Technology

I have a coworker who is essentially building a custom program in Sheets using AppScript, and has been using CGPT/Gemini the whole way.

While this person has a basic grasp of the fundamentals, there's a lot of missing information that gets filled in by the bots. Ultimately after enough fiddling, it will spit out usable code that works how it's supposed to, but honestly it ends up taking significantly longer to guide the bot into making just the right solution for a given problem. Not to mention the code is just a mess - even though it works there's no real consistency since it's built across prompts.

I'm confident that in this case and likely in plenty of other cases like it, the amount of time it takes to learn how to ask the bot the right questions in totality would be better spent just reading the documentation for whatever language is being used. At that point it might be worth it to spit out simple code that can be easily debugged.

Ultimately, it just feels like you're offloading complexity from one layer to the next, and in so doing quickly acquiring tech debt.

https://www.techrepublic.com/article/ai-generated-code-outages/

I use it as a time-saving device. The hardest part is spotting when it's not actually saving you time, but costing you time in back-and-forth over some little bug. I'm often better off fixing it myself when it gets stuck.

I find it's just like having another developer to bounce ideas off. I don't want it to produce 10k lines of code at a time, I want it to be digestible so I can tell if it's correct.

but chose bash because it made the most sense, that bash is shipped with most linux distros out of the box and one does not have to install another interpreter/compiler for another language.

Last time I checked (because I was writing Bash scripts based on the same assumption), Python was actually present on more Linux systems out of the box than Bash.

Because despite how easy it is to dupe people into thinking your methods are altruistic- AI exists to save money by eradicating jobs.

AI is the enemy. No matter how you frame it.

I have worked with somewhat large codebases before using LLMs. You can ask the LLM to point a specific problem and give it the context. I honestly don't see myself as capable without a LLM. And it is a good teacher. I learn much from using LLMs. No free advertisement for any of the suppliers here, but they are just useful.

You get access to information you can't find on any place of the Web. There is a large structural bad reaction to it, but it is useful.

(Edit) Also, I would like to add that people who said that questions won't be asked anymore seemingly never tried getting answers online in a discussion forum - people are viciously ill-tempered when answering.

With a LLM, you can just bother it endlessly and learn more about the world while you do it.

People are not "mad" or "hate" about AI, more like "concerned."

[NB: I'm no programmer. I can write some few lines of bash because Linux, I'm just relaying what I've read. I do use those bots but for something else - translation aid.]

The reasons that I've seen programmers complaining about LLM chatbots are:

1. concerns that AI will make human programmers obsolete
2. concerns that AI will reduce the market for human programmers
3. concerns about the copyright of the AI output
4. concerns about code quality (e.g. it assumes libraries and functions out of thin air)
5. concerns about the environmental impact of AI

In my opinion the first one is babble, the third one is complicated, but the other three are sensible.

I don't think that the current approaches being used by generative AIs are sufficient to reliably produce correct code; I think that they're more-amenable to human-consumable output (and even there, I'm much more enthusiastic about their use for images than text, as things stand). A human needs approximately-correct material to cue their brain; CPUs are more particular.

We'll probably get there, in the same sense that we can ultimately produce human-level AI for anything, but I think that it'll entail higher-level reasoning about a problem, which present generative text approaches don't do.

I did start with internet search....I could not find how to pass values into the function and return from a function easily,

So, now, this I have a hard time with.

When I search for "pass value function bash", this is the first page I get, which clearly shows an example:

https://stackoverflow.com/questions/6212219/passing-parameters-to-a-bash-function

This isn't where I'd consider generative AI to be a useful example; it's something that there will be existing material already readily-available via a search.

The other issue with using generative AI for coding is that for taking pre-existing code for common tasks and using it in multiple programs, we already have an approach: use libraries. That way code gets maintained and such, but doesn't need to be reimplemented by humans over-and-over.

Say someone says "I need linked-list code". Okay, I mean, that's a pretty common, plain Jane thing to need.

But if you use a library, and there's a bug in that code, and it gets fixed, then the bugfix propagates when you update to a newer library. If you generate a linked-list implementation, even if you wind up with working linked-list code at the end, then that isn't gonna happen.