There's No Limit to How Bad Code Can Get

1. LLM can fix this in my experience. an LLM, especially the more modern ones, have way more short term memory than most humans (or at least way more than me). They can dig through this kind of code and figure out all the edge cases, write test, suggest various paths to make things better and then execute on those paths. On request they will happily setup dev systems, staging systems, whatever it takes to make the transition safe. At least that's my experience. They can dig much further than I ever would.

2. Short of and maybe separate to the LLM fix, this pattern of technical debt I think is nearly inevitable, at least with humans. In a perfect world, every human and every reviewer knows exactly what architecture to write and what tests to convey all of the rules and assumptions because no matter what, people are going to leave. I've never seen that code base though. So the rules and assumptions are at best half written down, maybe in some comments or docs, comments or docs that the next person to edit that part of the code base may or may not see. And so it goes.

I work on a code base that runs on Windows, Mac, Linux, Android, iOS. Those OSes change over time, their requirements change, their APIs change, the world changes and new APIs are needed for new things people do, and our original choices for cross platform solutions, no longer fit perfectly. We need to keep moving and shipping and we can't just stop the world and re-architect. Further, like the OP, not everything is written down and communicating across hundreds of programmers is hard. So yes, not every decision is perfect. It never will be. Fortunately we work to fix these things and pay down our technical debt but it can take 5 to 10 years before we can finally remove some old path while we wait on usage numbers for old OSes to go down far enough that we can remove those paths and switch everyone over to the new. And then the cycle repeats.

100KLoC sounds like paradise compared to the latest codebase I touched. Having the signal to noise ratio fluctuate wildly at every member & file is highly distracting. When the information is dense and consistent, you can drop into a flow state more easily.

Four character variable names might sound awful but they can have an advantage. It's a form of compression once you are adapted to it. It forces you to keep things simple. When we can write an entire novel for a variable name, we may be tempted to inflate the scope of a solution.

No comments is universally a feature. If I want justification for a section of code, I am going to check git blame, PRs, linked issues, email, project management system, etc. The only code comments I value less than those written by humans are those written by LLMs. It is beyond pointless to shit up a codebase with this stuff. You could just ask the LLM to give you a live interpretation of the current state of the code instead of risking something falling out of sync.

I'd phrase it differently; we're now able to accumulate technical debt faster than ever, without even building the institutional knowable needed to keep it sane. While the models writes novels about what it's doing that no human or LLM will find any use for.

But at the same time; if the LLM makes coding 5-10x faster, there's plenty of left-over time we can now spend doing things properly. Document, test, plan, refactor, lint, use CI tooling. There is no excuse now that LLMs reduce the pain threshold for all of them.