I love this article just for the spirit of fun and experimentation on display. Setting up a VPS where Claude is just asked to go nuts - to the point where you're building a little script to keep Claude humming away - is a really fun idea.
This sort of thing is a great demonstration of why I remain excited about AI in spite of all the hype and anti-hype. It's just fun to mess with these tools, to let them get friction out of your way. It's a revival of the feelings I had when I first started coding: "wow, I really can do anything if I can just figure out how."
> “wow, I really can do _anything_ if I can just figure out how
Except this time it’s “if I can just figure out how and pay for the Claude API usage”.
This is one of the sadder things about AI usage getting more standard that I haven’t seen discussed much—-the barrier to entry is now monetary rather than just knowledge-based, which will make it _much_ harder for young people with no money to pick up.
Yes, they can still write code the manual way, but if the norm is to use AI I suspect that beginner’s guides, tutorials, etc. will become less common.
I think this is the main sentiment I can't wrap my head around. Using Claude Code or Cursor has been entirely a mind-numbingly tedious experience to me (even when it's been useful.) It's often faster, but 80% of the time is spent just sitting there waiting for it to finish working, and I'm not proud of the result because I didn't do anything except come up with the idea and figure out how to describe it well. It just ends up feeling like the coding equivalent of...like...copying down answers to cheat on a test. Not in the sense that it feels gross and wrong and immoral, but in the sense that it's unsatisfying and unfulfilling and I don't feel any pride in the work I've done.
For things where I just want something that does something I need as quickly as possible, sure, I wasn't going to care either way, but personal projects are where I find myself least wanting to vibe code anything. It feels like hiring someone else to do my hobbies for me.
Particularly with the VSCode extension. I was a loyal Cline user until recently because of how good the editor experience was, but the ability for Claude to go off and run for 10+ minutes effectively autonomously, and show me the diffs in realtime is a gamechanger. The token usage has also gotten much more efficient in the last few months. With proper IDE support now I don't see any reason at all to use anything else, especially not the "credit" based middle-man providers (Windsurf/Cursor et. al).
The title is a bit exaggerated. The depth of the projects covered in the article is clearly not representative of "all".
In fact, I now prefer to use a purely chat window to plan the overall direction and let LLM provide a few different architectural ideas, rather than asking LLM to write a lot of code whose detail I have no idea about.
That's my gist. All of these seem pretty basic apps I would see implemented to demo a new web or REST framework. Comment ranker is cool, but I can't imagine its doing much more than scrape text > call semantic api > modify DOM.
How much of this is buildings versus recalling tutorials in the dataset. For every vibe coded project with 20 lines of requirements, I have a model with 20 different fields all with unique semantic meanings. In focused areas, AI has been okay. But I have yet to see Claude or any model build and scale a code base with the same mindset.
This article feels like it was written as a dialectical exercise between an AI and a human. It would probably benefit from some more heavy human editing to make it more succinct and to give the overall article a structure. As it is, it's very difficult to follow along.
I’ve seen a lot of articles like this on the HN page recently… stuff that has one or two interesting tidbits, but is clearly just a conversation someone had with an AI and dumped into an article. Don’t make me wade through all the AI word barf to get the interesting points, that’s what old fashioned editing is for.
"I wrote this entire article in the Claude Code interactive window. The TUI flash (which I've read is a problem with the underlying library that's hard to fix) is really annoying, but it's a really nice writing flow to type stream of consciousness stuff into an editor, mixing text I want in the article, and instructions to Claude, and having it fix up the typos, do the formatting, and build the UX on the fly.
Nearly every word, choice of phrase, and the overall structure is still manually written by me, a human. I'm still on the fence about whether I'm just stuck in the old way by preferring to hand-craft my words, or if models are generally not good at writing.
"
Either he's lying, or you're wrong.
Agree on the structure part. I mostly read it as a piece from someone who's having fun with the tool. Not a structured article for future generations.
This article seems fun, and it's interesting, but I was waiting for the point and it never came.
The author didn't do anything actually useful or impactful, they played around with a toy and mimicked a portion of what it's like to spin up pet projects as a developer.
But hey, it could be that this says something after all. The first big public usages of AI were toys and vastly performed as a sideshow attraction for amused netizens. Maybe we haven't come very far at all, in comparison to the resources spent. It seems like all of the truly impressive and useful applications of this technology are still in specialized private sector work.
I appreciate this writeup. I live in the terminal and work primarily in vim, so I always appreciate folks talking about tooling from that perspective. Little of the article is that, but it's still interesting to see the workflow outlined here, and it gives me a few ideas to try more of.
However, I disagree that LLMs are anywhere near as good as what's described here for most things I've worked with.
So far, I'm pretty impressed with Cursor as a toy. It's not a usable tool for me, though. I haven't used Claude a ton, though I've seen co-workers use it quite a bit. Maybe I'm just not embracing the full "vibe coding" thing enough and not allowing AI agents to fully run wild.
I will concede that Claude and Cursor have gotten quite good at frontend web development generation. I don't doubt that there are a lot of tasks where they make sense.
However, I still have yet to see a _single_ example of any of these tools working for my domain. Every single case, even when the folks who are trumpeting the tools internally run the prompting/etc, results in catastrophic failure.
The ones people trumpet internally are cases where folks can't be bothered to learn the libraries they're working with.
The real issue is that people who aren't deeply familiar with the domain don't notice the problems with the changes LLMs make. They _seem_ reasonable. Essentially by definition.
Despite this, we are being nearly forced to use AI tooling on critical production scientific computing code. I have been told I should never be editing code directly and been told I must use AI tooling by various higher level execs and managers. Doing so is 10x to 100x slower than making changes directly. I don't have boilerplate. I do care about knowing what things do because I need to communicate that to customers and predict how changes to parameters will affect output.
I keep hearing things described as an "overactive intern", but I've never seen an intern this bad, and I've seen a _lot_ of interns. Interns don't make 1000 line changes that wreck core parts of the codebase despite being told to leave that part alone. Interns are willing to validate the underlying mathematical approximations to the physics and are capable of accurately reasoning about how different approximations will affect the output. Interns understand what the result of the pipeline will be used for and can communicate that in simple terms or more complex terms to customers. (You'd think this is what LLMs would be good at, but holy crap do they hallucinate when working with scientific terminology and jargon.)
Interns have PhDs (or in some cases, are still in grad school, but close to completion). They just don't have much software engineering experience yet. Maybe that's the ideal customer base for some of these LLM/AI code generation strategies, but those tools seem especially bad in the scientific computing domain.
My bottleneck isn't how fast I can type. My bottleneck is explaining to a customer how our data processing will affect their analysis.
(To our CEO) - Stop forcing us to use the wrong tools for our jobs.
(To the rest of the world) - Maybe I'm wrong and just being a luddite, but I haven't seem results that live up to the hype yet, especially within the scientific computing world.
In my view its a tool, at least for the moment. Learn it, work out how it works for you, and what it doesn't work for you. But assuming you are the professional they should trust your judgement, and you should also earn that trust. That's why you pay skilled people for. If that tool isn't the best to getting the job done use something else. Of course that professional should be evaluating tools and assuring us/management (whether by evidence or other means) that the most cost efficient and quality product is being built like any other profession.
I use AI, and for some things its great. But I'm feeling like they want us to use the "blunt instrument" that is AI when sometimes a smaller, more fine grained tool/just handcrafting code for accuracy at least for me is quicker and more appropriate. The autonomy window as I recently heard it expressed.
If Anthropic is smart they would open it up to other models now to make it default for everyone. Otherwise you are banking on Sonnet remaining the best coding model.
> I watched the autonomous startup builder a bit more.
I think i'm done with this community in the age of vibe coding. The line between satire, venture capitalism, business idea guys and sane tech enthusiasts is getting too blurry.
It didn't seem to do anything well. And weird quotes like 'I think it one-shotted that too' on something important. What on earth is this. Reading it is like experiencing a bad weird dream.
I've asked copilot (Claude Sonnet 4) to edit some specific parts of a project. It removed the lines that specifically have comments that say "do not remove" with long explanation why. Then it went ahead and modified the unit tests to ensure 100% coverage.
Using coding agent is great btw, but at least learn how to double check their work cuz they are also quite terrible.
You run a coding agent with no permissions checks on a production server anywhere I'm involved in security and I will strike down upon thee with great vengeance and furious anger.
Really, any coding agent our shop didn't write itself, though in those cases the smiting might be less theatrical than if you literally ran a yolo-mode agent on a prod server.
Is Claude Code better than the Gemini CLI? I've been using the Gemini CLI with Gemini 2.5 Pro and haven't been impressed. Maybe these LLMs aren't as good with Rust codebases? I'm guessing there are a lot more people looking to use these tools with JS and Python.
- Repeat more than 20 times the same response to my prompt rejecting its proposed changes; I just kept prompting to see how far it would go before doing something different. Claude Code would quickly guess there is something wrong and try something else or ask what I'm getting at
- Continually refer to outdated versions of files, even after I've told to re-read the files
- Refer to files in a different session on a different machine that have no relevance to what I'm currently doing, presumably simply because I logged in with the same account.
- Randomly crash or enter infinite loops, sometimes soon after starting
- Refuse to read files in a sibling or parent folder
- Fail to understand simple request.
- Propose empty changes
Claude Code is just far better. I only use Gemini CLI for the simplest of tasks
This is good stuff. While somebody could build a Trello clone or an image generator by typing “git clone “ followed by any number of existing projects, the code you’d get might’ve been written by a person, plus if you do that you’re not even spending any money, which just doesn’t seem right.
The future is vibe coding but what some people don’t yet appreciate what that vibe is, which is a Pachinko machine permanently inserted between the user and the computer. It’s wild to think that anybody got anything done without the thrill of feeding quarters into the computer and seeing if the ball lands on “post on Reddit” or “delete database”
I'd personally rather use gpt-5. The sub price is cheap and offers more overall value than an Anthropic sub or paying per token. The chatgpt app on iPhone and Mac are native and nicer than Anthropic's and offer more features. Codex is close enough to Claude Code and also now native. For me it's nicer to use the "same" model across each use case like text, images, code etc. this way I better understand the limitations and quirks of the model rather than the constant context switching to different models to get maybe slightly better perf. To each their own though depending on your personal use case.
> export IS_SANDBOX=1 && claude --dangerously-skip-permissions
FYI, this can be shortened to:
IS_SANDBOX=1 claude --dangerously-skip-permissions
You don't need the export in this case, nor does it need to be two separate commands joined by &&. (It's semantically different in that the variable is set only for the single `claude` invocation, not any commands which follow. That's often what you want though.)
> I asked Claude to rename all the files and I could go do something else while it churned away, reading the files and figuring out the correct names.
It's got infinite patience for performing tedious tasks manually and will gladly eat up all your tokens. When I see it doing something like this manually, I stop it and tell it to write a program to do the thing I want. e.g. I needed to change the shape of about 100 JSON files the other day and it wanted to go through them one-by-one. I stopped it after the third file, told it to write a script to import the old shape and write out the new shape, and 30 seconds later it was done. I also had it write me a script to... rename my stupidly named bank statements. :-)
This. I had a 10000 line css file, and told it to do a find and replace on some colours. It was hilariously bad at this and started chewing tokens. Asking it to write a script to swap it out and then execute that script for me and it was done instantly. Knowing the right questions to ask an AI is everything.
Why isn't anyone talking about the HackerNews Comment Ranker plugin? [1] That's amazing. I had this idea too -- to rank HN comments by their relevance to the actual article, and filter out comments that obviously didn't read it.
I need to modify this to work with local models, though. But this does illustrate the article's point -- we both had an idea, but only one person actually went ahead and did it, because they're more familiar with agentic coding than me.
93 comments
[ 4.5 ms ] story [ 71.3 ms ] threadThis sort of thing is a great demonstration of why I remain excited about AI in spite of all the hype and anti-hype. It's just fun to mess with these tools, to let them get friction out of your way. It's a revival of the feelings I had when I first started coding: "wow, I really can do anything if I can just figure out how."
Great article, thanks for sharing!
Except this time it’s “if I can just figure out how and pay for the Claude API usage”.
This is one of the sadder things about AI usage getting more standard that I haven’t seen discussed much—-the barrier to entry is now monetary rather than just knowledge-based, which will make it _much_ harder for young people with no money to pick up.
Yes, they can still write code the manual way, but if the norm is to use AI I suspect that beginner’s guides, tutorials, etc. will become less common.
I think this is the main sentiment I can't wrap my head around. Using Claude Code or Cursor has been entirely a mind-numbingly tedious experience to me (even when it's been useful.) It's often faster, but 80% of the time is spent just sitting there waiting for it to finish working, and I'm not proud of the result because I didn't do anything except come up with the idea and figure out how to describe it well. It just ends up feeling like the coding equivalent of...like...copying down answers to cheat on a test. Not in the sense that it feels gross and wrong and immoral, but in the sense that it's unsatisfying and unfulfilling and I don't feel any pride in the work I've done.
For things where I just want something that does something I need as quickly as possible, sure, I wasn't going to care either way, but personal projects are where I find myself least wanting to vibe code anything. It feels like hiring someone else to do my hobbies for me.
In fact, I now prefer to use a purely chat window to plan the overall direction and let LLM provide a few different architectural ideas, rather than asking LLM to write a lot of code whose detail I have no idea about.
How much of this is buildings versus recalling tutorials in the dataset. For every vibe coded project with 20 lines of requirements, I have a model with 20 different fields all with unique semantic meanings. In focused areas, AI has been okay. But I have yet to see Claude or any model build and scale a code base with the same mindset.
"I wrote this entire article in the Claude Code interactive window. The TUI flash (which I've read is a problem with the underlying library that's hard to fix) is really annoying, but it's a really nice writing flow to type stream of consciousness stuff into an editor, mixing text I want in the article, and instructions to Claude, and having it fix up the typos, do the formatting, and build the UX on the fly.
Nearly every word, choice of phrase, and the overall structure is still manually written by me, a human. I'm still on the fence about whether I'm just stuck in the old way by preferring to hand-craft my words, or if models are generally not good at writing.
"
Either he's lying, or you're wrong.
Agree on the structure part. I mostly read it as a piece from someone who's having fun with the tool. Not a structured article for future generations.
I thought the article was a satire after I read this ... but it wasn't!
The author didn't do anything actually useful or impactful, they played around with a toy and mimicked a portion of what it's like to spin up pet projects as a developer.
But hey, it could be that this says something after all. The first big public usages of AI were toys and vastly performed as a sideshow attraction for amused netizens. Maybe we haven't come very far at all, in comparison to the resources spent. It seems like all of the truly impressive and useful applications of this technology are still in specialized private sector work.
However, I disagree that LLMs are anywhere near as good as what's described here for most things I've worked with.
So far, I'm pretty impressed with Cursor as a toy. It's not a usable tool for me, though. I haven't used Claude a ton, though I've seen co-workers use it quite a bit. Maybe I'm just not embracing the full "vibe coding" thing enough and not allowing AI agents to fully run wild.
I will concede that Claude and Cursor have gotten quite good at frontend web development generation. I don't doubt that there are a lot of tasks where they make sense.
However, I still have yet to see a _single_ example of any of these tools working for my domain. Every single case, even when the folks who are trumpeting the tools internally run the prompting/etc, results in catastrophic failure.
The ones people trumpet internally are cases where folks can't be bothered to learn the libraries they're working with.
The real issue is that people who aren't deeply familiar with the domain don't notice the problems with the changes LLMs make. They _seem_ reasonable. Essentially by definition.
Despite this, we are being nearly forced to use AI tooling on critical production scientific computing code. I have been told I should never be editing code directly and been told I must use AI tooling by various higher level execs and managers. Doing so is 10x to 100x slower than making changes directly. I don't have boilerplate. I do care about knowing what things do because I need to communicate that to customers and predict how changes to parameters will affect output.
I keep hearing things described as an "overactive intern", but I've never seen an intern this bad, and I've seen a _lot_ of interns. Interns don't make 1000 line changes that wreck core parts of the codebase despite being told to leave that part alone. Interns are willing to validate the underlying mathematical approximations to the physics and are capable of accurately reasoning about how different approximations will affect the output. Interns understand what the result of the pipeline will be used for and can communicate that in simple terms or more complex terms to customers. (You'd think this is what LLMs would be good at, but holy crap do they hallucinate when working with scientific terminology and jargon.)
Interns have PhDs (or in some cases, are still in grad school, but close to completion). They just don't have much software engineering experience yet. Maybe that's the ideal customer base for some of these LLM/AI code generation strategies, but those tools seem especially bad in the scientific computing domain.
My bottleneck isn't how fast I can type. My bottleneck is explaining to a customer how our data processing will affect their analysis.
(To our CEO) - Stop forcing us to use the wrong tools for our jobs.
(To the rest of the world) - Maybe I'm wrong and just being a luddite, but I haven't seem results that live up to the hype yet, especially within the scientific computing world.
Wow, this is really extreme. We certainly got to this point faster than I expected.
I use AI, and for some things its great. But I'm feeling like they want us to use the "blunt instrument" that is AI when sometimes a smaller, more fine grained tool/just handcrafting code for accuracy at least for me is quicker and more appropriate. The autonomy window as I recently heard it expressed.
(Sure, I could let them use my credentials but that isn’t really legit/fair use.)
I think i'm done with this community in the age of vibe coding. The line between satire, venture capitalism, business idea guys and sane tech enthusiasts is getting too blurry.
Using coding agent is great btw, but at least learn how to double check their work cuz they are also quite terrible.
Really, any coding agent our shop didn't write itself, though in those cases the smiting might be less theatrical than if you literally ran a yolo-mode agent on a prod server.
- Repeat more than 20 times the same response to my prompt rejecting its proposed changes; I just kept prompting to see how far it would go before doing something different. Claude Code would quickly guess there is something wrong and try something else or ask what I'm getting at
- Continually refer to outdated versions of files, even after I've told to re-read the files
- Refer to files in a different session on a different machine that have no relevance to what I'm currently doing, presumably simply because I logged in with the same account.
- Randomly crash or enter infinite loops, sometimes soon after starting
- Refuse to read files in a sibling or parent folder
- Fail to understand simple request.
- Propose empty changes
Claude Code is just far better. I only use Gemini CLI for the simplest of tasks
The future is vibe coding but what some people don’t yet appreciate what that vibe is, which is a Pachinko machine permanently inserted between the user and the computer. It’s wild to think that anybody got anything done without the thrill of feeding quarters into the computer and seeing if the ball lands on “post on Reddit” or “delete database”
FYI, this can be shortened to:
You don't need the export in this case, nor does it need to be two separate commands joined by &&. (It's semantically different in that the variable is set only for the single `claude` invocation, not any commands which follow. That's often what you want though.)> I asked Claude to rename all the files and I could go do something else while it churned away, reading the files and figuring out the correct names.
It's got infinite patience for performing tedious tasks manually and will gladly eat up all your tokens. When I see it doing something like this manually, I stop it and tell it to write a program to do the thing I want. e.g. I needed to change the shape of about 100 JSON files the other day and it wanted to go through them one-by-one. I stopped it after the third file, told it to write a script to import the old shape and write out the new shape, and 30 seconds later it was done. I also had it write me a script to... rename my stupidly named bank statements. :-)
https://meyerweb.com/eric/comment/chech.html
Repo: https://github.com/sixhobbits/hn-comment-ranker
I need to modify this to work with local models, though. But this does illustrate the article's point -- we both had an idea, but only one person actually went ahead and did it, because they're more familiar with agentic coding than me.
[1] Oh. I think I understand why. /lh