There’s a particular kind of project that doesn’t start with a bang, but more of a soft thud as 14 years of technical debt land on your desk. That’s where I’ve been the past few weeks.
We’re embedded with a client team, helping untangle a sprawling legacy app. The original ask was simple: improve stability and get better visibility on what users are doing. But as always, simple on the surface rarely means simple underneath.
📖 Developer Diaries: Sam Lawrence on The Art of the Invisible Fix
First impressions? The codebase is huge. Layers upon layers of functionality, patched over time by different devs, each solving their own problem in their own way. The deeper you go, the more you uncover; duplicated logic, forgotten threads, and features that haven’t been touched in years.
It’s also been a great reminder that when you’re dealing with legacy systems, progress often looks… invisible. Especially early on. You're not pushing big features. You’re not rewriting whole modules. You're poking at memory leaks, tracking elusive crashes, and trying to figure out why the app doesn’t clean up after itself when you close a screen.
Crash hunting in this kind of environment is more detective work than development. These aren’t crashes you can trigger with a button press. They emerge over time, usually tied to threading issues or objects lingering in memory. Some logs point you in the right direction. Others give you just enough to know something’s wrong, somewhere, sometime.
The approach we’ve taken as a team is to divide and conquer. One of us is combing through the UI, fixing anything obviously off. Meanwhile, I’m living in the crash logs and profiling tools, trying to isolate patterns and figure out which issues are worth chasing. It’s meticulous. Sometimes thankless. But when you finally piece something together, it’s a good feeling.
We’ve also had to work closely with the client’s internal teams, which is its own kind of challenge. Like many orgs with large, long-lived products, they’ve got multiple teams, multiple systems, and not always a clear line of communication between them. It’s easy for someone in QA to be writing automation tests without the dev team even knowing. We’ve been nudging that along: pulling people into stand-ups, encouraging more cross-talk, trying to model a process that could stick after we’re gone.
Access has been another friction point. In high-security environments, you can’t just dip into production logs or peek at Jira tickets. So we’ve been helping them think about what realistic simulations look like. Can we artificially flood the app with documents? Mimic bad network conditions? Find ways to surface those edge-case crashes that only appear in real-world chaos?
One of the tools I’ve leaned on hard is Copilot inside Rider. With a codebase this big and undocumented, it’s been a huge time-saver just being able to ask, “What’s the purpose of this class?” or “Where’s this method being used?” It doesn’t give you the full picture, but it’s enough to orient yourself. Combine that with walkthrough recordings and a few key team conversations, and you start to build a mental map.
What has been interesting is watching the trust build. In week one, it was all about proving we understood the landscape. Now, a few weeks in, they’re asking us for recommendations on architecture, best practices, even future stack decisions. That’s the sweet spot. When the work moves from reactive fixes to proactive thinking.
📖 Developer Diaries: Sam Lawrence on The Art of the Invisible Fix
Of course, the irony is that our success might not be fully measurable within the timeline of the engagement. Some fixes are speculative; our best guess based on symptoms and logs. You patch it, ship it, and then... wait. Weeks later, maybe, the crash rate drops. Or maybe it resurfaces somewhere else. It’s not always glamorous, but it’s foundational work. The kind that quietly makes everything better.
So no, there’s not a big flashy demo to show yet. But we’re building confidence. In the code. In the process. In the people.
And sometimes that’s the most valuable thing we can deliver.
This is an AI generated summary of a conversation with Dootrix Technical Lead - Sam Lawrence