[captainbland]

I think the particular problem is if AI is just producing large volumes of code which are unnecessary, because the LLM is simply not able to create a more concise solution. If this is the case it suggests these LLM generated solutions are likely bringing about a lot of tech debt faster than anyone is ever likely to be able to resolve it. Although maybe people are banking on LLMs themselves one day being sophisticated enough to do it, although that would also be the perfect time to price gouge them.

[alan-stark]

Agree. We've seen cowboy developers who move fast by producing unreadable code and cutting every corner. And sometimes that's ok. Say you want a proof of concept to validate demand and iterate on feedback. But we want maintainable and reliable production code we can reason about and grasp quickly. Tech debt has a price to pay and looks like LLM abusers are on a path to waking up with a heavy hangover :)

[quantiq]

We hired some LLM cowboy developer externals that were pushing out a plethora of PRs daily and a large portion of our team's time at one point was dedicated entirely to just doing PR reviews. Eventually we let them go, and the last few months for us has been dedicated to cleaning up vast quantities of unmaintainable LLM code that's entered our codebase.

I think it's still early days, and it's probably the case that a lot of software development teams have yet to realize that a team basically just doing PR reviews is a strong indication that a codebase is very quickly trending away from maintainability. Our team is still heavily using LLMs and coding agents, but our PR backlog recently has been very manageable.

I suspect we'll start seeing a lot of teams realize they're inundated with tech debt as soon as it becomes difficult for even LLMs to maintain their codebases. The "go fast and spit out as much code as humanly possible" trend that I think has infected software development will eventually come back to bite quite a few companies.

[alan-stark]

Yep, it's the early days. Eventually we'll work out something like Design Patterns for Hybrid Development, where humans are responsible for software architecture, breaking requirements into maintainable SOLID components, and defining pass/fail criteria. Armed with that, LLMs will do the actual boilerplate implementation and serve as our Rubber Ducky Council for Brainstorming :)