So with LLM outputting average code, and people using LLM more and more, I guess the average code will become worse over time ?
1. Things are evolving. The models, and especially the harnesses, are getting better. There was an inflection point at the end of last year, so anything before that is no longer relevant to the discussion. Probably anything before now, since we've had about 6 months with real agentic engineering and things are starting to become clearer.
2. Application and effectiveness is not equally distributed. This is the newest and most significant technology humans have created. We are still building and figuring it out. Some people are better at it, some people use it rather unwisely.
The problem isn't the amount of code, it's how fitting/unfitting the abstractions are. Wrong abstractions are bugs in waiting. If there's much code with wrong abstractions, future change becomes difficult.
Source: me, I've created many bad abstractions and they led to much pain...
Its also really bad at inventing and leaning on invariants. I make rules in my code all the time - "by the time we get to path X, we know Y and Z are true.". In aggregate, these invariants make code simpler and easier to reason about. But claude doesn't do that. It just kind of - slops through and adds bespoke "just in case" workarounds all over the place. Every time I read through code its written - without fail - I find bad design / architectural choices.
Maybe mythos will change this. But for now I've slowed way down on my claude code usage. You can't build a skyscraper on a foundation of mud.
When I eventually read through the current state of the upload processing code it was like an absurd tree of checks on checks on fallbacks on triple checks added in response to whatever bug I reported in a bizarrely additive way and could be massively simplified (which would also make it less brittle to edge cases that then demanded more checks and workarounds).
The other issue is that for the upload API, there is documentation but not for every little bug or edge case so each time the model "wakes up" and loads everything into context it sees that crazy web of checks and edge cases as the only source of truth for the API so is hesitant to touch anything unless 100% necessary which then leads to more conservative behavior of additive code which makes the problem worse over time.
Codex seems a bit better but I still have to guide it towards proper abstractions/refactors to avoid that piling on cruft effect.
At work we are integrating with third party platform to automate excel-powered calculations. It is awful. Rendering the table in browser takes 10s or one click on Export button will throw backend in OutOfMemory state.
I don't disagree there is a lot of slop being produced right now, but I'm still optimistic in the long-run.
On a more serious note, I wonder if this might eventually encourage people to use languages that are a little harder to write but much more concise (functional languages for instance). When you're paying per-token enterprise bean java style verbosity totally sucks