logging or monitoring, intermittent issues remain elusive, surfacing only in production and leaving developers to guess at the root cause.
I’ve previously discussed the drawbacks of relying heavily on complex tooling to manage over-complicated microservice architectures. However, if you find yourself in such a situation – or facing the kind of elusive, long-standing bug mentioned above—introducing some targeted tools can be a practical initial step to regain control and enhance system observability.
Observability doesn’t mean piling on layers of complex tooling. A simple, well-thought-out system of logging and metrics is often enough to track down even the hardest-to-reproduce bugs. When a bug lingers for years, it’s a clear sign that the system isn’t giving developers the information they need to do their job.
Conclusion
So, someone was wrong on the internet (but who was it?)
We’ve looked at how debugging breaks down—whether it’s microservices piling on complexity, teams slowing progress, or dependencies adding invisible layers of risk. Tools can certainly help, but they don’t fix systems that are harder to debug than they need to be.
Simpler systems, better communication, and clearer observability make debugging faster and less painful. It’s not glamorous, but it works. If you find yourself spending weeks or months on a bug, maybe it’s time to ask why.
References, sources and memes
Here’s the original article that inspired this post:
- Original article: Copilot Induced Crash
- Reddit discussion: Reddit Thread
For more on my approach to system design, you might find these articles insightful:
Tooling is part of the solution (I’ve tried to not harp on about it too much in this post):
By the way, the post you’re reading was once called “A two hour bug”, but it turns out nobody wants to read about that: it fell completely flat. So, here’s the same post, but with a more clickbaity title.
Here’s this post as a meme rather than a well-articulated argument:
