Banning open source would basically destroy the entire Internet in the United States. No tech bro is going to want that.

That’s fair. I guess what I hate is what the term represents, rather than the term itself.

I actively hate the term “vibe coding.” The fact is, while using an LLM for certain tasks is helpful, trying to build out an entire, production-ready application just by prompts is a huge waste of time and is guaranteed to produce garbage code.

At some point, people like your coworker are going to have to look at the code and work on it, and if they don’t know what they’re doing, they’ll fail.

I commend them for giving it a shot, but I also commend them for recognizing it wasn’t working.

Are you using agent mode?

That’s still not actually knowing anything. It’s just temporarily adding more context to its model.

And it’s always very temporary. I have a yarn project I’m working on right now, and I used Copilot in VS Code in agent mode to scaffold it as an experiment. One of the refinements I included in the prompt file to build it is reminders throughout for things it wouldn’t need reminding of if it actually “knew” the repo.

• I had to constantly remind it that it’s a yarn project, otherwise it would inevitably start trying to use NPM as it progressed through the prompt.
• For some reason, when it’s in agent mode and it makes a mistake, it wants to delete files it has fucked up, which always requires human intervention, so I peppered the prompt with reminders not to do that, but to blank the file out and start over in it.
• The frontend of the project uses TailwindCSS. It could not remember not to keep trying to downgrade its configuration to an earlier version instead of using the current one, so I wrote the entire configuration for it by hand and inserted it into the prompt file. If I let it try to build the configuration itself, it would inevitably fuck it up and then say something completely false, like, “The version of TailwindCSS we’re using is still in beta, let me try downgrading to the previous version.”

I’m not saying it wasn’t helpful. It probably cut 20% off the time it would have taken me to scaffold out the app myself, which is significant. But it certainly couldn’t keep track of the context provided by the repo, even though it was creating that context itself.

Working with Copilot is like working with a very talented and fast junior developer whose methamphetamine addiction has been getting the better of it lately, and who has early onset dementia or a brain injury that destroyed their short-term memory.

Like I said, I do find it useful at times. But not only shouldn’t it replace coders, it fundamentally can’t. At least, not without a fundamental rearchitecturing of how they work.

The reason it goes down a “really bad path” is that it’s basically glorified autocomplete. It doesn’t know anything.

On top of that, spoken and written language are very imprecise, and there’s no way for an LLM to derive what you really wanted from context clues such as your tone of voice.

Take the phrase “fruit flies like a banana.” Am I saying that a piece of fruit might fly in a manner akin to how another piece of fruit, a banana, flies if thrown? Or am I saying that the insect called the fruit fly might like to consume a banana?

It’s a humorous line, but my point is serious: We unintentionally speak in ambiguous ways like that all the time. And while we’ve got brains that can interpret unspoken signals to parse intended meaning from a word or phrase, LLMs don’t.

Experienced software developer, here. “AI” is useful to me in some contexts. Specifically when I want to scaffold out a completely new application (so I’m not worried about clobbering existing code) and I don’t want to do it by hand, it saves me time.

And… that’s about it. It sucks at code review, and will break shit in your repo if you let it.

It’s true, although the smart companies aren’t laying off workers in the first place, because they’re treating AI as a tool to enhance their productivity rather than a tool to replace them.

The thing is, if they just pared those claims down a bit, they’d be accurate. Switch from “Copilot can build an entire application for you from scratch while giving you a blowjob” to “Copilot can help developers by automating some repetitive and time-consuming tasks,” and you still have a good thing.

Weird. The cuts apparently include cancellation of several games that were planned and many of them will hit the Xbox division.

I would’ve thought that the increased productivity that Copilot theoretically gives developers would have resulted in the reduced staff still being able to finish those games.

Autocomplete on steroids, but suffering dementia.

Yep. My TV has not and never will be on the Internet in any way. I picked it for its screen quality, and the fact that it also has “smart” components never even entered into the decision. Because those smart components will literally never do anything.

Seems like it’s cheaper and more efficient just to pay people to fuck on camera.

Oh my God… The best/worst thing about the idea of AI porn is how AI tends to forget anything that isn’t still on the screen. So now I’m imagining the camera zooming in on someone’s jibblies, then zooming out and now it’s someone else’s jibblies, and the background is completely different.

The trick to using an AI agent effectively is already knowing exactly what you want, typing the request out in excruciating detail, and being a good developer who properly reviews code so you catch all the errors and repetition the AI agent will absolutely include.

So… Yeah. 100% agree. AI agents are useful, but impossible to use if you aren’t already skilled with code.

Well, technically, yes. You’re right. But they’re a specific, narrow type of neural network, while I was thinking of the broader class and more traditional applications, like data analysis. I should have been more specific.

That’s only part of the problem. Yes, JavaScript is a fragmented clusterfuck. Typescript is leagues better, but by no means perfect. Still, that doesn’t explain why the LLM can’t recall that I’m using Yarn while it’s processing the instruction that specifically told it to use Yarn. Or why it tries to start editing code when I tell it not to. Those are still issues that aren’t specific to the language.

But it still manages to fuck it up.

I’ve been experimenting with using Claude’s Sonnet model in Copilot in agent mode for my job, and one of the things that’s become abundantly clear is that it has certain types of behavior that are heavily represented in the model, so it assumes you want that behavior even if you explicitly tell it you don’t.

Say you’re working in a yarn workspaces project, and you instruct Copilot to build and test a new dashboard using an instruction file. You’ll need to include explicit and repeated reminders all throughout the file to use yarn, not NPM, because even though yarn is very popular today, there are so many older examples of using NPM in its model that it’s just going to assume that’s what you actually want - thereby fucking up your codebase.

I’ve also had lots of cases where I tell it I don’t want it to edit any code, just to analyze and explain something that’s there and how to update it… and then I have to stop it from editing code anyway, because halfway through it forgot that I didn’t want edits, just explanations.

I can envision a system where an LLM becomes one part of a reasoning AI, acting as a kind of fuzzy “dataset” that a proper neural network incorporates and reasons with, and the LLM could be kept real-time updated (sort of) with MCP servers that incorporate anything new it learns.

But I don’t think we’re anywhere near there yet.

I would argue that without consistent and enforced type hinting, dynamically typed languages offer very little benefit from type-checking at runtime. And with consistent, enforced type hinting, they might as well be considered actual statically typed languages.

Don’t get me wrong, that’s a good thing. Properly configured Python development environments basically give you both, even if I’m not a fan of the syntax.