[moron4hire]

This feels like a parallel to the Gell-Mann amnesia effect.

Recently, my company has been investigating AI tools for coding. I know this sounds very late to the game, but we're a DoD consultancy and one not traditional associated with software development. So, for most of the people in the company, they are very impressed with the AI's output.

I, on the other hand, am a fairly recent addition to the company. I was specifically hired to be a "wildcard" in their usual operations. Which is too say, maybe 10 of us in a company of 3000 know what we're doing regarding software (but that's being generous because I don't really have visibility into half of the company). So, that means 99.7% of the company doesn't have the experience necessary to tell what good software development looks like.

The stuff the people using the AI are putting out is... better than what the MilOps analysts pressed into writing Python-scripts-with-delusions-of-grandeur were doing before, but by no means what I'd call quality software. I have pretty deep experience in both back end and front end. It's a step above "code written by smart people completely inexperienced in writing software that has to be maintained over a lifetime", but many steps below, "software that can successfully be maintained over a lifetime".

[IX-103]

Well, that's what you'd expect from an LLM. They're not designed to give you the best solution. They're designed to give you the most likely solution. Which means that the results would be expected to be average, as "above average" solutions are unlikely by definition.

You can tweak the prompt a bit to skew the probability distribution with careful prompting (LLMs that are told to claim to be math PHDs are better at math problems, for instance), but in the end all of those weights in the model are spent to encode the most probable outputs.

So, it will be interesting to see how this plays out. If the average person using AI is able to produce above average code, then we could end up in a virtuous cycle where AI continuously improves with human help. On the other hand, if this just allows more low quality code to be written then the opposite happens and AI becomes more and more useless.

[leptons]

I have no doubt which way it is going to go.

[jack_h]

Before the industrial revolution a cabinetmaker would spend a significant amount of time advancing from apprentice to journeyman to master using only hand tools. Now master cabinetmakers that only use hand tools are exceedingly rare, most furniture is made with power tools and a related but largely different skillset.

When it comes to software the entire reason maintainability is a goal is because writing and improving software is incredibly time consuming and requires a lot of skill. It requires so much skill and time that during my decades in industry I rarely found code I would consider quality. Furthermore the output from AI tools currently may have various drawbacks, but this technology is going to keep improving year over year for the foreseeable future.

[dchftcs]

Maintainable software is also more maintainable by AI. The required standards may be a bit different, for example there may be less emphasis on white space styling, but, for example, complexity in the form of subtle connections between different parts of a system is a burden for both humans and AI. AI isn't magic, it still has to reason, it fails on complexity beyond its ability to reason, and maintainable code is one that is easier to reason with.