“fractional CTO”(no clue what that means, don’t ask me)

For those who were also interested to find out: Consultant and advisor in a part time role, paid to make decisions that would usually fall under the scope of a CTO, but for smaller companies who can't afford a full-time experienced CTO

It looks like a rigid design philosophy that must completely rebuild for any change. If the speed of production becomes fast enough, and the cost low enough, iterating the entire program for every change would become feasible and cost effective.

@AutistoMephisto@lemmy.world @technology@lemmy.world

I used to deal with programming since I was 9 y.o., with my professional career in DevOps starting several years later, in 2013. I dealt with lots of other's code, legacy code, very shitty code (especially done by my "managers" who cosplayed as programmers), and tons of technical debts.

Even though I'm quite of a LLM power-user (because I'm a person devoid of other humans in my daily existence), I never relied on LLMs to "create" my code: rather, what I did a lot was tinkering with different LLMs to "analyze" my own code that I wrote myself, both to experiment with their limits (e.g.: I wrote a lot of cryptic, code-golf one-liners and fed it to the LLMs in order to test their ability to "connect the dots" on whatever was happening behind the cryptic syntax) and to try and use them as a pair of external eyes beyond mine (due to their ability to "connect the dots", and by that I mean their ability, as fancy Markov chains, to relate tokens to other tokens with similar semantic proximity).

I did test them (especially Claude/Sonnet) for their "ability" to output code, not intending to use the code because I'm better off writing my own thing, but you likely know the maxim, one can't criticize what they don't know. And I tried to know them so I could criticize them. To me, the code is.. pretty readable. Definitely awful code, but readable nonetheless.

So, when the person says...

The developers can’t debug code they didn’t write.

...even though they argue they have more than 25 years of experience, it feels to me like they don't.

One thing is saying "developers find it pretty annoying to debug code they didn't write", a statement that I'd totally agree! It's awful to try to debug other's (human or otherwise) code, because you need to try to put yourself on their shoes without knowing how their shoes are... But it's doable, especially by people who deal with programming logic since their childhood.

Saying "developers can't debug code they didn't write", to me, seems like a layperson who doesn't belong to the field of Computer Science, doesn't like programming, and/or only pursued a "software engineer" career purely because of money/capitalistic mindset. Either way, if a developer can't debug other's code, sorry to say, but they're not developers!

Don't take me wrong: I'm not intending to be prideful or pretending to be awesome, this is beyond my person, I'm nothing, I'm no one. I abandoned my career, because I hate the way the technology is growing more and more enshittified. Working as a programmer for capitalistic purposes ended up depleting the joy I used to have back when I coded in a daily basis. I'm not on the "job market" anymore, so what I'm saying is based on more than 10 years of former professional experience. And my experience says: a developer that can't put themselves into at least trying to understand the worst code out there can't call themselves a developer, full stop.

I work in an company who is all-in on selling AI and we are trying desperately to use this AI ourselves. We've concluded internally that AI can only be trusted with small use cases that are easily validated by humans, or for fast prototyping work.. hack day stuff to validate a possibility but not an actual high quality safe and scalable implementation, or in writing tests of existing code, to increase test coverage. yes, I know thats a bad idea but QA blessed the result.... so um .. cool.

The use case we zeroed in on is writing well schema'd configs in yaml or json. Even then, a good percentage of the time the AI will miss very significant mandatory sections, or add hallucinations that are unrelated to the task at hand. We then can use AI to test AI's work, several times using several AIs. And to a degree, it'll catch a lot of the issues, but not all. So we then code review and lint with code we wrote that AI never touched, and send all the erroring configs to a human. It does work, but cant be used for mission critical applications. And nothing about the AI or the process of using it is free. Its also disturbingly not idempotent. Did it fail? Run it again a few times and it'll pass. We think it still saves money when done at scale, but not as much as we promise external AI consumers. The Senior leadership know its currently overhyped trash and pressure us to use it anyway on expectations it'll improve in the future, so we give the mandatory crisp salute of alignment and we're off.

I will say its great for writing yearly personnel reviews. It adds nonsense and doesnt get the whole review correct, but it writes very flowery stuff so managers dont have to. So we use it for first drafts and then remove a lot of the true BS out of it. If it gets stuff wrong, oh well, human perception is flawed.

This is our shared future. One of the biggest use cases identified for the industry is health care. Because its hard to assign blame on errors when AI gets it wrong, and AI will do whatever the insurance middle men tell it to do.

I think we desperately need a law saying no AI use in health care decisions, before its too late. This half-assed tech is 100% going to kill a lot of sick people.