It helped me finish my webRTC client for a esp32 microcontroller. Thats fairly low level. It did it without breaking a sweat - 2hrs, and we had a model which works with my pipecat-based based server.

I loaded the lowest level piece of software I wrote in the last 15 years - a memory spoofing aimbot poc exploiting architectural issues in x86 (things like memory breakpoints set on logical memory - not hw addresses - allowing to read memory without tripping kernel-level detection tools, ability to trigger PFs on pages where the POC was hiding to escape detection, low level gnarly stuff like this). I asked it to clean up the code base and propose why it would not work under current version of windows. It did that pretty well.

Lower level stuff does of course exist, but not a whole lot IMHO. I would not assume claude will struggle with kernel level stuff at all. If anything, this is better documented than the over-abstraced mainstream stuff.

Vibe coding will eventually come for that.

The cost of hallucinations though - you potentially have a stronger point there. It wouldn’t surprise me if that fails to sway some decision makers but it doesn’t give the average dev a bit more ground to work with.

And this is exactly the problem. Developers are happily passing off their biggest valuable asset to, essentially, their replacements while, at the same time, convincing themselves that them playing the "ideas guy" or "conductor" roles is the real value they bring to the table.

Like, get real!

I feel like I'm rapidly going insane. It wasn't that long ago when many people in this forum would boldly exclaim that their software development skills were their capital and take pride in their ability to build stuff. It also wasn't that long ago when the "ideas guys" were a meme here.

We're ceding almost all of our bargaining power because programming "was never valuable." And we're doing it with smiles from ear to ear.

I'm thinking back to my contracting days when a typical customer might have a team of ten people but only one or two did the bulk of the work. Now the whole team can be productive for whatever measure you use for productivity.

It's not so great for the one or two but fantastic for everybody else.

Well yeah! This is objectively a great process for getting a lot of work done.

The problems I've been working on are at a much higher level than the nuts and bolts.

I'm currently exploring domain-specific languages aimed at writing web applications. I've been particularly interested in, much like bash, data flowing through pipelines. I have spent quite a bit of time and I'm definitely not vibe coding but I've probably only writen 1-2% of the code in these projects.

It is so much work to build out a new language with a surrounding ecosystem of tooling. Not even five years ago this would have necessarily been a full time multi-year endeavor or at least required a team of researchers. Now I can tinker away in my off hours.

This is what I am exploring:

https://williamcotton.com/articles/the-evolution-of-a-dsl

Did I not craft the syntax and semantics of these languages?

Huh? What about all the open source software you use, did you build all of it?

What about the phone in your hand, did you design that?

HN loves to believe they are the noble few - men and women of math and science, driven by nothing but the pure joy of their craft

But this whole AI thing has been super revealing. Almost everyone here is just the same old same old, only that now that the change is hitting close to home, you’re clutching your pearls and lamenting the days when devs were devs

The younger generation born into the AI world is going to leave you in the dust because they aren’t scared of it

My math teacher used to say that people felt this was about…calculators, imagine that

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.

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

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.

> 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.

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

> ...and those who love delivering value/solutions. I am in the latter camp. The happy consumer and the polished product is what gives me satisfaction...

Can't the customer now just skip you and generate a product for himself via AI?

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.

And yet, there's still room for people who love to code to do great work. Look at bun for instance https://bun.com/. It's a JavaScript runtime that dramatically improves on the performance of node.js to the point where it will likely completely deprecate it in the coming years. It does so many things right out of the box, but it's essentially just an incremental improvement in the development world.

I think AI-augmented development will lead to faster and vastly improved software over the years. This isn't just a space that's being disrupted on the maker/creator side of developing software. And from a makers/creators point of view, you wouldn't even need to keep up with the latest trends like performance, AI should just know which libraries are the best to use to develop your solutions.

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.