I am jack's complete lack of surprise.

I have never seen an AI generated code which is correct. Not once. I've certainly seen it broadly correct and used it for the gist of something. But normally it fucks something up - imports, dependencies, logic, API calls, or a combination of all them.

I sure as hell wouldn't trust to use it without reviewing it thoroughly. And anyone stupid enough to use it blindly through "vibe" programming deserves everything they get. And most likely that will be a massive bill and code which is horribly broken in some serious and subtle way.

But will something be done about it?

NOooOoOoOoOoo. As long as it is still the new shiny toy for techbros and executive-bros to tinker with, it'll continue.

The biggest value I get from AI in this space is when I get handed a pile of spagehtti and ask for an initial overview.

For most large projects, writing the code is the easy part anyway.

So when the AI bubble burst, will there be coding jobs available to clean up the mess?

AI companies and investors are absolutely overhyping its capabilities, but if you haven't tried it before I'd strongly recommend doing so. For simple bash scripts and Python it almost always gets something workable first try, genuinely saving time.

AI LLMs are pretty terrible for nearly every other task I've tried. I suspect it's because the same amount of quality training data just doesn't exist for other fields.

I'm not a programmer in any sense. Recently, I made a project where I used python and raspberry pi and had to train some small models on a KITTI data set. I used AI to write the broad structure of the code, but in the end, it took me a lot of time going through python documentation as well as the documentation of the specific tools/modules I used to actually get the code working. Would an experienced programmer get the same work done in an afternoon? Probably. But the code AI output still had a lot of flaws. Someone who knows more than me would probably input better prompts and better follow up requirements and probably get a better structure from the AI, but I doubt they'll get a complete code. In the end, even to use AI, you have to know what you're doing to use AI efficiently and you still have to polish the code into something that actually works.

No shit sherlock!

According to Deutsche Bank the AI bubble is ~~a~~ the pillar of our economy now.

So when it pops. I guess that's kinda apocalyptic.

Edit - strikethrough

Oh wow. No shit. Anyway!

About that "net slowdown". I think it's true, but only in specific cases. If the user already knows well how to write code, an LLM might be only marginally useful or even useless.

However, there are ways to make it useful, but it requires specific circumstances. For example, you can't be bothered to write a simple loop, you can use and LLM to do it. Give the boring routine to an LLM, and you can focus on naming the variables in a fitting way or adjusting the finer details to your liking.

Can't be bothered to look up the exact syntax for a function you use only twice a year? Let and LLM handle that, and tweak the details. Now, you didn't spend 15 minutes reading stack overflow posts that don't answer the exact question you had in mind. Instead, you spent 5 minutes on the whole thing, and that includes the tweaking and troubleshooting parts.

If you have zero programming experience, you can use an LLM to write some code for you, but prepare to spend the whole day troubleshooting something that is essentially a black box to you. Alternatively, you could ask a human to write the same thing in 5-15 minutes depending on the method they choose.

so is the profit it was foretold to generate, but it actually costs money than its actually generating.

The people talking about AI coding the most at my job are architects and it drives me insane.

Wait, it was hyped? Not just ridiculed?

The good news is: AI is a lot less impressive than it seemed at first.

The bad news is: so are a lot of jobs.

LLMs/"Vibe Coding" is probably a little bit more useful than the average intern with some tasks bumping up to an early career hire (what would historically be a Junior Engineer before title inflation/stagnation).

As in: it can generate code that might do what you want. But you need (actual) senior engineers to review the code thoroughly. And... how do people get the experience they need to do that?

Which basically results in turning everyone into a manager. Except your reports aren't humans and you don't get more pay. Instead your reports are vscode plugins. Which... sounds like absolute hell but I can get why the (wannabe) management class loves that.

https://www.youtube.com/watch?v=VsE0BwQ3l8U&t=1492s

And the band plays on

I can't even get Copilot to write Vitest files for React without making a mountain of junk code that describes drivel.