> those who love delivering value/solutions.

This is such marketing speak. The words mean nothing, they’re just a vague amalgamation of feelings. “Vibes”, if you will.

If you “love delivering value and solutions”, go donate and volunteer at a food bank, there’s no need for code at any point.

> The happy consumer and the polished product

More marketing speak. If you are using LLMs to write your code, by definition your product isn’t “polished”. Polishing means pouring over every detail with care to ensure perfection. Letting an LLM spit out code you just accept is not it.

The word you’re looking for is “shiny”, meaning that it looks good at a glance but may or may not be worth anything.

Agree with those 2 camps. The latter camp is all cheered up which is nice, but they should be asking the question if their solution is valuable enough to be maintained. If so, you should make all generated code your code, exactly in the form it needs to be according to your deep expertise. If not, congratulations, you have invented throw-away code. Code of conduct: don't throw this code at people from the former camp.

Or to phrase it more succinctly: if you are in camp 2 but don't have the passion of camp 1, you are a threat for the long term. The reverse is dangerous too, but can be offset to a certain extent with good product management.

You’re forcing a binary choice here.

I think for a lot of minor things, having AI generate stuff is okay, but it’s rather astounding how verbose and sometimes bizarre the code is. It mostly works, but it can be hard to read. What I’m reading from a lot of people is that they’re enjoying coding again because they don’t have to deal with the stuff they don’t want to do, which...I mean, that’s just it isn’t it? Everyone wants to work on what they enjoy, but that’s not how most things work.

Another problem is that if you just let the AI do a lot of the foundational stuff and only focus on the stuff that you’re interested in, you sometimes just miss giant pieces of important context. I’ve tried reading AI driven code, sometimes it makes sense, sometimes it’s just unextensible nonsense that superficially works.

This isn’t tech that should replace anything and needs to be monitored judiciously. It can have value, but what I suspect is going to happen is we are going to have a field day with people fixing and dealing with ridiculous security holes for the next decade after this irrational exuberance goes away. It should be used in the same way that any other ML technique should be. Judiciously and in a specific use case.

Said another way, if these models are the future of general programming, where are the apps already? We’re years into this and where are they? We have no actual case studies, just a bunch of marketing copy and personal anecdotes. I went hunting for some business case studies a while ago and I found a Deloitte “case study” which was just pages of “AI may help” without any actual concrete cases. Where are the actual academic studies showing that this works?

People claiming AI makes them code faster reminds me that Apple years ago demonstrated in multiple human interaction studies that the mouse is faster, but test subjects all thought keyboard shortcuts were faster [1]. Sometimes objective data doesn’t matter, but it’s amusing that the whole pitch for agentic AI is that it is faster and evidence is murky for this at best.

[1] https://www.asktog.com/TOI/toi06KeyboardVMouse1.html

This false dichotomy comes up from time to time, that you either like dicking around with code in your basement or you like being a big boy with your business pants on delivering the world's 8000th online PDF tools site. It's tired. Please let it die.

If you really want to deliver polished products, you still have to manually review the code. When I tried actually "vibecoding" something, I got exhausted so fast by trying to keep up with the metric tons of code output by the AI. I think most developers agree that reviewing other people's code is more exhausting mentally than writing your own. So I doubt those who see coding as too mentally straining will take the time to fully review AI written code.

More likely that step is just skipped and replaced with thoughts and prayers.

polished product, and LLM generated code should not be put in the same conversation.

I just work here, man. What's all this 'love' stuff? :) I propose a third camp: skilled employee seeking compensation.

edit: to stay on the larger topic, I haven't been swayed much one way or the other. ~90% of the code I need existed a decade ago in the form of reusable modules. Anything new is closer to pseudo-code, an amplifier or sandbox isn't something I'm that interested in.

They're not that binary.

I like using my software engineering skills to solve people's problems. I don't do coding for it's own sake - there's always a thing I'm trying to implement for someone.

As a professional, your job is to deliver value and solutions. It used to be that you could do this by writing code. AI changes this calculus because if the machine can write the code instead, the value you deliver by writing it yourself is greatly diminished.

I've also noticed a kind of grouping like this. I've described them as the "Builders" and the "Solvers". Where the former enjoys the construction aspect of the code more, and the latter enjoys the problem/puzzle-solving aspect of code more. I guess it's more of a scale than a binary, since everyone's got a bit of both, but I think I agree that AI is more fun for the builders.