At some point you hit a project size that is too large or has too many interdependencies, and you have to be very careful about how you manage the context and should expect the llm to start generating too much code or subtle bugs.
Once you hit that size, in my opinion, it's usually best to drop back to brainstorming mode, only use the llm to help you with the design, and either write the code yourself, or write the skeleton of the code yourself and have the llm fill it in.
With too much code, llms just don't seem able yet to only add a few more lines of code, make use of existing code, or be clever and replace a few lines of code with a few more lines of code. They nearly always will add a bunch of new abstractions.
You can be explicit about these things.
But I have no issues with using Claude Code to write code in larger projects, including adapting to existing patterns, it’s just not vibe coding - I architect the modules, and I know more or less exactly what I want the end result to be. I review all code in detail to make sure it’s precisely what I want. You just have to write good instructions and manage the context well (give it sample code to reference, have agent.md files for guidance, etc.)
These are the perfect size projects vibe coding is currently good for.
So, yes, ONE DAY, AI will be doing all sorts of things (from POTUS and CEO on down), once it is capable of on-the-job learning and picking up new skills, and everything else that isn't just language model + agent + RAG. It the meantime, the core competence of an LLM is blinkers-on (context-on) executing - coding - according to tasks (part of some plan) assigned to it by a human who, just like a lead assigning tasks to human team members, is aware of what it can and can not do, and is capable of overseeing the project.
The capabilities now are strong enough to mix and match almost fully in the co-pilot range on substantial projects and repos.
Once your codebase exceeds a certain size, it becomes counter-productive to have code that is dependent on the implementation of other modules (tight coupling). In Claude Code terms this means your current architecture is forcing the model to read too many lines of code into its context which is degrading performance.
The solution is the same as it is for humans:
"Program to an interface, not an implementation." --Design Patterns: Elements of Reusable Object-Oriented Software (1994)
Suddenly, you've freed up large chunks of context and Claude is now able to continue making progress.
Of course, the project could continue to grow and the relatively small interface declarations could become too many to fit in context. At that point it would be worthwhile taking a look at the application to see if larger chunks of it could be separated from the rest. Managing the number and breadth of changes that Claude is tasked with making would also help since it's unlikely that every job requires touching dozens of different parts of the application so project management skills can get you even further.
The whole thing feels a bit like god-of-the-gaps situation, where we keep trying to squeeze humanity into whatever remaining little gaps the current generation of AI hasn’t mastered yet.
you can tell by how many people earnestly share AI generated images, many are completely tasteless but people don't care
Side note: I once wrote about recreating Delicious Library: https://dingyu.me/blog/recreating-delicious-library-in-2025
Vibe coding has really helped me explore skills outside of my comfort zone which can then be applied in combination with other existing skills or interests in new ways.
In the case of your project, I imagine that now that you can gather data such as books from an image of a bookshelf, you can do something similar in infinite other ways.
I wonder if you could develop this as an add on to Hardcover.app - you could fetch people's books, images, and display the bookshelf.
All the data seems to be there:
https://hardcover.app/@BenHouston3D/books/read?order=owner_l...
SerpAPI provides a very valuable programmatic access to search that Google are hell bent on never properly providing
Something you don’t really mention in the post is why do this? Do you have an end goal or utility in mind for the book shelf? Is it literally just to track ownership? What do you do with that information?
I want my website to slowly become a collection of things I do and like, and this bookshelf is just one of those pieces.
I’ve been vibe-coding a personalized outliner app in Rust based on gpui and CRDTs (loro.dev) over the last couple days - something just for me, and in a big part just to explore the problem space - and so far it’s been very nice and fun.
Especially exploring multiple approaches, because exploring an approach just means leaving the laptop working for an hour without my attendance and then seeing the result.
Often I would have it write up a design doc with todos for a feature I wanted based on its exploration, and then just launch a bash for loop that launches Claude with “work on phase $i” (with some extra boilerplate instructions), which would have it occupied for a while.
So many systems are fault-tolerant, and it’s great to remember that in a world where LLMs introduce new faults. Kudos to OP for this mindset; more anti-AI posters would benefit from sitting with the idea from time to time.
This is the right mindset.
My experience with Claude was mostly very good. Certainly the UI is far better than what I'd come up with myself. The backend is close to what I'd write myself. When I'm unhappy I'm able to explain the shortcomings and it's able to mostly fix itself. This sort of small-scale, self-contained project was made possible thanks to Claude.
Other times it just couldn't. The validation for the start and end dates it decided was z.string().or(z.date()).optional().transform((val) => (val ? new Date(val) : undefined)). It looked way too complex. I asked if it could be simplified, Claude said no. I suggested z.date().optional(). Claude patiently explained this was impossible. I tried it anyway, it worked. Claude said "you're absolutely right!". But this behaviour was the exception rather than the rule.
> Claude did not invent that idea. It executed it.
> Claude handled implementation. I handled taste.
This style of writing always gets me now :)
^^ These dramatic statements are almost always AI influenced, I seem to always see them in people's emails now as well. "we didnt reinvent the wheel. we are the wheel."
Seriously: what tool do you want to use that's immediately available to the absolute lowest common denominator "writers" on the Internet?
"It's not X, it's Y" literally makes my stomach churn from seeing so much of it on LinkedIn.
I think it some kind of value - vibe dynamics that play in making the brain conscious about it being written with AI or otherwise.
> I started asking for things I did not need.
For a community that prides itself on depth of conversation, ideas, etc. I'm surprised to so much praise for a post like this. I'll be the skeptic. What does it bring to you to vibe code your vibe shelf?
To me, this project perfectly encapsulates the uselessness of AI, small projects like this are good learning or relearning experience and by outsourcing your thinking to AI you deprive yourself of any learning, ownership, or the self fulfillment that comes with it. Unless, of course, you think engaging in "tedious" activities with things you enjoy have zero value, and if getting lost in the weeds isn't the whole point. Perhaps in one of those books you didn't read, you missed a lesson about the journey being more important than the destination, but idk I'm more of a film person.
The only piece of wisdom here is the final sentence:
> Taste still does not [get cheaper].
Though, only in irony.
First, I took photographs of all my physical books simply by photographing the bookshelves such that the book spines were visible.
Then passed the photographs with a prompt akin to, "These are photographs of bookshelves. Create a table of book title and book author based on the spines of the books in these photographed shelves." ChatGPT4’s vision model handled this no problem with pretty high accuracy.
I then vibe-coded a Python program with ChatGPT4 to use the Google Books API (an API key for that is free) to generate a table, and then a CSV, of: book title, book author, and isbn13. Google Books API lets you look up an ISBN based on other metadata like title and author easily.
Finally, I uploaded the enriched CSV into a free account of https://libib.com. This is a free SaaS that creates a digital bookshelf and it can import books en masse if you have their ISBNs. You can see the result of this here for my bookshelf:
https://www.libib.com/u/freenode-fr33n0d3
There are some nice titles in there for HN readers! My admin app for Libib (the one at https://libib.com) is more full-featured than the above public website showcases. It's basically software for running small lending libraries. But, in my case, the “lending library” is just my office’s physical bookshelf.
I also added a Libib collection there that is a sync of my Goodreads history, since I read way more Kindle books than physical books these days. That was a similarly vibe-coded project. But easier since Goodreads can export your book collection, including isbn13, to a file.
As for my actual physical bookshelf, it is more a collection of books I either prefer in print, or that are old, or out-of-print, or pre-digital & never-digitized.
I liked the Libib software so much I end up donating to it every year. I originally discovered it because it is used for Recurse Center’s lending library in the Recurse Center space in Brooklyn, NY (https://recurse.com).
Also, Libib has a Android, iPhoneOS, and iPadOS apps -- these are very basic but they do allow you to add new books simply by scanning their ISBN barcode, which is quite handy when I pick up new items.
I did enjoy reading the OP writeup, it’s a fun idea to vibe-code the actual digital bookshelf app, as well!
This is my experience with agents, particularly Claude Code. It supplies sufficient activation energy to get me over the hump. It makes each next step easy enough that I take it.
Not either of the species of algorithms you've described, but still an advance.
This is the "promise" that was being sold here and in reality, we yet haven't seen anything innovative or even a sophisticated original groundbreaking discovery from an LLM with most of the claims being faked or unverified.
Most of the 'vibe-coding' uses here are quite frankly performative or used for someone's blog for 'content'.
This is still pretty great!
Don't get me wrong, AI is at least as game-changing for programming as StackOverflow and Google were back in the day. Being able to not only look up but automatically integrate things into your codebase that already exist in some form in the training data is incredibly useful. I use it every day, and it's saved me hours of work for certain specific tasks [0]. For tasks like that, it is indeed a 10x productivity multiplier. But since these tasks only comprise a small fraction of the full software development process, the rest of which cannot be so easily automated, AI is not the overall 10x force multiplier that some claim.
Until it decides to include code it gathered from a stackoverflow post 15 years ago probably introducing security related issues or makes up libraries on the go or even worse, tries to make u install libs that were part of a data poisoning attack.
As someone who frequently uses Claude Code, I cannot say that a year's worth of features/improvements have been added in the last month. It bears repeating: if AI is truly a 10x force multiplier, you should expect to see a ~year's worth of progress in a month.
That's obviously not going to happen, because AI tools can't solve for taste. Just because a developer can churn out working code with an LLM doesn't mean they have the skills to figure out what the right working code to contribute to a project is, and how to do so in a way that makes the maintainers lives easier and not harder.
That skill will remain rare.
(Also SQLite famously refuses to accept external contributions, but that's a different issue.)
Why? People don't ask hammers to do much more than bash in nails into walls.
AI coding tools can be incredibly powerful -- but shouldn't that power be focused on what the tool is actually good at?
There are many, many times that AI coding tools can and should be used to create a "small program that already exists in multiple forms in the training data."
I do things like this very regularly for my small business. It's allowed me to do things that I simply would not have been able to do previously.
People keep asking AI coding tools to be something other than what they currently are. Sure, that would be cool. But they absolutely have increased my productivity 10x for exactly the type of work they're good at assisting with.
I think it's for a very reasonable reason: the AI coding tool salespeople are often selling the tools as something other than what they currently are.
I think you're right, that if you calibrate your expectations to what the tools are capable of, there's definitely. It would be nice if the marketing around AI also did the same thing.
Maybe this is possible. Maybe not.
However, it's a fantasy. Granted, it is a compelling fantasy. But its not one based on reality.
A good example:
"AI will probably be smarter than any single human next year. By 2029, AI is probably smarter than all humans combined.” -- Elon Musk
This is, of course, ridiculous. But, why should we let reality get in the way of a good fantasy?
Let's not disregard interesting achievements because they are not something else.
No one is propping up a multi-billion dollar tech bubble by promising hammers that do more than bash nails. As a point of comparison that makes no sense.
“It resembles a normal hammer but is outfitted with an little motor and an flexible head part which moves back and forth in a hammering motion, sparing the user from moving his or her own hand to hammer something by their own force and by so making their job easier”
I am happy as is tbh, not even looking for AGI and all. Just that the LLM be close enough to my thinking scale so that it does not feel "why am I talking with this robot".
1. Current LLMs do much better than produce "small programs that already exist in multiple forms in the training data". Of course the knowledge they use does need to exist somewhere in training data, but they operate at a higher level of abstraction than simply spitting out programs they've already seen whole cloth. Way higher.
2. Inventing a new compression algorithm is beyond the expectations of all but the the most wild-eyed LLM proponents, today.
That seems to be a strawman here, no? Sure, there exist people/companies claiming 10x-100x productivity improvements. I agree it's bullshit.
But the article doesn't seem to be claiming anything like this - it's showing the use of vibe-coding for a small personalized side-project, something that's completely valid, sensible, and a perfect use-case for vibe-coding.
This is going to destroy my home network, since I never moved it off the little Lenovo box sitting in my laundry room beside the Eero waypoint, but I’m out of town for three days, so
Granted, the seed of the idea was someone posting about how they wired pyiodide to Ace in 400 lines of JavaScript, so I can’t truly argue it’s non-trivial.
As a light troll to hackernews, only AI-written contributions are accepted
[Edit: the true inception of this project was my kid learning Python at school and trinket.io inexplicably putting Python 3 but not 2 behind the paywall. Alas, Securely will not let him and his classmates actually access it ]
Here is how it works: I take the latest state of the art model, usually one of the two or three currently being hyped....and ask it to create a short document that teaches Java, Python, or Rust, in 30 to 60 min, complete with code examples. Then I ask the same model to review its own produced artifact, for correctness and best practices.
What happens next is remarkably consistent. The model produces a glowing review, confidently declaring the document “production ready”… while the code either does not compile, contains obvious bugs, or relies on outright bad practices.
When I point this out, the model apologizes profusely and generates a “fixed” version which still contains errors. I rinse and repeat until I give up.
This is still true today, including with models like Opus 4.5 and ChatGPT 5.2. So whenever I read comments about these models being historic breakthroughs, I can’t help but imagine they are mostly coming from teams proudly generating technical debt at 100× the usual speed.
Things go even worst, when you ask the model to review a Cloud Architecture....
This is a critical observation of the vibocene.
Vibe coded a library last month for my website however its much simpler and has Antilibrary section for all the stuff I have not read.
I wish book archive sites like archive.org scanned and stored the book spines as well as the covers, but AFAICT none do.
Very relatable!
This is such a key thing I remind myself when I build apps like this for myself. I have a similar app that has a page with 900-odd ratings, and another with 550 owned books. I decided that I won't bother with infinite scroll or complex search and filtering until my browser can no longer handle rendering that data. "Find in page" works well enough for me for now.
kingkongjaffa•2h ago
One-off scripts and single page html/css/js apps that run locally are fantastically accessible now too.
As someone who doesn't code for a living, but can write code, I would often go on hours/day long side quests writing these kind of apps for work and for my personal life. I know the structure and architecture but lack the fluency for speedy execution since I'm not writing code everyday. Claude code fills that speed gap and turned my days/hours long side quests into minutes for trivial stuff, and hours for genuinely powerful stuff at home and at work.