Maybe I didn't make it clear, but I didn't build the software in my comment. A clanker did.

Vibe-coding is a claude code <-> QA loop on the end result that anyone can do (the non-experts in his claim).

An example of a cycle looks like "now add an Options tab that let's me customize the global hotkey" where I'm only an end-user.

Once again, where do my 20 years of software experience come up in a process where I don't even read code?

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thewebguyd 2 days ago | parent | next [-]

> An example of a cycle looks like "now add an Options tab that let's me customize the global hotkey" where I'm only an end-user

Which is a prompt that someone with experience would write. Your average, non-technical person isn't going to prompt something like that, they are going to say "make it so I can change the settings" or something else super vague and struggle. We all know how difficult it is to define software requirements.

Just because an LLM wrote the actual code doesn't mean your prompts weren't more effective because of your experience and expertise in building software.

Sit someone down in front of an LLM with zero development or UI experience at all and they will get very different results. Chances are they won't even specify "macOS menu bar app" in the prompt and the LLM will end up trying to make them a webapp.

Your vibe coding experience just proves my initial point, that these tools are useful for those who already have experience and can lean on that to craft effective prompts. Someone non-technical isn't going to make effective use of an LLM to make software.

	▲	hombre_fatal 2 days ago \| parent \| next [-]
		Counter point: https://news.ycombinator.com/item?id=46234943 Your original claim: > The hype is all about "this tech will enable non-experts to do things they couldn't do before" Are you saying that a prompt like "make a macOS weather app for me" and "make an options menu that lets me set my location" are only something an expert can do? I need to know what you think their expertise is in.
	▲	ModernMech 2 days ago \| parent \| prev [-]
		Here's how I look at it as a roboticist: The LLM prompt space is an ND space where you can start at any point, and then the LLM carves a path through the space for so many tokens using the instructions you provided, until it stops and asks for another direction. This frames LLM prompt coding as a sort of navigation task. The problem is difficult because at every decision point, there's an infinite number of things you could say that could lead to better or worse results in the future. Think of a robot going down the sidewalk. It controls itself autonomously, but it stops at every intersection and asks "where to next boss?" You can tell it either to cross the street, or drive directly into traffic, or do any number of other things that could cause it to get closer to its destination, further away, or even to obliterate itself. In the concrete world, it's easy to direct this robot, and to direct it such that it avoids bad outcomes, and to see that it's achieving good outcomes -- it's physically getting closer to the destination. But when prompting in an abstract sense, its hard to see where the robot is going unless you're an expert in that abstract field. As an expert, you know the right way to go is across the street. As a novice, you might tell the LLM to just drive into traffic, and it will happily oblige. The other problem is feedback. When you direct the physical robot to drive into traffic, you witness its demise, its fate is catastrophic, and if you didn't realize it before, you'd see the danger then. The robot also becomes incapacitated, and it can't report falsely about its continued progress. But in the abstract case, the LLM isn't obliterated, it continues to report on progress that isn't real, and as a non expert, you can't tell its been flattened into a pancake. The whole output chain is now completely and thoroughly off the rails, but you can't see the smoldering ruins of your navigation instructions because it's told you "Exactly, you're absolutely right!"

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onethought 2 days ago | parent | prev [-]

But anyone didn't do it... you an expert in software development did it.

I would hazard a guess that your knowledge lead to better prompts, better approach... heck even understanding how to build a status bar menu on Mac OS is slightly expert knowledge.

You are illustrating the GP's point, not negating it.

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hombre_fatal 2 days ago | parent [-]

> I would hazard a guess that your knowledge lead to better prompts, better approach... heck even understanding how to build a status bar menu on Mac OS is slightly expert knowledge.

You're imagining that I'm giving Claude technical advice, but that is the point I'm trying to make: I am not.

This is what "vibe-coding" tries to specify.

I am only giving Claude UX feedback from using the app it makes. "Add a dropdown that lets me change the girth".

Now, I do have a natural taste for UX as a software user, and through that I can drive Claude to make a pretty good app. But my software engineering skills are not utilized... except for that one time I told Claude to use an AGDT because I fancy them.

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ModernMech 2 days ago | parent [-]

My mother wouldn't be able to do what you did. She wouldn't even know where to start despite using LLMs all the time. Half of my CS students wouldn't know where to start either. None of my freshman would. My grad students can do this but not all of them.

Your 20 years is assisting you in ways you don't know; you're so experienced you don't know what it means to be inexperienced anymore. Now, it's true you probably don't need 20 years to do what you did, but you need some experience. Its not that the task you posed to the LLM is trivial for everyone due to the LLM, its that its trivial for you because you have 20 years experience. For people with experience, the LLM makes moderate tasks trivial, hard tasks moderate, and impossible tasks technically doable.

For example, my MS students can vibe code a UI, but they can't vibe code a complete bytecode compiler. They can use AI to assist them, but it's not a trivial task at all, they will have to spend a lot of time on it, and if they don't have the background knowledge they will end up mired.

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hombre_fatal 2 days ago | parent [-]

The person at the top of the thread only made a claim about "non-experts".

Your mom wouldn't vibe-code software that she wants not because she's not a software engineer, but because she doesn't engage with software as a user at the level where she cares to do that.

Consider these two vibe-coded examples of waybar apps in r/omarchy where the OP admits he has zero software experience:

- Weather app: https://www.reddit.com/r/waybar/comments/1p6rv12/an_update_t...

- Activity monitor app: https://www.reddit.com/r/omarchy/comments/1p3hpfq/another_on...

That is a direct refutation of OP's claim. LLM enabled a non-expert to build something they couldn't before.

Unless you too think there exists a necessary expertise in coming up with these prompts:

- "I want a menubar app that shows me the current weather"

- "Now make it show weather in my current location"

- "Color the temperatures based on hot vs cold"

- "It's broken please find out why"

Is "menubar" too much expertise for you? I just asked claude "what is that bar at the top of my screen with all the icons" and it told me that it's macOS' menubar.

	▲	bopbopbop7 2 days ago \| parent \| next [-]
		Your best examples of non-experts are two Linux power users?
	▲	ModernMech 2 days ago \| parent \| prev [-]
		I didn't make clear I was responding to your question: "Where do my 20 years of software dev experience fit into this except beyond imparting my aesthetic preferences?" Anyway, I think you kind of unintentionally proved my point. These two examples are pretty trivial as far as software goes, and it enabled someone with a little technical experience to implement them where before they couldn't have. They work well because: a) the full implementation for these apps don't even fill up the AI context window. It's easy to keep the LLM on task. b) it's a tutorial style-app that people often write as "babby's first UI widget", so there are thousands of examples of exactly this kind of thing online; therefore the LLM has little trouble summoning the correct code in its entirety. But still, someone with zero technical experience is going to be immediately thwarted by the prompts you provided. Take the first one "I want a menubar app that shows me the current weather". https://chatgpt.com/share/693b20ac-dcec-8001-8ca8-50c612b074... ChatGPT response: "Nice — here's a ready-to-run macOS menubar app you can drop into Xcode..." She's already out of her depth by word 11. You expect your mom to use Xcode? Mine certainly can't. Even I have trouble with Xcode and I use it for work. Almost every single word in that response would need to be explained to her, it might as well be a foreign language. Now, the LLM could help explain it to her, and that's what's great about them. But by the time she knows enough to actually find the original response actionable, she would have gained... knowledge and experience enough to operate it just to the level of writing that particular weather app. Though having done that, it's still unreasonable to now believe she could then use the LLM to write a bytecode compiler, because other people who have a Ph.D. in CS can. The LLM doesn't level the playing field, it's still lopsided toward the Ph.D.s / senior devs with 20 years exp.