For the animations specifically, it's using Motion (fka Framer Motion) Javascript library. If you describe some animations from the site to an LLM and ask it to use Framer motion, you get very similar results. The creator likely just prompted for a while until they were happy with the outcome.
I guess they really do eat their own dogfood and vibe code their way through it without care for technical debt? In a way, it’s a good challenge, but it’s fairly painful to watch the current state of the project (which is about a year old now, so it should be in prime shape).
> is about a year old now, so it should be in prime shape
A 1yo project may be in good shape if written by just one dev, maybe a few. But if you have many devs, I can guarantee it will be messy and buggy. If anything, at 1yo it is probably still full of bugs because not enough time has elapsed for people to run into them.
It's only 510k LoC, at ~100 lines of code a day for a year, this code base would take 23 engineers a year to write. That's for 220 working days in somewhere civilized.
And I'm sure we all know that when working on a greenfield project you can produce a lot more LoC per day than maintaining a legacy one.
Given that vibe code is significantly more verbose, you're probably talking about ~15 engineers worth of code?
I know that's all silly numbers, but this is just attempting to give people some context here, this isn't a massive code base. I've not read a lot of it, so maybe it's better than the verbose code I see Claude put out sometimes.
Which makes for an interesting thought / discussion; code is written to be read by humans first, executed by computers second. What would code look like if it was written to be read by LLMs? The way they work now (or, how they're trained) is on human language and code, but there might be a style that's better for LLMs. Whatever metric of "better" you may use.
Just a thought experiment, I very much doubt I'm the first one to think of it. It's probably in the same line of "why doesn't an LLM just write assembly directly"
LLMs read and write human-code because humans have been reading and writing human-code. The sample size of assembly problems is, in my estimate, too small for LLMs to efficiently read and write it for common use cases.
I liken it to the problem of applying machine learning to hard video games (e.g. Starcraft). When trained to mimic human strategies, it can be extremely effective, but machine learning will not discover broadly effective strategies on a reasonable timescale.
If you convert "human strategies" to "human theory, programming languages, and design patterns", perhaps the point will be clear.
But: could the ouroboric cycle of LLM use decay the common strategies and design patterns we use into inexplicable blobs of assembly? Can LLMs improve at programming if humans do not advance the theory or invent new languages, patterns, etc?
> It's probably in the same line of "why doesn't an LLM just write assembly directly"
My suspicion is that the "language" part of LLMs means they tend to prefer languages which are closer to human languages than assembly and benefit from much of the same abstractions and tooling (hence the recent acquisition of bun and astral).
Yes but my point was that they seem to explicitly not care about code quality and/or the insane amount of bloat, and seem to just want the LLM to be able to deal with it.
I've heard somewhere that they have roughly 100% code churn every few months, so yes, they unfortunately don't care about code quality. It's a shame, because it's still the best coding agent, in my experience.
Yes, but as I said, it’s in a way the ultimate form of dogfooding: ideally they’ll be able to get the LLM smart enough to keep the codebase working well long-term.
Now whether that’s actually possible is a second topic.
Kairos and auto-dream are more interesting than anything in the agent loop section. Memory consolidation between sessions is the actual unsolved problem. The rest is just plumbing tbh
There's this weird thing about AI generated content where it has the perfect presentation but conveys very little.
For example the whole animation on this website, what does it say beyond that you make a request to backend and get a response that may have some tool call?
That's fair. The site isn't meant to be a deep technical dive, it's more of a visual high-level guide of what I've curated while exploring the codebase while assisted by AI, 500k loc codebase is just too much to sift through in a short amount of time.
I doubt there is anything special about the transformer code the frontier labs use. The only thing proprietary in it are probably the infrastructure-specific optimizations for very large scale distributed training and some GPU kernel tricks. The real moat is the training data, especially the RLHF/finetuning data and verifiable reward environments, and the GPU clusters of course.
The open source models are quite close, and they'd probably be just as good with the equivalent amount of compute/data the frontier labs have access to.
However, I assume that usage data could be increasingly valuable as well. That will likely help the big commercial cloud models to maintain a head start for general use.
Really nice visualisation of this, makes understanding the flow at a high levle pretty clear. Also the tool system and command catalog, particularly the gated ones are super interesting.
I think it's good that it's out there, and I wonder why Anthropic have been keeping it closed source; clearly they can't possibly think that the CC source code is a competitive advantage...?
Agents in general are easy to make, and trivial to make for yourself especially, and the result will be much better than what any of the big providers can make for you.
`pi` with whatever commands/extensions you want to make for yourself is better than CC if you really don't want to go through the trouble of making your own thing.
I feel the same way. Given it's AI-written, looking at the code isn't even worth it to me. I would rather read a blog post about how they develop it day to day.
I mean, I get it: vibe-coded software deserves vibe-coded coverage. But I would at least appreciate it if the main part of it, the animation, went at a speed that at least makes it possible to follow along and didn't glitch out with elements randomly disappearing in Firefox...
It's on the front page because it looks really cool. You can complain about it being vibe coded, but it still looks good. If you ask Claude to allow the user to slow down the animation, it can do that quite easily, that's just not a problem caused by vibe coding. And I'm on FF and didn't notice anything glitching out.
Thanks, I'll use this for teaching next week (on what not to do). BashTool.ts :D But, in general, I guess it just shows yet again that the emperor has no clothes.
A 1yo project may be in good shape if written by just one dev, maybe a few. But if you have many devs, I can guarantee it will be messy and buggy. If anything, at 1yo it is probably still full of bugs because not enough time has elapsed for people to run into them.
And I'm sure we all know that when working on a greenfield project you can produce a lot more LoC per day than maintaining a legacy one.
Given that vibe code is significantly more verbose, you're probably talking about ~15 engineers worth of code?
I know that's all silly numbers, but this is just attempting to give people some context here, this isn't a massive code base. I've not read a lot of it, so maybe it's better than the verbose code I see Claude put out sometimes.
Just a thought experiment, I very much doubt I'm the first one to think of it. It's probably in the same line of "why doesn't an LLM just write assembly directly"
I liken it to the problem of applying machine learning to hard video games (e.g. Starcraft). When trained to mimic human strategies, it can be extremely effective, but machine learning will not discover broadly effective strategies on a reasonable timescale.
If you convert "human strategies" to "human theory, programming languages, and design patterns", perhaps the point will be clear.
But: could the ouroboric cycle of LLM use decay the common strategies and design patterns we use into inexplicable blobs of assembly? Can LLMs improve at programming if humans do not advance the theory or invent new languages, patterns, etc?
My suspicion is that the "language" part of LLMs means they tend to prefer languages which are closer to human languages than assembly and benefit from much of the same abstractions and tooling (hence the recent acquisition of bun and astral).
Now whether that’s actually possible is a second topic.
This deployment is temporarily paused
https://web.archive.org/web/20260331105051/https://www.cclea...
BTW, that's why you should use your own infrastructure and not depend on Vercel
Also I definitely want a Claude Code spirit animal
(Yes, I know I can turn it off. I have.)
“Complete thyself.”
And I want an octopus. Who orchestrates octopuses.
For example the whole animation on this website, what does it say beyond that you make a request to backend and get a response that may have some tool call?
The open source models are quite close, and they'd probably be just as good with the equivalent amount of compute/data the frontier labs have access to.
However, I assume that usage data could be increasingly valuable as well. That will likely help the big commercial cloud models to maintain a head start for general use.
I use it all day and love it. Don't get me wrong. But it's a terminal-based app that talks to an LLM and calls local functions. Ooookay…
Agents in general are easy to make, and trivial to make for yourself especially, and the result will be much better than what any of the big providers can make for you.
`pi` with whatever commands/extensions you want to make for yourself is better than CC if you really don't want to go through the trouble of making your own thing.
curious as i haven't gotten around to writing my own agent yet
But you can do a lot of interesting things on top of this. I highly recommend writing an agent and hooking it up to a local model.
0 - https://github.com/zackautocracy/claude-code/blob/main/src/u...
it looks really interesting.
How is this on the front page?
- find nothing - still manage to fill entire lages - somehow have a similar structure - are boring as fuck
At least this one is 3/4, the previous one had BINGO.
In all seriousness. I think you‘re supposed to run these in some kind of sandbox.
Which emperor, specifically?