[steveBK123]

The other hard to measure part is that I see/hear a lot of LLM usage going towards dev work that was never prioritized before.

Suddenly devs who were cranking out features with no interest in infrastructure are attacking giant refactors to make the code more understandable to the LLM.

Other devs are using LLMs to build themselves quality of life SDLC tools completely separate from the core code base.

Plenty of other examples of this.

[leoedin]

The quality of my bash scripts is 100x what they used to be. Proper help messages, flag parsing, functions, internal variables, using sed all the time (I could never wrap my head around that).

Of course, the main issue is that they’re completely undebbugable now. My bash scripts used to be a sequential list of commands, now they’re 500 lines of variable laden functions.

Is my life any better? Dunno. But it’s satisfying (until there’s a bug)

[nasretdinov]

> the main issue is that they’re completely undebbugable now

Well, that means the quality actually dropped then :). Looking impressive isn't equal to quality, understandability and reliability is

[xboxnolifes]

100x UX quality, not DX quality.

[gmassman]

Not necessarily…. As with all engineering choices there are tradeoffs involved. There can be both advantages and disadvantages to using AI to build scripts. And more likely than not you’ll need AI to help debug the scripts when they have issues. Real tradeoffs to consider.

[mckee_plus_plus]

I switched to js for dev related scripting after seeing how much python scripting is used for portable c++ projects like chromium.

A node glob() or a regexp string.replace call is probably easier to read than spaghetti shell.

And your llm might do a much better job of creating clean, readable and testable code.

[metalspot]

llms are 100X for me, but only 10X goes into actual shipping code. the rest is all on doing the dev process the way it actually should be done: incremental POCs, refining specifications, modularization, exhaustive test suites with 95%+ logical unit test coverage, fuzzing unit test coverage, exhaustive e2e testing, with a fuzzer harness over e2e tests for long term simulation and scale testing, bechmark gated self improvement loops for performance optimization, etc. i guarantee you i can ship higher quality 100% llm generated code than any human.

[t-writescode]

It scares me how much of this is true - people truly weren't doing all of this before; but like ... some of us (like myself) were, and we were trying to push other people to write good code like that - code that helped everyone else's future velocity be faster - including our own on the next MR and the next one after that.

I'm glad you're doing all those right things; but, really, some of us were already doing most of, if not all of that. And some of us (like myself) were doing it very quickly, too, since we'd been doing it that way over a decade and constantly getting faster.

[move-on-by]

Just one more data point but this is what I’m seeing too. The extreme ‘ruthless’ prioritization has stopped and devs (who want it) have breathing room to make the enhancements they’ve been wanting all along. Turns out what is good for AI is also good for regular old school SDLC. All you have to do is say it will make AI more effective.

[senderista]

You missed documentation. There was never time for that until now.

[sensanaty]

IME LLM docs are worse than useless the majority of the time. It's like most LLM writing, an inscrutable wall of text that simultaneously says nothing and too much at the same time.

[senderista]

I agree, but there's been a push at my company for humans to write docs to help the LLMs.