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AI doesn't generate working products, that's still your job

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Re: AI doesn't generate working products, that's still your job

#151

Post by bakugo »

smolder wrote: post #100
budsniffer952 wrote: post #28

Earlier quoted context omitted.

Popped over to HackerNews, read two comment sections and the top comments in both articles were users saying the same thing: "AI can't write code! The whole thing will come crumbling down any minute! Just you wait!" I've never seen this community like this. Are these people cooked? We are years into this and they haven't been able to figure it out? They are going to continue to tell people using these tools successfu…

> Are these people cooked? Yes. This is a weird kind of denial about the LLMs that cost nation-state levels of energy doing human nerd work. They aren't perfect at all, but there's very little reason to be anything but a prompt engineer and proof reader anymore.

Prompt engineering? Proof reading? That's so last month, who even does that anymore? What a nerd.

All this condescending drivel about how "anyone who still writes code by hand is a loser, but not me, I'm a prompt engineer because I'm smart and forward-thinking" is so painfully tone-deaf, as if this "prompt engineering" has any lasting value and isn't just a momentary stepping stone towards a techno-feudalist future where every tech company consists of a small group of very wealthy executives, typing what they want in plain words into a text box and having the AI do everything for them, with no need for anyone below them.

Re: AI doesn't generate working products, that's still your job

#152

Post by baq »

ThePhysicist wrote: post #46

I'm about to throw away multiple months of LLM generated code for one of my side projects. I was really careful writing design specs and it wasn't even a new code base the LLM worked on, but still after several months of AI changes I feel my code degraded more and more into a subtle mess. Hard to explain, each individual change looked good and logical and on the surface the codebase looks fine, but looking at the who…

It’s a garbage collection problem. They’re good at adding stuff. They’re bad at removing stuff. You have to go out of your way to have them remove stuff; rubrics, byte for byte identical outputs, bug for bug compatibility etc and then convince the cursed things that it’s still safe to rip and replace. Bonus points when you get them to stop before the ‘replace’ and everything still works.

Re: AI doesn't generate working products, that's still your job

#153

Post by hoppp »

I agree that the people who vibe code driven by the fear of being left behind are in a sort of self fulfilling loop.

The more code is generated without understanding, the less likely it will be maintained and it will be left behind the audited code in quality and in usefulness.

It's so easy to get into AI that the only thing we can be left behind is personal experience or learning. But jumping in and spending on claude to vibe up a SaaS...pretty much anyone can do that now.

Re: AI doesn't generate working products, that's still your job

#154

Post by f2hex »

Anyone who thinks this way has completely lost sight of what it means to use generative AI for software projects, namely, the concept of a tool, however sophisticated it may be, but still just a tool. The goal of a project can be anything from a prototype to a finished product, and using AI tools does not change what you want to achieve as the final result.

Re: AI doesn't generate working products, that's still your job

#155

Post by thewhitetulip »

ThePhysicist wrote: post #46

I'm about to throw away multiple months of LLM generated code for one of my side projects. I was really careful writing design specs and it wasn't even a new code base the LLM worked on, but still after several months of AI changes I feel my code degraded more and more into a subtle mess. Hard to explain, each individual change looked good and logical and on the surface the codebase looks fine, but looking at the who…

I had a funny yet tragic experience about LLM last week

A CICD flow had broken. It was not giving the URL of a deployed service.

A team member used AI to fix it without reading the code and AI added 55 lines of code

When I noticed the issue, I modified the code by removing 5 extra lines and used the right command to get the url

Earlier I was doing a grep and matching the output against .com to get the url Recently I noticed that the utility provided a --format json option that was much cleaner!

Re: AI doesn't generate working products, that's still your job

#156

Post by mexicocitinluez »

jaccola wrote: post #24

The test is simple: have we seen great new products or improvements in the products we use over the past 12,24,36 months? The only great new product I’ve used is my LLM of choice, and those labs seem to be hiring more humans than ever. Maybe it’s true that Claude only just got good enough and that 12 months from now our day to day lives will be way better thanks to LLM-driven product improvements/breakthroughs. My be…

> have we seen great new products or improvements in the products we use over the past 12,24,36 months

This sentiment drives me nuts.

I'm on a handful of software dev subreddits and the amount of new products popping up has tripled since these tools became available.

I also don't understand how you'd expect to measure this. Is there some single list of all software that's been released that annotates whether AI was used? Do you have some feed of every project that hits GitHub that you're meticulously tracking? The idea that you personally should have seen these improvements or they didn't happen is wild to me.

I work in healthcare. Where the # of products has skyrocketed due to these tools. Some are bad, some are good. But to say that nothing has come out of it is just objectively not true.

Re: AI doesn't generate working products, that's still your job

#157

Post by sajithdilshan »

rideontime wrote: post #146
sajithdilshan wrote: post #144

I have two different experiences with LLMs. First one is that I have vibe coded two different projects for work, one is a slack plugin which basically pushes alerts to a channel based on a people roaster and another one is a gmeet plugin to add a talking timer for each participant in the meeting. I used Opuse 4.6 and both were written with a node backend and I actually don't have a good understanding on how it works,…

This mirrors my experience. Vibe-coding one-off, low-risk apps, it's been fantastic. Trying to take the same approach when implementing features in massive legacy codebases has been an utter nightmare.

Exactly, and in most companies engineers have to implement feature in an existing codebase and hardly get to work on a completely greenfield projects. In my experience most of the time LLM take a quick dirty shortcuts to implement thing in a legacy codebase. It work, but not efficient and would collapse under heavy load, especially DB query implementations

Re: AI doesn't generate working products, that's still your job

#158

Post by whstl »

havkom wrote: post #129
microtonal wrote: post #106

Earlier quoted context omitted.

I am more and more just using LLM assistance over fully agentic programming. Even when writing detailed instructions, guardrails, and whatnot, a lot of modern models (e.g. Opus) are optimized to work autonomously. But over time they just make a mess out of code bases, often because they don't truly understand good design, but will just make changes until they reaches their objective, leaving a mess for a human to cle…

They are great instruction followers in general. This is, one single bad instruction during months of work can mess things up.

I would say they're great until they aren't. Which means at some point in a session or in a long-lived-project they will resist very hard being steered like it would be done by another developer, product manager, a designer, or just the market in general.

Most people don't find this to happen because the size of projects and the granularity of the expectations are wildly different.

Re: AI doesn't generate working products, that's still your job

#159

Post by sicher »

I am very product focused with my projects. I have Claude write 100% of the code but I challenge its suggestions and make damn sure there are ways for it to verify functionality and correctness. I don't read much of the generated code but am adamant that there are tests: unit, integration and (if possible) against other implementations. And I care a LOT about performance.

So far (last 6-7 months) I've built tons of stuff in my spare time: A pdf generator lib, a scheme implementation (R5RS and R7RS) with AOT compilation, a screenplay editor, a code editor, a ripgrep-like lib/engine/cli tool for fast search in a workspace, a markdown parser, a Fountain (screenplay) parser, a lib for dealing with updating apps, tooling for finding duplicate code and generating codemaps - and much more.

It's been an absolute ride.

Re: AI doesn't generate working products, that's still your job

#160

Post by baq »

adamddev1 wrote: post #145
schnebbau wrote: post #113

Earlier quoted context omitted.

This has happened to my side project too. There's so much going on in the code now that I can't possibly grok it to make changes safely by myself any more. But I think that's OK. Because I don't have to grok it anymore. I've been crafting beautiful code for almost 20 years - that itch is scratched. Now I just want to be productive and build cool stuff. AI is helping me make a better end-product in a fraction of the t…

> In the same way high-level languages are a layer on top of writing machine code manually. Another layer, yes, but NOT "in the same way." It is a new, different kind of layer. The other layers were deterministic, not probabilistic.

Probabilistic algorithms are not new. If the distribution is known you can bend surprisingly many things to your will in the long run - and the most interesting part is the long run can be unexpectedly short.

LLMs are quite interesting in that regard because you have a lot of levers to influence the shape of the distribution; the ways are different for each model, so it’s a very experimental science, but applying the scientific method is exactly how you get good results.

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