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AI makes tech debt more expensive

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Re: AI makes tech debt more expensive

#31

Post by asabla »

leptons wrote: post #12

I asked the AI to write me some code to get a list of all the objects in an S3 bucket. It returned some code that worked, it would no doubt be approved by most developers. But on further inspection I noticed that it would cause a bug if the bucket had more than 1000 objects because S3 only delivers 1000 max objects per request, and the API is paged, and the AI had no ability to understand this. So the AI's code would…

at some extent I do agree with the point you're trying to make.

But unless you include pagination needs to be handled as well, the LLM will naively just implement the bare minimum.

Context matters. And supplying enough context is what makes all the difference when interacting with these kind of solutions.

Re: AI makes tech debt more expensive

#32

Post by hyccupi »

RangerScience wrote: post #16
perrygeo wrote: post #6

> Companies with relatively young, high-quality codebases benefit the most from generative AI tools, while companies with gnarly, legacy codebases will struggle to adopt them. In other words, the penalty for having a ‘high-debt’ codebase is now larger than ever. This mirrors my experience using LLMs on personal projects. They can provide good advice only to the extent that your project stays within the bounds of well…

Eh, it’s been kinda nice to just hit tab-to-complete on things like formulaic (but comprehensive) test suites, etc. I never wanted the LLM to take over the (fun) part - thinking through the hard/unusual parts of the problem - but you’re also not wrong that they’re needed the least for the boilerplate. It’s still nice :)

> It’s still nice :)

This is the thing about the kind of free advertising so many on this site provide for these llm corpos.

I’ve seen so many comparisons between “ai” and “stack overflow” that mirror this sentiment of “it’s still nice :)”.

Who’s laying off and replacing thousands of working staff for “still nice :)” or because of “stack overflow”?

Who’s hiring former alphabet agency heads to their board for “still nice :)”?

Who’s forcing these services into everything for “still nice :)”?

Who’s raising billions for “still nice :)”?

So while developers argue tooth and nail for these tools that they seemingly think everyone only sees through their personal lens of a “still nice :)” developer tool, the companies are leveraging that effort to oversell their product beyond the scope of “still nice :)”.

Re: AI makes tech debt more expensive

#33

Post by bunderbunder »

dkdbejwi383 wrote: post #8

> However, in ‘high-debt’ environments with subtle control flow, long-range dependencies, and unexpected patterns, they struggle to generate a useful response I'd argue that a lot of this is not "tech debt" but just signs of maturity in a codebase. Real world business requirements don't often map cleanly onto any given pattern. Over time codebases develop these "scars", little patches of weirdness. It's often temptin…

I recently watched a team speedrun this phenomenon in rather dramatic fashion. They released a ground-up rewrite of an existing service to much fanfare, talking about how much simpler it was than the old version. Only to spend the next year systematically restoring most of those pieces of complexity as whoever was on pager duty that week got to experience a high-pressure object lesson in why some design quirk of the original existed in the first place.

Fast forward to now and we're basically back to where we started. Only now they're working on code that was written in a different language, which I suppose is (to misappropriate a Royce quote) "worth something, but not much."

That said, this is also a great example of why I get so irritated with colleagues who believe it's possible for code to be "self-documenting" on anything larger than a micro-scale. That's what the original code tried to do, and it meant that its current maintainers were left without any frickin' clue why all those epicycles were in there. Sure, documentation can go stale, but even a slightly inaccurate accounting for the reason would have, at the very least, served as a clear reminder that a reason did indeed exist. Without that, there wasn't much to prevent them from falling into the perennially popular assumption that one's esteemed predecessors were idiots who had no clue what they were doing.

Re: AI makes tech debt more expensive

#34

Post by endemic »

holoduke wrote: post #26
dcchambers wrote: post #23

LLM code gen tools are really freaking good...at making the exact same react boilerplate app that everyone else has. The moment you need to do something novel or complicated they choke up. This is why I'm not very confident that tools like Vercel's v0 ( https://v0.dev/ ) are useful for more than just playing around. It seems very impressive at first glance - but it's a mile wide and only an inch deep.

If can you can create boilerplate code, logging, documentation, common algorithms by AI it saves you a lot of time which you can use on your specialized stuff. I am convinced that you can make yourself x2 by using an AI. Just use it in the proper way.

I feel like we should get rid of the boilerplate, rather than have an LLM barf it out.

Re: AI makes tech debt more expensive

#35

Post by hyccupi »

dcchambers wrote: post #21
perrygeo wrote: post #6

> Companies with relatively young, high-quality codebases benefit the most from generative AI tools, while companies with gnarly, legacy codebases will struggle to adopt them. In other words, the penalty for having a ‘high-debt’ codebase is now larger than ever. This mirrors my experience using LLMs on personal projects. They can provide good advice only to the extent that your project stays within the bounds of well…

Like most of us it appears LLMs really only want to work on greenfield projects.

Good joke, but the reality is they falter even more on truly greenfield projects.

See: https://news.ycombinator.com/item?id=42134602

Re: AI makes tech debt more expensive

#36

Post by TOGoS »

perrygeo wrote: post #6

> Companies with relatively young, high-quality codebases benefit the most from generative AI tools, while companies with gnarly, legacy codebases will struggle to adopt them. In other words, the penalty for having a ‘high-debt’ codebase is now larger than ever. This mirrors my experience using LLMs on personal projects. They can provide good advice only to the extent that your project stays within the bounds of well…

> They work best where we need them the least.

Just like most of the web frameworks and ORMs I've been forced to use over the years.

Re: AI makes tech debt more expensive

#38

Post by comboy »

perrygeo wrote: post #6

> Companies with relatively young, high-quality codebases benefit the most from generative AI tools, while companies with gnarly, legacy codebases will struggle to adopt them. In other words, the penalty for having a ‘high-debt’ codebase is now larger than ever. This mirrors my experience using LLMs on personal projects. They can provide good advice only to the extent that your project stays within the bounds of well…

Same experience, but I think it's going to change. As models get better, their context window keeps growing while mine stays the same.

To be clear, our context window can be really huge if you are living the project. But not if you are new to it or even getting back to it after a few years.

Re: AI makes tech debt more expensive

#39

Post by graycat »

perrygeo wrote: post #6

> Companies with relatively young, high-quality codebases benefit the most from generative AI tools, while companies with gnarly, legacy codebases will struggle to adopt them. In other words, the penalty for having a ‘high-debt’ codebase is now larger than ever. This mirrors my experience using LLMs on personal projects. They can provide good advice only to the extent that your project stays within the bounds of well…

I suspected some of that, and your explanation looks more general and good.

Or, for a joke, LLMs plagiarize!

Re: AI makes tech debt more expensive

#40

Post by dcchambers »

holoduke wrote: post #26
dcchambers wrote: post #23

LLM code gen tools are really freaking good...at making the exact same react boilerplate app that everyone else has. The moment you need to do something novel or complicated they choke up. This is why I'm not very confident that tools like Vercel's v0 ( https://v0.dev/ ) are useful for more than just playing around. It seems very impressive at first glance - but it's a mile wide and only an inch deep.

If can you can create boilerplate code, logging, documentation, common algorithms by AI it saves you a lot of time which you can use on your specialized stuff. I am convinced that you can make yourself x2 by using an AI. Just use it in the proper way.

I guess that's a good way to think of it. Despite not being very useful (currently, anyway) for certain types of complicated or novel work - they still are very useful for other types of work and can help reduce development toil.
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