AI doesn’t do shit, be honest.
AI doesn't generate working products, that's still your job
101–110 of 317 posts
Re: AI doesn't generate working products, that's still your job
#102Earlier quoted context omitted.
Yeah, it's baffling. I can't relate to these statements at all. What are people doing? Surely the smart people of HN would have been able to figure this out a long time ago. I also don't find these people in real life. Even the most junior developers I know are able to navigate this without creating this supposed mess.
Its a bit unkind to talk like this - the obvious and equally unproductive response is to question if you are really as good as you think you are. Are those junior developers not making a mess, or do you lack the insight to see it?
Big codebases tend to become a mess anyway so if your company has experience dealing with shit, the fact that now shit is AI-generated doesn't substantially change anything.
And I'm not joking. Imagine it this way - managing a group of skilled professionals is a completely different skill from managing a bunch of alcoholics doing a minimum-wage job, and sometimes the latter situation is just the reality you find yourself in.
Re: AI doesn't generate working products, that's still your job
#103I'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…
There’s been infinitely times where I was stuck at some problem and every single solution was complex, messy, over-engineered and somehow wrong, until I went on a walk or moved to a different issue and suddenly it would hit me that I was looking at it all wrong, and there’s a simple solution there but my tunnel vision didn’t let me see it. LLM rob you of that, everything is instant, there’s no time to reflect, there’…
I would say that the mechanism for this is actually due to the nature of working with LLMs: they free your attention.
Say you're working on a project, and it does an ok job like what the GP says. Each step looks fine, but put together it looks off. You give it some instructions, and then you let it work.
But what are you doing in the freed up time? You context switch into another project and give that some instructions.
Now you have two or three or ten projects that superficially look fine, but you yourself have context switched so much you don't have the overview anymore of why exactly each project needs fixing.
Re: AI doesn't generate working products, that's still your job
#104When you have built your working product try this prompt: - Review the codebase is it production ready? I'm selling it for $1million dollars can it meet that standard. Then cry as the ai reveals that it didn't actually do anything close to what it said it did. I call this my million dollar prompt, as in it teaches you just how much you are being fooled.
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…
you have to remember, 70 million people voted for the current US regime and many of them billionaires.
The ability to delude ones self and not pay attention to the "facts on the code" is moumentally built into the human condition.
Everyones experience is some unique snowflake of just how easy their mental gymnastics are.
Re: AI doesn't generate working products, that's still your job
#105Earlier quoted context omitted.
In today's massive applications, the number of people who can see the entire structure is very limited—yet commercial applications still work. And I think GPT Codex and the products from AI companies are, at least for now, working reasonably well. Of course, it depends on your baseline for quality. But here's what I think is the core point: Modern SaaS applications have become significantly more complex compared to o…
We have been building complex software before and we continue to do so. The question is where is this mythical codebase 10 times more complex then the Linux kernel that we were previously unable to produce? Or let it just be complex software. Where is it? What are the names?
I think this is a complex issue.
If there were a need for a new open-source OS to replace Linux, it would be used then. Once infrastructure becomes entrenched, the cost of dismantling or replacing it becomes enormous.
So you might argue:
'If AI is so great, shouldn't it be able to directly modify Linux's millions of lines of code right now?'
My answer is different:
'Why break something that already works? It only makes sense to change it when a problem actually arises.'
The example of Bun, originally written in Zig and later ported to Rust, illustrates this. Zig is a relatively new language, but whether for political reasons or not, Bun was eventually ported to Rust. And after the rewrite, Bun still works just fine.
And rewriting infrastructure from scratch is fundamentally a cost issue.
I can handle up to 60,000 lines of code on my own. With AI, I can handle up to around 200,000 lines. But building new infrastructure from scratch is an entirely different matter.
Why would you replace something that already works with AI? That's a separate question. If the current OS were no longer viable and a new one were needed, then the situation would be different.
In other words, I don't think your argument is wrong—I just don't think there's enough motivation for it.
In that sense, codebases that heavily use AI are already appearing in abundance.
There were issues with Open CLAW, but it was purely AI-written and still boasted a huge number of active users, right?
Same goes for Codex.
So my conclusion is this: AI is currently being used in layers above the infrastructure. But if a new infrastructure needs to be built, that's when AI will come into play.
In other words, it's a matter of motivation. Using AI for coding doesn't eliminate maintenance costs. And to be extreme, both maintenance and generation now require spending 'tokens'—you're paying money instead of the developer's time. We need to think about that cost.
In other words, there's no reason to break something that's already working.
I'd summarize it as: there's no reason to reinvent the wheel.
Re: AI doesn't generate working products, that's still your job
#106I'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 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 clean up. Also, models like Opus always want to do too much work/research. I'm not sure if this is caused by Anthropic optimizing for tokenmaxing or the model being overoptimized for agentic programming.
I also notice this in PRs from of others. Yes, in a shallow sense, it solved the problem that they had in their prompt. But while doing it, their LLMs made very suboptimal solutions that are hard to maintain long-term.
So, I have increasingly resorted to smaller open source models or 'weaker' models like Claude 4.5 or 4.6, since they are often much better for LLM-assisted programming, where you have the implementation steps in your head (you know what the implementation should look like) and work towards the solution with the model step by step. Working like that is extremely powerful and much faster than programming by hand (an LLM memoizes/searches the APIs faster/better and can more quickly write the boilerplate that programming sometimes also requires. I feel like a can be a few times faster than my old self, while not leaving the code base behind in a mess, and not atrophying knowledge, since I still do most of the thinking, design, etc.
Re: AI doesn't generate working products, that's still your job
#107> An experienced engineer using modern AI tools can move at a pace that would have been unimaginable five years ago.
I dunno sometimes I think I should have sticked with a simpler solution coded by hand with more tradeoffs, than trying doing more and spend days back and forth in an endless feedback loop. Or fighting back the Agent that is more than happy to over produce.
IMO the problem is not the single developer using more agentic tooling, it's the whole work chain, who reviews your changes use agentic tooling assistance and over produce a lot of feedback and you're back with the clanker making many decisions that just drains you at the end of the day. I miss the times where we released many more simple things sith many more tradeoffs and business decisions
Re: AI doesn't generate working products, that's still your job
#108I've seen too many similar posts on Hacker News. From 2025 to 2026, I've seen countless articles with titles like 'The Prototype Isn't the Product.' I think these are defensive mechanisms, a kind of lullaby for the Gen AI era. Why is this discourse endlessly reproduced? In my view, it's because the industry is still searching for a new methodology to control the waterfall of Gen AI code. The cognitive dissonance that…
> Looking at the countless repetitive posts on HN, it shows what HN programmers are afraid of. They're afraid of the destruction of their overall meta-methodology. I think this already happened. What's hard to swallow for us is the countless years spent studying, researching, and investing our time to be the best possible professionals in a very demanding, skill-intensive industry. Now that software development is st…
Similar situation here, am a senior dev with 26 years in the industry and now some management experience.
Some of my guys are getting massively productive, some are not really catching the wave. But me … I feel like the joy of coding has been sucked out from under me, and I see the (very sharp) product guys being more and more able to tell Claude rather than ask a developer. If they can perform 90% of what we were doing and fulfill customer needs, probably faster, who needs us any more?
I’ve started wondering if it’s too late to retrain as an electrician.
Re: AI doesn't generate working products, that's still your job
#109I'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…
You get a sense for when things start to drift.
“Any organization, cleanup or consolidation needed?”
Re: AI doesn't generate working products, that's still your job
#110The 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…
I have a similar one. Is Claude Code (web and/or VS Code) still a buggy mess? Pretty much every single agent loop bugs out and requires a hard refresh, which sometimes still doesn’t help. And they have an effectively infinite LLM budget and unreleased models to fix the issues.