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How about releasing your own source code? It is a beautiful site, love the UX as well as functionality.

This is nice, I really like the style/tone/cadence.

The only suggestion/nit I have is that you could add some kind of asterisk or hover helper to the part when you talk about 'Anthropic's message format', as it did make me want to come here and point out how it's ackchually OpenAI's format and is very common.

Only because I figure if this was my first time learning about all this stuff I think I'd appreciate a deep dive into the format or the v1 api as one of the optional next steps.

I’m using pi and cc locally in a docker container connected to a local llama.cpp so the whole agentic loop is 100% offline.

I had used pi and cc to analyze the unpacked cc to compare their design, architecture and implementation.

I guess your site was also coded with pi and it is very impressive. Wonderful if you can do a visualization for pi vs cc as well. My local models might not be powerful enough.

Thanks for the hard work!

Is there any nice themes for pi?

Thank you for this brother, well done

Can you give me more info about your own agentic setup ?

I find it really strange that there is so much negative commentary on the _code_, but so little commentary on the core architecture.

My takeaway from looking at the tool list is that they got the fundamental architecture right - try to create a very simple and general set of tools on the client-side (e.g. read file, output rich text, etc) so that the server can innovate rapidly without revving the client (and also so that if, say, the source code leaks, none of the secret sauce does).

Overall, when I see this I think they are focused on the right issues, and I think their tool list looks pretty simple/elegant/general. I picture the server team constantly thinking - we have these client-side tools/APIs, how can we use them optimally? How can we get more out of them. That is where the secret sauce lives.

It’s not surprising. There has been quite a bit of industrial research in how to manage mere apes to be deterministic with huge software control systems, and they are an unruly bunch I assure you.

It's hard to tell how much it says about difficulty of harnessing vs how much it says about difficulty of maintaining a clean and not bloated codebase when coding with AI.

We propped the entire economy up on it. Just look at the s&p top 10. Actually even top 50 holdings.

If it doesn't deliver on the promise we have bigger problems than "oh no the code is insecure". We went from "I think this will work" to "this has to work because if it doesn't we have one of those 'you owe the bank a billion dollars' situations"

There seem to be multiple mechanisms compensating for imperfect, lossy memory. "Dreaming" is another band-aid on inability to reliably store memory without loss of precision. How lossy is this pruning process?

It's one thing to give Claude a narrow task with clear parameters, and another to watch errors or incorrect assumptions snowball as you have a more complex conversation or open-ended task.

Kinda depends how much of it is vibe coded. It could easily be 5x larger than it needs to be just because the LLM felt like it if they've not been careful.

The time is ripe for deterministic AI; incidentally, this was also released today: https://itsid.cloud/ - presumably will be useful for anyone who wants to quickly recreate an open source Python package or other copyrighted work to change its license.

> Right now, they're great for prompting simple sites/platforms but they break at large enterprise repos

Can you expand on this?

My experience is they require excessive steering but do not “break”

Indeed. In some ways, this is just kind of an extrapolation of the overall trend toward extreme bloat that we’ve seen in the past 15 years, just accelerated because LLMs code a lot faster. I’m pretty accustomed to dealing with Web application code bases that are 6-10 years old, where the hacks have piled up on top of other hacks, piled on top of early, tough-to-reverse bad decisions and assumptions, and nobody has had time to go back and do major refactors. This just seems like more of the same, except now you can create a 10 year-old hack-filled code base in three hours.

> they break at large enterprise repos.

I don't know where you get this. you should ask folks at Meta. They are probably the biggest and happiest users of CC

What do you mean by "actually governing the agents at the system level", and how is it different from "herding cats"?

I think these folks are attempting to build systems with IAM, entity states, business rules: all built over two foundational DSLs - https://typmo.com

So this is more like an art than science - and Claude Code happens to be the best at this messy art (imo).

Thousands of developers are using Claude Code successfully (I think?).

So what specifically is the gripe? If it works, it works right?

brute-forcing pattern-matching at scale. These are brittle systems with enormous duct-taping to hold everything together. workarounds on workarounds.

> A 500k line codebase for an agent CLI proves one thing: making a probabilistic LLM behave deterministically is a massive state-management nightmare.

Considering what the entire system ends up being capable of, 500k lines is about 0.001% of what I would have expected something like that to require 10 years ago.

You can combine that with all the training and inference code, and at the end of the day, a system that literally writes code ends up being smaller than the LibreOffice codebase.

It boggles the mind, really.

>A 500k line codebase for an agent CLI proves one thing: making a probabilistic LLM behave deterministically is a massive state-management nightmare. Right now, they're great for prompting simple sites/platforms but they break at large enterprise repos.

Is that the case? I'm pretty sure Claude Code is one of the most massively successful pieces of software made in the last decade. I don't know how that proves your point. Will this codebase become unmanageable eventually? Maybe, but literally every agent harness out there is just copying their lead at this point.

Who cares about LoC? Its a metric that hasn't mattered since we measured productivity in it in the 1980s. For all we know they made these design choices so they could more easily reuse the code in other codebases. Ideally you'd build the library to do that at the same time, but this is start up time constraints to repay loans and shit.

The bloat is mostly error handling for a fundamentally unpredictable system. A simple agent loop is 200 lines. But then you need graceful recovery when the model hallucinates a tool call, context window management, permission boundaries so it doesn't rm -rf your repo, state persistence across crashes, rate limiting, and cost tracking. Each one is simple individually. Together they're 500k lines.

Check out pi coding agent, https://pi.dev

> just TUIs

For starters, CC's TUI is React-based.

Opencode actually has a pretty solid codebase quality wise. I have done brief pokes and its been largely fine.

> These are just TUIs that call a model endpoint with some shell-out commands.

Claude Code CLI is actually horrible: it's a full headless browser rendering that's then converted in real-time to text to show in the terminal. And that fact leaks to the user: when the model outputs ASCII, the converter shall happily convert it to Unicode (no latter than yesterday there was a TFA complaining about Unicode characters breaking Unix pipes / parsers expecting ASCII commands).

It's ultra annoying during debugging sessions (that is not when in a full agentic loop where it YOLOs a solution): you can't easily cut/paste from the CLI because the output you get is not what the model did output.

Mega, mega, mega annoying.

What should be something simple becomes a rube-goldberg machinery that, of course, fucks up something fundamental: converting the model's characters to something else is just pathetically bad.

Anyone from Anthropic reading? Get your shit together: if you keep this "headless browser rendering converted to text", at least do not fucking modify the characters.*

I don't have a lot of experience with them but I would have thought static analysis tools circa 2020 would have managed it just fine.

How was this generated ? I'm quite sure "with ai/claude code" but what are the actual steps ?

I just checked competitors' codebases:

- Opencode (anomalyco/opencode) is about 670k LOC

- Codex (openai/codex) is about 720k LOC

- Gemini (google-gemini/gemini-cli) is about 570k LOC

Claude Code's 500k LOC doesn't seem out of the ordinary.

There’s probably a subconscious incentive to make a tool that’s “complex” because the underlying LLM also is complex.

yeah its honestly full of vibe fixes to vibe hacks with no overarching desig. . some great little empirical observations though!i think the only clever bit relative to my own designs is just tracking time since last cache ht to check ttl. idk why i hadnt thought of that, but makes perfect sense

I don't know if you're mindlessly repeating the HN trope that JS/typescript/Electron is bad and that all bloat can easily prevented, but if you're truly interested in answers to your questions: RTFA.

How many LoC should it be, for that kind of program?

Well, I assume this is all just generated with Claude Code, right? Whether there is much back and forth with the LLM is a valid question and nothing wrong with generating websites (I do it too for some side projects). Claude loves generating websites with a particular style of serif font. We also saw this with https://tboteproject.com/timeline/ and I've just generally seen it from various designs that coworkers have spit out over months using Claude defaults.

I guess I just find it weird because all the signals are messed up so whenever I see these sorts of layouts, I feel like I'm looking at the average where I don't think "gorgeous and interesting" at all. Instead, I'm forced to think "I should be skeptical of this based on the presentation because it presents as high quality but this may be hiding someone who is not actually aware of what they're presenting in any depth" as the author may have just shoved in a prompt and let it spin.

There's actually a similarly designed website (font weights, font styles etc) here in New Zealand (https://nzoilwatch.com/) where at a glance, it might seem like some overloaded professional-backed thing but instead it's just some guy who may or may not know anything about oil at all, yet people are linking it around the place like some sort of authoritative resource.

I would have way less of an issue if people just put their names by things and disclosed their LLM usage (which again, is fine) rather than giving the potentially false impression to unequipped people that the information presented is actually as accurate and trustworthy as the polish would suggest.

Claude itself can generate this in minutes if you know how to ask.

I was talking to one of the people who works at a big agentic coding tools. If I recall correctly, he was talking about how they use the tool to build the tool. I was complaining that all of the websites/frontends I make look pretty weak, and I'm amazed they get much slicker looking UIs with the same tool. He showed me that one way they do it is by having an extensive UI library of components/graphics/whatever, and also mentioned that the folks build their UIs know how to prompt/use the tool because it's backed by years of UI development knowledge & superior resources. I realized I didn't have any of that, and it actually made me feel better.

Last week we I was struggling to go from vague prompt to a OMG-it's-so-nice-looking web app, I remembered that example above and then decided to create my own component library, which I did in a couple days: https://www.substrateui.dev/. I was actually super happy that I was able to accomplish that, and then I realized I wanted to better understand the content that I had vibe coded into existence. So now I'm recreating that design system step by step w/ Claude code, filling in gaps in my knowledge & learning a bit about colors, typography, CSS, blah blah blah. It's actually a lot of fun because I'm able to explore all of the concepts and learn enough to build a front end that doesn't suck & is good enough for my use case without getting stuck for days on trying to center a stupid div by hand or play whack-mole-fix-something-and-break-something-else when trying to clean up AI slop.

Is this gorgeous?

Content resizing, needing to juggle a speed knob to read, and the overall presentation makes it feel like Edward Tufte flavored nightmare fuel.

But somehow, according to HN, LLMs make you less productive, not more :)

More like 2 hours.

.

Is this what perfection looks like?

That's where we are now, lots of us doing similar. Don't get hung up on who gets noticed, that "value" is almost zero now.

> 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.

Put yourself in their shoes; either the quality of Claude's coding continues to improve or else their business is probably doomed if it stagnates, so for them it makes sense to punt technical debt to the future when more capable versions of their models will be able to better fix it.

This is why I personally don't take technical debt arguments about how LLM maintained code bases deteriorate with size/age seriously; it presumes that at some point I'll give up with the LLM and be left with a mess to clean up by hand, but that's not going to happen, future maintenance is to be left to LLMs and if that isn't possible for some reason then the project is as good as dead anyway. When you start a project with a LLM the plan should be to see it through with LLMs, planning to have unaided humans take over maintenance at some point is a mistake.

Boris Cherny, the creator of Claude Code said he uses CC to build CC.

They explicitly boast about using claude code to write code: https://x.com/bcherny/status/2007179836704600237

That's how you get "oh this TUI API wrapper needs 68GB of RAM" https://x.com/jarredsumner/status/2026497606575398987 or "we need 16ms to lay out a few hundred characters on screen that's why it's a small game engine": https://x.com/trq212/status/2014051501786931427

I found it a useful overview. My primary question about the client source was - is there any secret sauce in it? Based on this site, the answer is no, the client is quite simple/dumb, and all the secret sauce resides on the server/in the model.

I particularly valued the tool list. People in these comments are complaining about how bad the code is, but I found the client-side tools that the model actually uses to be pretty clean/general.

My takeaway was more that at a very basic level they know what they are doing - keep the client general, so that you can innovate on the server side without revving the client as much.

It's live! If you're on the latest cc you can use /buddy now.

I need the dragon pet... someone add it to open code / pi, please!

It's available on the internet archive

https://web.archive.org/web/20260331105051/https://www.cclea...

BTW, that's why you should use your own infrastructure and not depend on Vercel

Same!

Also it's just randomly incorrect in places. For instance, it lists "fox" as one of the "Buddy" species, but that's not in the code.

When you're picking most likely tokens, you get least surprising tokens, ones with least entropy and least information per token.

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.

Really Weird but then it's so easy spot AI text by this pattern

I agree with you and I'm generally an AI "defender" when people superficially dismiss AI capabilities, but this is a more subtle point.

If you prompt with little raw material and little actual specification of what you want to see in the end, eg you just say make a detailed breakdown dashboard-like site that analyzes this codebase, the result will have this uncanny character.

I'd describe it as a kind of "fanfic", it (and now I'm not just talking about this website but my overall impression related to this phenomenon) reminds me a bit like how when I was 15 or so, I had an idea about how the world works then things turned out to be less flashy, less movie-like, less clear-cut, less-impressive-to-a-teenage-boy than I had thought.

If you know the concept of "stupid man's idea of a smart man", I'd say AI made stuff (with little iteration) gives this outward appearance of a smart man from the Reddit-midwit-cinematic-universe. It's like how guns in movies sound more like guns than real guns. It's hyperreality.

Again this is less about the capabilities of AI and it's more connected to the people-pleasing nature of it. It's like you prompt it for some epic dinner and it heaps you up some hmmm epic bacon with bacon yeah (referring to the hivemind-meme). Or BigMac on the poster vs the tray, and the poster one is a model made with different components that are more photogenic. It's a simulacrum.

It looks more like your naive currently imagined thing about what you think you need vs what you'd actually need. It's like prompting your ideal girlfriend into AI avatar existence. I'm sure she will fit your ideal thought and imagination much better but your actual life would need the actual thing.

This relates to the Persona thing that Anthropic has been exploring, that each prompt guides the model towards adopting a certain archetypal fiction character as it's persona and there are certain attraction basins that get reinforced with post training. And in the computer world, simulated action can be easily turned into real action with harnesses and tools, so I'm not saying that it doesn't accomplish the task. But it seems that there are more sloppy personas, and it seems that experts can more easily avoid summoning them by giving them context that reflects more mundane reality than a novice or an expert who gives little context. Otherwise the AI persona will be summoned from the Reddit midwit movie.

I'm not fully clear about all this, but I think we have a lot to figure out around how to use and judge the output of AI in a productive workflow. I don't think it will go away ever, but will need some trimming at the edges for sure.

If you need flashy motion graphics to explain 'returns data from API,' you probably can't justify the pixel budget or the user's time.

Projects like Beads help with memory consolidation by making it somewhat moot, since it stays "offline" and can be recollected at any moment.

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.

That’s what every agent does. They are fundamentally simple.

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.

Clever architecture often can still beat clever programming.

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.

> What is the motivation for someone to put out junk like this?

Getting something with a link to their GitHub onto the frontpage of HN. Because form matters much more in this world than substance.

Clout and reaching the top of HN apparently.

The animated explanation at the top is also way too fast at 1x, almost impossible to follow; that immediately hinted at the author not fully reading/experiencing the result before publishing this.

Why is it that some people feel entitled to take this kind of tone as soon as AI is used?

It's inappropriate to label a free side project 'junk' or 'slop' even if it contains major errors.

Particularly when there's a disclaimer about possible inaccuracies on the page.

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.

That's the hallmark of "vibe coding": optimizing for immediate output while treating the utils folder as a generic junk drawer.

I just stumbled on a fascinating replacement candidate while clicking around on embed models on hugging face: https://github.com/lightonai/next-plaid/tree/main/colgrep

it looks really interesting.

This loads some bars and then just breaks for me :(

Many people seem to believe the Claude Code has some sort of secret sauce in the agent itself for some reason.

I have no idea why because in my experience Claude Code and the same models inside of Cursor behave almost identically. I think all the secret sauce is in the RLHF.

It is vibe coded.

it's just bunch of useless junk

Are you not feeling the vibes?

In all seriousness. I think you‘re supposed to run these in some kind of sandbox.

> it just shows yet again that the emperor has no clothes

Which emperor, specifically?

What exactly is shitty here? A program i use for hours every day to do the job previously done by many N human beings, without many bugs, seems to have code thats seemingly messy but still clearly works.