Join the discussion
Write your take first — we'll ask for email only when you're ready to publish.
- Hacker News
- Personally, i've taken a serious step back from 'unsupervised' vibe-coding. When the codebase is clean and you want some additional fix or small feature, Claude is quite good at mimicking your style and does a pretty good job.
When asking for a new major feature, despite hard guidelines and context (that eat half your context window), then it quickly ships bloat. The foundations are not very well organized and this is where you acknowledge it is all about random-prediction of the next word-thing.
Overall, i've wasted more time reviewing the PR and trying to steer it properly than I expected. So multi-layer agent vibe coding is no longer the way to go *for me*. Maybe with unlimited tokens and a better prompt, to be investigated...
by simon84 - And it can quickly start spiraling out of control. The bloated implementations keep adding more and more context it needs for the next change. Discovery results start getting worse, implementations get worse, and bloat continues to increase.by Rapzid
- This reads too much like it was LLM generated. I can't say for sure if it was but I have an allergic reaction to the short snappy know-it-all LLM writing style.by shahbaby
- yeah, it set off my llm radar tooby fromwilliam
- Writing code by hand but blog post are written by LLMs?by baxtr
- AI;DR
- > Vibe-coding makes you feel like you have infinite implementation budget. You don't. You have infinite LINE budget (the AI will generate as much code as you want). But you have the same finite complexity budget as always.
This is a special case of a general fundamental point I'm struggling with.
Let's assume AI has reduced the marginal cost of code to zero. So our supply of code is now infinite.
Meanwhile, other critical factors continue to be finite: time in a day, attention, interest, goodwill, paying customers, money, energy.
So how do you choose what to build?
Like a genie, the tools give us the power to ask for whatever we want. And like a genie, it turns out we often don't really know what we want.
by viceconsole - I have vibe coded 3 applications I never had time to code but always wanted.
Now it is different in a way where now I don’t have time to use those apps.
That’s a joke.
But I do believe it answers the question of “what to build?”. If you didn’t have time before LLM assisted coding you still don’t have time for it. You most likely know what is used and what not already by heart or by some measurements.
by ozim - Right - knowing what to actually build always has been and always will be the limiting factor to actual success. I could spend months and hundreds of dollars generating the absolute BEST todo list that's out there but nobody wants that.
- So you're not actually writing code by hand? I'm very confused by the difference between the title and the conclusion here.by xantronix
- I don't think they even wrote the article by hand. It seems like the title got to the top of HN not the article.by dwedge
- The point was to come up with a sensationalistic headline that HN eats up and post flies to the front page.by rane
- I feel like I’m watching developers speed run project and product management learnings.
We’ve moved to seeing that specs are useful and that having someone write lots of wrong code doesn’t make the project move faster (lots of times devs get annoyed at meetings and discussions because it hinders the code writing, but often those are there to stop everyone writing more of the wrong thing)
We’ve seen people find out that task management is useful.
Now more I’m seeing talk of fully doing the design work upfront. And we head towards waterfall style dev.
Then we’ll see someone start naming the process of prototyping, then I’m sure something about incremental features where you have to ma age old vs new requirements. Then talk of how really the customer needs to be involved more.
Genuinely, look at what projects and product managers do. They have been guiding projects where the product is code yet they are not expected to read the code and are required to use only natural language to achieve this.
by IanCal - So right. All these guys have never been managers. Do you think humans don't write things that break? Or that teams sometimes take a wrong path and burn a week of work? Or months? Well now you can experience all of that in 30 minutes of vibecoding. As a former tech product manager, it feels EXACTLY the same.
- Title says
> back to writing code by hand
But what they are doing is
> doing the __design work__ myself, by hand, before any code gets written.
So... Claude still is generating the code I guess?
And seriously, I can't understand that they thought their vibe coded project works fine and even bought a domain for the project without ever looking at source code it generated, FOR 7 MONTHS??
by plastic041 - I bought domains for projects minutes after the idea.
I don’t think it’s that weird to not look at the code if it’s a side project and you follow along incrementally via diffs. It’s definitely a different way of working but it’s not that crazy.
by dewey - In short, it is simply a click-bait title.
And the goal of the article is to draw attention to their project.
by 0xpgm - I always find these kinds of posts interesting, to compare the velocity that people seem to get with Ai, vs what I get by just coding by hand
Coincidentally I've been working on a project for about 7 months now: its a 3d MMO. Currently its playable, and people are having fun with it - it has decent (but needs work) graphics, and you can cram a few hundred people into the server easily currently. The architecture is pretty nice, and its easy to extend and add features onto. Overall, I'm very happy with the progress, and its on track to launch after probably a years worth of development
In 7 months vibe coding, OP failed to produce a basic TUI. Maybe the feature velocity feels high, but this seems unbelievably slow for building a basic piece of UI like this - this is the kind of thing you could knock out in a few weeks by hand. There are tonnes of TUI libraries that are high quality at this point, and all you need to do is populate some tables with whatever data you're looking for. Its surprising that its taking so long
There seems to be a strong bias where using AI feels like you're making a lot of progress very quickly, but compared to manual coding it often seems to be significantly slower in practice. This seems to be backed up by the available productivity data, where AI users feel faster but produce less
by 20k - It's more complex than that, I think the reality is that there's a lot of code that's just not that deep bro. I have some purely personal projects that have components that I don't understand anymore, I wrote that shit by hand, they still work but I haven't touched that shit in years. There's a lot of code that AI can write that's like that that helps me, the stuff I would forget about even if I wrote it by hand. I think you have to have discipline in it's use, it's a tool like any other.
AI, and especially agentic AI can make you lose situational awareness over a codebase and when you're doing deep work that SUUUUCKS, but it's not useless, you just have to play to it's strengths. Though my favorite hill to die on is telling people not to underestimate it's value as autocomplete. Turns out 40 gigabytes of autocomplete makes for a fucking amazing autocomplete. Try it with llama.vim + qwen coder 30b, it feels like the editor is reading your mind sometimes and the latency is so low.
- This was made in two days of vibe coding. It has flaws, but it's impressive as hell:
It's got a fun Zelda-inspired mechanic (I won't say which one), and you'll have to unlock abilities and parts of the world over several quests and modes to "win".
It's also multiplayer.
by echelon - Seems to be baked into the GPT- produce text- aka to produce language and code is life and purpose. So the whole system is inherently internally biased towards "roll your own everything?" unless spoke too in a "Senior-dev" language, that prevents these repetitions.by 21asdffdsa12
- This is probably because the people who feel like they receive the most benefit from LLMs never actually knew much about or were just incapable of writing good software before they started using LLMs.by manicennui
- This struck me as odd too. 7 months? It wouldn’t take that long to write it in a new language.
Another thing I don’t see mentioned is code quality.
Vibe-coded code bases are an excellent example of why LLMs aren’t very good at writing code. It will often correct its own mistakes only to make them again immediately after and Inconsistent pattern use.
Recently Claude has been making some “interesting” code style choices, not inline with the code base it’s currently supposed to be working on.
by chromadon - You nailed it, I came to the same conclusion recently. When people show me what have they done with LLM, I am left unimpressed as mostly they show things that can be done manually in a very short time. I also failed to observe the rise in availability of impressive software, which coincides with the fact that LLMs are currently being used to solve simple problems, instead of important ones.by fancythat
- > There seems to be a strong bias where using AI feels like you're making a lot of progress very quickly, but compared to manual coding it often seems to be significantly slower in practice.
This metric highly depends on who uses the AI to do what, where strong emphasis is on "who" and "what".
In my line of work (software developer) the biggest time sinks are meetings where people need to align proposed solutions with the expectations of stakeholders. From that aspect AI won't help much, or at all, so measuring the difference of man hours spent from solution proposal to when it ends up in the test loops with and without AI would yield... very disappointing results.
But for troubleshooting and fixing bugs, or actually implementing solutions once they have been approved? For me, I'm at least 10x'ing myself compared to before I was using AI. Not only in pure time, but also in my ability to reason around observed behaviors and investigating what those observations mean when troubleshooting.
But I also work with people who simply cannot make the AI produce valuable (correct) results. I think if you know exactly what you want and how you want it, AI is a great help. You just tell it to do what you would have done anyway, and it does it quicker than you could. But if you don't know exactly what you want, AI will be outright harmful to your progress.
by ZaoLahma - That’s the same story I had.
The swindle goes like this, AI on a good codebase can build a lot of features, you think it’s faster it even seems safer and more accurate on times, especially in domains you don’t know everything about.
This goes in for a while whilst the codebase gets bigger and exploration takes longer and failure rate increases. You don’t want it to be true and try harder so you only stop after it practically became impossible to make any changes.
You look at the code again and there is so much code spaghetti is an understatement it’s the Chinese wall.
You start working…, and you realize what was going on
I deleted 75,000 of 140,000 lines of code and I honestly feel like the 3 months I went hard into agentic coding I wasted and I failed my users by building useless features increasing bugs, losing the mental model of my code and not finding the problems I didn’t know about the kind of hard decisions you only see when you in the code, the stuff that wanders in your mind for days
by jwpapi - Obviously this is all my fault and others might have a better jugdement when using it. I’m just sharing my experience compared to the promises you easily might believe reading X/HN/Anthropic.
I still have a lot of usage for AI: Exploration, Double-checking me, teaching me. But writing code became very tough for me to accept. Nex-edit autocompletes mainly
by jwpapi - Yep. I’m approaching the same problem from a different angle: writing code fast means you aren’t being thoughtful about the features you’re building. I started realizing that after I had kids and spent more time thinking about code than writing it and it really improved the quality of my work: https://bower.sh/thinking-slow-writing-fastby qudat
- I haven't had the chance to work on large codebases, but isn't it possible to somehow adapt the workflow of Working Effectively with Legacy Code, building islands of higher quality code, using the AI to help reconstruct developer intention and business rules and building seams and unit tests for the target modules?
AI doesn't necessarily have to increase your throughput, it can also serve as a flexible exploration and refactoring tool that will support either later hand crafter code or agentic implementation.
by gchamonlive - Were you auto-committing everything without reading the generated code? and if you read it but didn't understand it why not just ask for detailed comments for each output? Knowing that a larger codebase causes it to struggle means the output needs to be increasingly scrutinized as it becomes more complex.