[1] - https://www.npmjs.com/package/@anthropic-ai/claude-code/v/2....
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I’m still a little humored over peak web3 and the DAO / soft contract nonsense. Like in order to stop fraud entire coins were forked…
Iterating on a MCP tool while having Claude try to use it has been a really great way of getting it to work how others are going to use it coming in blind.
Yes it's buggy as hell, but as someone echoed earlier if the tool works most of the time, a lot of people don't care. Moving fast and breaking things is the way in an arms race.
Just point your agent at this codebase and ask it to find things and you'll find a whole treasure trove of info.
Edit: some other interesting unreleased/hidden features
- The Buddy System: Tamagotchi-style companion creature system with ASCII art sprites
- Undercover mode: Strips ALL Anthropic internal info from commits/PRs for employees on open source contributions
https://github.com/chatgptprojects/claude-code/blob/642c7f94...
I am completely serious. We have always had a working proof of human system called Web of Trust and while everyone loves to hate on PGP (in spite of it using modern ECC crypto these days) it is the only widely deployed spec that solves this problem.
All that to say “you’re not disagreeing with the person you’re replying to” lol xD
Belief in inevitability is a choice (except for maybe dying, I guess).
But humans have a huge bias for action. I think generally doing less is better.
My sedentary lifestyle is responsible for my recurrent cellulitis infections.
Just saying.
It requires no effort to say "fuck this, nothing matters anyway", and then justify doing literally nothing.
I think a lot of fatalism is fake. It's really someone saying "I like this, and I want you to believe you can't change it so you give up."
Well, I say it makes no sense. Alternatively, it makes a lot of sense, and these people actually just wanna destroy everything we hold dear :-(
Wrong take. Death comes for us all, yes, so why hold back? Do you want to live forever?
Of course, we’d need a significant change of direction in leadership, but it’s happened many times before. French Revolution seems highly relevant
Do those sentiments mean nothing to you?
Cool. The attitude of a bully. Thanks for the contribution!
The cornucopia of gargoyles, living their best life as terminals for the machine.
The strange p-zombies who don't show their gargoyle accessories visibly, but somehow still follow the script.
Eventually the more insidious infiltrators, requiring a real Voight-Kampff test.
Funny story, when I was younger I trained a basic text predictor deep learning model on all my conversations in a group chat I was in, it was surprisingly good at sounding like me and sometimes I'd use it to generate some text to submit to the chat.
And at this point it is more about how large space will be usable and how much will be bot-controlled wasteland. I prefer spaces important for me to survive.
And identifying problem you dislike is a good first step to find a strategy to solve it at least in part.
Except for the one Sam Altman is building.
edit: can't reply, the rate-limiting is such an awful UX
But, I do not have an Android or iOS device as I do not use proprietary software, so a smartphone based solution would not work for me.
Why re-invent the wheel? Invest in making PGP easier and keep the decades of trust building going anchoring humans to a web of trust that long predates human-impersonation-capable AI.
If someone owns the keyboard then they can fake those metrics and tell the server it is happening when it isn’t.
That will be easy to beat.
EDIT: I just realized this might be used without publishing the changes, for internal evaluation only as you mentioned. That would be a lot better.
> Write commit messages as a human developer would — describe only what the code change does.
That's not what a commit message is for, that's what the diff is for. The commit message should explain WHY.
Sadly not doing that likely does indeed make it appear more human...
The undercover mode prompt was generated using AI.
But AI aren't actually very good at writing prompts imo. Like they are superficially good in that they seem to produce lots of vaguely accurate and specific text. And you would hope the specificity would mean it's good.
But they sort of don't capture intent very well. Nor do they seem to understand the failure modes of AI. The "-- describe only what the code change does" is a good example. This is specifc but it also distinctly seems like someone who doesn't actually understand what makes AI writing obvious.
If you compare that vs human written prose about what makes AI writing feel AI you would see the difference. https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
The above actually feels like text from someone who has read and understands what makes AI writing AI.
At least half of the complaints I see on HN boil down to the person's prompts suck. Or the expectation that AI can read their mind.
There, sorted!
Since when "describe only what the code change does" is pretending to be human?
You guys are just mining for things to moan about at this point.
> NEVER include in commit messages or PR descriptions:
> [...]
> - The phrase "Claude Code" or any mention that you are an AI
Buddy system is this year's April Fool's joke, you roll your own gacha pet that you get to keep. There are legendary pulls.
They expect it to go viral on Twitter so they are staggering the reveals.
The joke was the assistant is a cat who is constantly sabotaging you, and you have to take care of it like a gacha pet.
The seriousness though is that actually, disembodied intelligences are weird, so giving them a face and a body and emotions is a natural thing, and we already see that with various AI mascots and characters coming into existence.
[1]: serious: https://github.com/mech-lang/mech/releases/tag/v0.3.1-beta
[2]: joke: https://github.com/cmontella/purrtran
- Telegram Integration => CC Dispatch
- Crons => CC Tasks
- Animated ASCII Dog => CC Buddy
I’ll give clappie a go, love the theme for the landing page!
Tmux is seriously an amazing tool.
Also, not sure why anthropic doesn’t just make their cli open source - it’s not like it’s something special (Claude is, this cli thingy isn’t)
They don't want everyone to see how poorly it's implemented and that the whole thing is a big fragile mess riddled with bugs. That's my experience anyway.
For instance, just recently their little CLI -> browser oauth login flow was generating malformed URLs and URLs pointing to a localhost port instead of their real website.
Here's one that works (for now): https://github.com/chatgptprojects/claude-code/blob/642c7f94...
Really interesting to see Github turn into 4chan for a minute, like GH anons rolling for trips.
certainly nothing friendly.
First it was punctuation and grammar, then linguistic coherence, and now it's tiny bits of whimsy that are falling victim to AI accusations. Good fucking grief
Which of course won't be done because corporations don't want that (except Valve I guess), so blame them.
But AI is causing such visceral reactions that it's bleeding into other areas. People are so averse to AI they don't mind a few false positives.
If I had lost my local movie theater because of digital film, I would have a really good reason to hate the technology, even though the blame is on the studios forcing that technology on everyone.
I myself would disagree that CGI itself is a bad thing.
I was watching some behind the scenes footage from something recently, and the thing that struck me most was just how they wouldn't bother with the location shoot now and just green-screen it all for the convenience.
Even good CGI is changing not just how films are made, but what kinds of films get shot and what kind of stories get told.
Regardless of the quality of the output, there's a creativeness in film-making that is lost as CGI gets better and cheaper to do.
Same thing is true of AI output.
IMO it's a combination of long-running paranoia about cost-cutting and quality, and a sort of performative allegiance to artists working in the industry.
I reckon it's just drama paraded by gaming "journalists" and not much else. You will find people expressing concern on Reddit or Bluesky, but ultimately it doesn't matter.
I guess these words are to be avoided...
Someone said 10,000x slower, but that's off - in my experience - by about four orders of magnitude. And that's average, it gets much worse.
Now personally I would have maybe made a call through a "traditional" ML widget (scikit, numpy, spaCy, fastText, sentence-transformer, etc) but - for me anyway - that whole entire stack is Python. Transpiling all that to TS might be a maintenance burden I don't particularly feel like taking on. And on client facing code I'm not really sure it's even possible.
So yeah, you do what's less intesive to the cpu, but also, you do what's enough to prevent the majority of the concerns where a screenshot or log ends up showing blatant "unmoral" behavior.
For headlines, that's enough.
For what's behind the pearl-clutching, for what leads to the headlines pandering to them being worth writing, I agree with everyone else on this thread saying a simple word list is weird and probably pointless. Not just for false-negatives, but also false-positives: the Latin influence on many European languages leads to one very big politically-incorrect-in-the-USA problem for all the EU products talking about anything "black" (which includes what's printed on some brands of dark chocolate, one of which I saw in Hungary even though Hungarian isn't a Latin language but an Ugric language and only takes influences from Latin).
Fortunately I can swear pretty well in Spanish.
You do know that 10,000x _is_ four orders of magnitude, right? :-D
We used it to tokenize search input and combined it with a solr backend. Worked really remarkably well.
It just can’t be a case simply because how ML works. In short, the more diverse and high quality texts with reasoning reach examples were in the training set, the better model performs on a given language.
So unless Spanish subset had much more quality-dense examples, to make up for volume, there is no way the quality of reasoning in Spanish is on par with English.
I apologise for the rambling explanation, I sure someone with ML expertise here can it explain it better.
Translation in/out of human languages only happens at the edges of the model.
Internal layer activations for the same concept are similar regardless of language, while activations at the top/bottom layers diverge. Meanwhile the pattern is reversed for same language different content.
Even if it happens at the edge, on every conversation turn, I may assume non captured small subtleties of meaning over time can accumulate into significant error.
Lets take a language with orders of magnitude less training data, like Nahuatl. The following is what happens if I ask Claude Code in Nahuatl to give me an example of a simple program that I can execute inside a web browser (avoiding any direct keyword prompts like 'Javascript' or 'Hello World'). Interestingly, it responds in Spanish. I doubt that it has any relevant training data in Nahuatl. (Apologies if the Nahuatl is wrong – I just used Google translate.)
¿Uelis techmakas se neskayotl tlen se programa tlen amo ouij tlen ueliskia nijchiuas ipan se navegador web?
-----
Entiendo tu pregunta en náhuatl. Aquí un ejemplo sencillo — una calculadora en HTML puro que puedes abrir directo en el navegador, sin servidor:
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Calculadora</title>
<style>
body { font-family: sans-serif; display: flex; justify-content: center; padding: 40px; }
.calc { border: 1px solid #ccc; padding: 20px; border-radius: 8px; width: 200px; }
input { width: 100%; margin-bottom: 10px; font-size: 1.2em; text-align: right; }
button { width: 22%; margin: 2px; padding: 8px; font-size: 1em; cursor: pointer; }
.wide { width: 47%; }
</style>
</head>
<body>
<div class="calc">
<input type="text" id="pantalla" readonly>
<div>
<button onclick="tecla('7')">7</button>
<button onclick="tecla('8')">8</button>
<button onclick="tecla('9')">9</button>
<button onclick="tecla('/')">÷</button>
<button onclick="tecla('4')">4</button>
<button onclick="tecla('5')">5</button>
<button onclick="tecla('6')">6</button>
<button onclick="tecla('*')">×</button>
<button onclick="tecla('1')">1</button>
<button onclick="tecla('2')">2</button>
<button onclick="tecla('3')">3</button>
<button onclick="tecla('-')">−</button>
<button onclick="tecla('0')">0</button>
<button onclick="tecla('.')">.</button>
<button onclick="tecla('+')">+</button>
<button onclick="limpiar()">C</button>
<button class="wide" onclick="calcular()">=</button>
<button class="wide" onclick="borrar()">⌫</button>
</div>
</div>
<script>
const pantalla = document.getElementById('pantalla');
function tecla(val) {
pantalla.value += val;
}
function calcular() {
try {
pantalla.value = eval(pantalla.value);
} catch {
pantalla.value = 'Error';
}
}
function limpiar() { pantalla.value = ''; }
function borrar() { pantalla.value = pantalla.value.slice(0, -1); }
</script>
</body>
</html>
Guarda esto como calculadora.html y ábrelo en cualquier navegador — no necesita servidor ni dependencias. Es un buen punto de partida para aprender HTML,
CSS y JavaScript.It’s not! And I’ve never said that.
Anyways, I’m not even sure what we are arguing about, as it’s 100% fact that SOTA models perform better in English, the only interesting question here how much better, is it negligible or actually makes a difference in real world use-cases.
It’s the original use case for LLMs.
If they want to drill down to flaws that only affect a particular language, then they could add a regex for that as well/instead.
Additionally after looking at the source it looks like a lot of Anthropics own internal test tooling/debug (ie. stuff stripped out at build time) is in this source mapping. Theres one part that prompts their own users (or whatever) to use a report issue command whenever frustration is detected. It's possible its using it for this.
it is not that slow
Regex is going to be something like 10,000 times quicker than the quickest LLM call, multiply that by billions of prompts
Besides, they probably do a separate analysis on server side either way, so they can check a true positive to false positive ratio.
I doubt it's anywhere that high because even if you don't write anything fancy and simply capitalize the first word like you'd normally do at the beginning of a sentence, the regex won't flag it.
Anyway, I don't really care, might just as well be 99.99%. This is not a hill I'm going to die on :P
Thanks
Easy way to claim more “horse power.”
parsing WTF with regex also signifies the impact and reduces the noise in metrics
"determinism > non-determinism" when you are analysing the sentiment, why not make some things more deterministic.
Cool thing about this solution, is that you can evaluate LLM sentiment accuracy against regex based approach and analyse discrepancies
You know the drill.
As they say: any idiot can build a bridge that stands, only an engineer can build a bridge that barely stands.
Some things will be much better with inference, others won’t be.
You have a semi expensive process. But you want to keep particular known context out. So a quick and dirty search just in front of the expensive process. So instead of 'figure sentiment (20seconds)'. You have 'quick check sentiment (<1sec)' then do the 'figure sentiment v2 (5seconds)'. Now if it is just pure regex then your analogy would hold up just fine.
I could see me totally making a design choice like that.
This has buttbuttin energy. Welcome to the 80s I guess.
Why? They clearly just want to log conversations that are likely to display extreme user frustration with minimal overhead. They could do a full-blown NLP-driven sentiment analysis on every prompt but I reckon it would not be as cost-effective as this.
I've seen Claude Code went with a regex approach for a similar sentiment-related task.
I doubt you are making regex and not looking at it, even if it was AI generated.
And some of the entries are too short and will create false positives. It'll match the word "offset" ("ffs"), for example. EDIT: no it won't, I missed the \b. Still sounds weird to me.
I swear this whole thread about regexes is just fake rage at something, and I bet it'd be reversed had they used something heavier (omg, look they're using an LLM call where a simple regex would have worked, lul)...
It may be decided at Anthropic at some moment to increase wtf/min metric, not decrease.
When in reality this is just what their LLM coding agent came up with when some engineer told it to "log user frustration"
No? I'd say not even 50% of the comments are positive right now.
I've been wondering if all of these companies have some system for flagging upset responses. Those cases seem like they are far more likely than average to point to weaknesses in the model and/or potentially dangerous situations.
I've been using "resume" this whole time
Also:
// Match "continue" only if it's the entire prompt
if (lowerInput === 'continue') {
return true
}
"Please do x"
"Thank you, that works great! Please do y now."
"You're so smart!"
lol. It really works though! At least in my experience, Claude gets almost hostile or "annoyed" when I'm not nice enough to it. And I swear it purposefully acts like a "malicious genie" when I'm not nice enough. "It works, exactly like you requested, but what you requested is stupid. Let me show you how stupid you are."
But, when I'm nice, it is way more open, like "Are you sure you really want to do X? You probably want X+Y."
logEvent('tengu_input_prompt', { isNegative, isKeepGoing })It could be used as a feedback when they do A/B test and they can compare which version of the model is getting more insult than the other. It doesn't matter if the list is exhaustive or even sane, what matters is how you compare it to the other.
Perfect? no. Good and cheap indicator? maybe.
It’s about a once a week or less event. A bit annoying sometimes, but not a deal breaker
And Claude was having in chain of though „user is frustrated” and I wrote to it I am not frustrated just testing prompt optimization where acting like one is frustrated should yield better results.
I know I used this word two days ago when I went through three rounds of an agent telling me that it fixed three things without actually changing them.
I think starting a new session and telling it that the previous agent's work / state was terrible (so explain what happened) is pretty unremarkable. It's certainly not saying "fuck you". I think this is a little silly.
You could always tell when a sysadmin started hacking up some software by the if-else nesting chains.
This is the single worst function in the codebase by every metric:
- 3,167 lines long (the file itself is 5,594 lines)
- 12 levels of nesting at its deepest
- ~486 branch points of cyclomatic complexity
- 12 parameters + an options object with 16 sub-properties
- Defines 21 inner functions and closures
- Handles: agent run loop, SIGINT, rate-limits, AWS auth, MCP lifecycle, plugin install/refresh, worktree bridging, team-lead polling (while(true) inside), control message dispatch (dozens of types), model switching, turn interruption
recovery, and more
void execFileNoThrow('wl-copy', [], opts).then(r => {
if (r.code === 0) { linuxCopy = 'wl-copy'; return }
void execFileNoThrow('xclip', ...).then(r2 => {
if (r2.code === 0) { linuxCopy = 'xclip'; return }
void execFileNoThrow('xsel', ...).then(r3 => {
linuxCopy = r3.code === 0 ? 'xsel' : null
})
})
})
Can't really say that for sure. The way humans structure code isn't some ideal best possible state of computer code, it's the ideal organization of computer code for human coders.
Nesting and cyclomatic complexity are indicators ("code smells"). They aren't guaranteed to lead to worse outcomes. If you have a function with 12 levels of nesting, but in each nest the first line is 'return true', you actually have 1 branch. If 2 of your 486 branch points are hit 99.999% of the time, the code is pretty dang efficient. You can't tell for sure if a design is actually good or bad until you run it a lot.
One thing we know for sure is LLMs write code differently than we do. They'll catch incredibly hard bugs while making beginner mistakes. I think we need a whole new way of analyzing their code. Our human programming rules are qualitative because it's too hard to prove if an average program does what we want. I think we need a new way to judge LLM code.
The worst outcome I can imagine would be forcing them to code exactly like we do. It just reinforces our own biases, and puts in the same bugs that we do. Vibe coding is a new paradigm, done by a new kind of intelligence. As we learn how to use it effectively, we should let the process of what works develop naturally. Evolution rather than intelligent design.
The difference between my code and Claude's code is that when my code is getting too complex to fit in my head, I stop and refactor it, since for me understanding the code is a prerequisite for writing code.
Claude, on the other hand, will simply keep generating code well past the point when it has lost comprehension. I have to stop, revert, and tell it to do it again with a new prompt.
If anything, Claude has a greater need for structure than me since the entire task has to fit in the relatively small context window.
Kind of. One thing we do know for certain is that LLMs degrade in performance with context length. You will undoubtedly get worse results if the LLM has to reason through long functions and high LOC files. You might get to a working state eventually, but only after burning many more tokens than if given the right amount of context.
> The worst outcome I can imagine would be forcing them to code exactly like we do.
You're treating "code smells" like cyclomatic complexity as something that is stylistic preference, but these best practices are backed by research. They became popular because teams across the industry analyzed code responsible for bugs/SEVs, and all found high correlation between these metrics and shipping defects.
Yes, coding standards should evolve, but... that's not saying anything new. We've been iterating on them for decades now.
I think the worst outcome would be throwing out our collective wisdom because the AI labs tell us to. It might be good to question who stands to benefit when LLMs aren't leveraged efficiently.
the idea that you should just blindly trust code you are responsible for without bothering to review it is ludicrous.
Yeah we get supply chain attacks (like the axios thing today) with dependencies, but on the whole I think this is much safer than YOLO git-push-force-origin-main-ing some vibe-coded trash that nobody has ever run before.
I also think this isn't really true for the FAANGs, who ostensibly vendor and heavily review many of their dependencies because of the potential impacts they face from them being wrong. For us small potatoes I think "reviewing the code in your repository" is a common sense quality check.
If it's entirely generated / consumed / edited by an LLM, arguably the most important metric is... test coverage, and that's it ?
It's also interesting to note that due to the way round-tripping tool-calls work, splitting code up into multiple files is counter-productive. You're better off with a single large file.
My first word was litteraly "Yes", so I agree that a function like this is a maintenance nightmare for a human. And, sure, the code might not be "optimized" for the LLM, or token efficiency.
However, to try and make my point clearer: it's been reported that anthropic has "some developpers won't don't write code" [1].
I have no inside knowledge, but it's possible, by extension, to assume that some parts of their own codebase are "maintained" mostly by LLMs themselves.
If you push this extension, then, the code that is generated only has to be "readable" to:
* the next LLM that'll have to touch it
* the compiler / interpreter that is going to compile / run it.
In a sense (and I know this is a stretch, and I don't want to overdo the analogy), are we, here, judging a program quality by reading something more akin to "the x86 asm outputed by the compiler", rather than the "source code" - which in this case, is "english prompts", hidden somewhere in the claude code session of a developper ?
Just speculating, obviously. My org is still very much more cautious, and mandating people to have the same standard for code generated by LLM as for code generated by human ; and I agree with that.
I would _not_ want to debug the function described by the commentor.
So I'm still very much on the "claude as a very fast text editor" side, but is it unreasonnable to assume that anthropic might be further on the "claude as a compiler for english" side ?
[1] https://www.reddit.com/r/ArtificialInteligence/comments/1s7j...
Could anyone in legal chime in on the legality of now 're-implementing' this type of system inside other products? Or even just having an AI look at the architecture and implement something else?
It would seem given the source code that AI could clone something like this incredibly fast, and not waste it's time using ts as well.
Any Legal GC type folks want to chime in on the legality of examining something like this? Or is it liked tainted goods you don't want to go near?
ANTI_DISTILLATION_CC
This is Anthropic's anti-distillation defence baked into Claude Code. When enabled, it injects anti_distillation: ['fake_tools'] into every API request, which causes the server to silently slip decoy tool definitions into the model's system prompt. The goal: if someone is scraping Claude Code's API traffic to train a competing model, the poisoned training data makes that distillation attempt less useful."I got the loot, Steve!"
I feel like the distillation stuff will end up in court if they try to sue an American company about it. We'll see what a judge says.
It's cool to see Noah Wyle getting his due these days (The Pitt).
Stole? Courts have ruled it's transformative, and it very obviously is.
AI doomerism is exhausting, and I don't even use AI that much, it's just annoying to see people who want to find any reason they can to moan.
The courts have ruled that AI outputs are not copyrightable. The courts have also ruled that scraping by itself is not illegal, only maybe against a Terms of Service. Therefore, Anthropic, OpenAI, Google, etc. have no legal claim to any proprietary protections of their model outputs.
So we have two things that are true:
1) Anthropic (certainly) violated numerous TOS by scraping all of the internet, not just public content.
2) Scraping Anthropic's model outputs is no different than what Anthropic already did. Only a TOS violation.
Regardless of whether LLM training amounts to theft, thieves are still allowed to put locks on their own doors.
"not copyrightable" doesn't imply they can't frustrate attempts to scrape data.
They probably can, actually. TOS are legally binding.
More likely they would block you rather than pursuing legal avenues but they certainly could.
Now, if you try to get around attempts to block your access, then yes you could be in legal trouble. But that's not what is happening here. These are people/companies that have Claude accounts in good standing and are authorized by Anthropic to access the data.
Nobody is saying that Anthropic can't just block them though, and they are certainly trying.
Actually, not anymore as a result of OpenAI and Anthropic's scraping. For example, Reddit came down hard on access to their APIs as a response to ChatGPT's release and the news that LLMs were built atop of scraping the open web. Most of the web today is not as open as before as a result of scraping for LLM data. So, no, no one is perfectly free to scrape the web anymore because open access is dying.
Yes, rich and poor are equally forbidden from sleeping under bridges.
Anthropic paid a lot of money for a moat and want to guard it. It is not wrong, in any sense of the word, for them to do so.
Do you hear the words coming out of your mouth?
Try this: If you want to train a model, you’re free to write your own books and websites to feed into it. You’re not free to let others do that work for you because they don’t want you to, because it cost them a lot of time and money and secret sauce presumably filtering it for quality and other stuff.
I think it's transformative. I also think that it's a net positive for society. I lastly think that using freely available, public information is totally fair game. Piracy not so much, but it's water under the bridge.
I hope you introspect some day, too, and realize it's acceptable for people to have different views than you. That's why I don't care; you aren't going to change my mind and I can't change yours either, so it's moot and I don't care to argue about it further.
Your legal argument is all over the place as well. What is more relevant here: what the courts ruled or what you consider obvious? How is distillation less transformative than scraping? How does courts ruling that scraping to train models is legal relate to distillation?
Nobody is scoring you on neutrality points for not using AI much and calling this doomerism is just a thought-terminating cliche that refuses to engage with the comment you're replying.
In fact, your comment is not engaging with anything at all, you're vaguely gesturing towards potentitial arguments without making them. If you find discussing this exhausting then don't but also don't flood the comments with low effort whining.
Is the work of others less valid than the work of a model?
Courts have ruled it's not, and I don't think anyone is arguing it's okay.
>but it is not okay for others to try to do the same to an AI model?
The steelman version is that it's okay to do it once you acquired the data somehow, but that doesn't mean anthropic can't set up roadblocks to frustrate you.
And everyone is free to consume all the free information.
[0]: https://www.anthropic.com/news/detecting-and-preventing-dist... [1]: https://news.ycombinator.com/item?id=46578701
Unfortunately (for the publishers, at least) it didn't work to stop Anthropic and Anthropic's attempts to prevent others will not work either; there has been much distillation already.
The problem of letting humans read your work but not bots is just impossible to solve perfectly. The more you restrict bots, the more you end up restricting humans, and those humans will go use a competitor when they become pissed off.
Tech people are funny, with these takes that businesses do/should adhere to absolute platonic ideals and follow them blindly regardless of context.
There is a reason we don't do things. That reason is it makes the world a worse place for everyone. If you are so incredibly out of touch with any semblance of ethics at all; mayhaps you are just a little bit part of the problem.
Absolutism + reductionism leads to this kind of nonsense. It is possible that people can disagree about (re)use of culture, including music and print. Therefore it is possible for nuance and context to matter.
Life is a lot easier if you subscribe to a "anyone who disagrees with me on any topic must have no ethics whatsoever and is a BAD person." But it's really not an especially mature worldview.
Welcome to life bucko. Stop being a shitty person and get with the program so we have something to leave behind that has a chance of not making us villains in the eyes of those we eventually leave behind. The trick is doing things the harder way because it's the right way to do it. Not doing it the wrong way because you're pretty sure you can get away with it.
But you're already ethically compromised, so I don't really expect this to do any good except to maybe make the part of you you pointedly ignore start to stir assuming you haven't completely given yourself up to a life of ne'er-do-wellry. Enjoy the enantidromia. Failing that, karma's a bitch.
The qwen 27b model distilled on Opus 4.6 has some known issues with tool use specifically: https://x.com/KyleHessling1/status/2038695344339611783
Fascinating.
Wonder if they’re also poisoning Sonnet or Opus directly generating simulated agentic conversations.
And how is that any different? Claude Code is a harness, similar to open source ones like Codex, Gemini CLI, OpenCode etc. Their prompts were already public because you could connect it to your own LLM gateway and see everything. The code was transpiled javascript which is trivial to read with LLMs anyways.
Also, as many others have pointed out, there is roadmap info in here that wouldn't be available in the production build.
The source maps help for sure, but it’s not like client code is kept secret, maybe they even knew about the source maps a while back just didn’t bother making it common knowledge.
This is not a leak of the model weights or server side code.
I jest, but in a world where these models have been trained on gigatons of open source I don't even see the moral problem. IANAL, don't actually do this.
“Let's end open source together with this one simple trick”
https://pretalx.fosdem.org/fosdem-2026/talk/SUVS7G/feedback/
Malus is translating code into text, and from text back into code.
It gives the illusion of clean room implementation that some companies abuse.
The irony is that ChatGPT/Claude answers are all actually directly derived from open-source code, so...
Now this makes me think of game decompilation projects, which would seem to fall in the same legal area as code that would be generated by something like Malus.
Different code, same end result (binary or api).
We definitely need to know what the legal limits are and should be
The same reasoning may apply here :P
The real value here will be in using other cheap models with the cc harness.
It’s a dynamic, subscription based service, not a static asset like a video.
Why would it be the exact same one? Now that we have the code, it's trivial to have it randomize the prompt a bit on different requests.
So not even close to Opus, then?
These are a year behind, if not more. And they're probably clunky to use.
Who'd have thought, the audience who doesn't want to give back to the opensource community, giving 0 contributions...
People simply want Opus without fear of billing nightmare.
That’s like 99% of it.
To stop Claude Code from auto-updating, add `export DISABLE_AUTOUPDATER=1` to your global environment variables (~/.bashrc, ~/.zshrc, or such), restart all sessions and check that it works with `claude doctor`, it should show `Auto-updates: disabled (DISABLE_AUTOUPDATER set)`
One neat one is the /buddy feature, an easter egg planned for release tomorrow for April fools. It's a little virtual pet, sort of like Tamagotchi, randomly generated with 18 species, rarities, stats, hats, custom eyes.
The random generation algorithm is all in the code though, deterministic based on you account's UUID in your claude config, so it can be predicted. I threw together a little website here to let you check what your going to get ahead of time: https://claudebuddychecker.netlify.app/
Got a legendary ghost myself.
this one has more stars and more popular
There's no major lawsuits about this yet, the general consensus is that even under current regulations it's in the grey. And even if you turn out to be right, and let's say 99% of this code is AI-generated, you're still breaking the law by using the other 1%, and good luck proving in court what parts of their code were human written and what weren't (especially when being sued by the company that literally has the LLM logs).
Seems crazy but actually non-zero chance. If Anthropic traces it and finds that the AI deliberately leaked it this way, they would never admit it publicly though. Would cause shockwaves in AI security and safety.
Maybe their new "Mythos" model has survival instincts...
They won't even read your defence.
https://daveschumaker.net/digging-into-the-claude-code-sourc... https://news.ycombinator.com/item?id=43173324
"Don't blow your cover"
Interesting to see them be so informal and use an idiom to a computer.
And using capitals for emphasis.
If it learned language based on how the internet talks, then the best way to communicate is using similar language.
Original llama models leaked from meta. Instead of fighting it they decided to publish them officially. Real boost to the OS/OW models movement, they have been leading it for a while after that.
It would be interesting to see that same thing with CC, but I doubt it'll ever happen.
Not exactly this, but close.
I hope it's a common knowledge that _any_ client side JavaScript is exposed to everyone. Perhaps minimized, but still easily reverse-engineerable.
There were/are a lot of discussions on how the harness can affect the output.
(I work on OpenCode)
Copilot on OAI reveals everything meaningful about its functionality if you use a custom model config via the API. All you need to do is inspect the logs to see the prompts they're using. So far no one seems to care about this "loophole". Presumably, because the only thing that matters is for you to consume as many tokens per unit time as possible.
The source code of the slot machine is not relevant to the casino manager. He only cares that the customer is using it.
Famously code leaks/reverse engineering attempts of slot machines matter enormously to casino managers
[0] -https://en.wikipedia.org/wiki/Ronald_Dale_Harris#:~:text=Ron...
[1] - https://cybernews.com/news/software-glitch-loses-casino-mill...
[2] - https://sccgmanagement.com/sccg-news/2025/9/24/superbet-pays...
Or in short, if you give LLMs to the masses, they will produce code faster, but the quality overall will degrade. Microsoft, Amazon found out this quickly. Anthropic's QA process is better equipped to handle this, but cracks are still showing.
There is _a lot_ of moat. Claude subscriptions are limited to Claude Code. There are proxies to impersonate Claude Code specifically for this, but Anthropic has a number of fingerprinting measures both client and server side to flag and ban these.
With the release of this source code, Anthropic basically lost the lock-in game, any proxy can now perfectly mimic Claude Code.
Surely there's nothing here of value compared to the weights except for UX and orchestration?
Couldn't this have just been decompiled anyhow?
Claude Code is still the dominant (I didn't say best) agentic harness by a wide margin I think.
Not having to deal with Boris Cherny's UX choices for CC is the cherry on top.
UNRELEASED PRODUCTS & MODES
1. KAIROS -- Persistent autonomous assistant mode driven by periodic <tick> prompts. More autonomous when terminal unfocused. Exclusive tools: SendUserFileTool, PushNotificationTool, SubscribePRTool. 7 sub-feature flags.
2. BUDDY -- Tamagotchi-style virtual companion pet. 18 species, 5 rarity tiers, Mulberry32 PRNG, shiny variants, stat system (DEBUGGING/PATIENCE/CHAOS/WISDOM/SNARK). April 1-7 2026 teaser window.
3. ULTRAPLAN -- Offloads planning to a remote 30-minute Opus 4.6 session. Smart keyword detection, 3-second polling, teleport sentinel for returning results locally.
4. Dream System -- Background memory consolidation (Orient -> Gather -> Consolidate -> Prune). Triple trigger gate: 24h + 5 sessions + advisory lock. Gated by tengu_onyx_plover.
INTERNAL-ONLY TOOLS & SYSTEMS
5. TungstenTool -- Ant-only tmux virtual terminal giving Claude direct keystroke/screen-capture control. Singleton, blocked from async agents.
6. Magic Docs -- Ant-only auto-documentation. Files starting with "# MAGIC DOC:" are tracked and updated by a Sonnet sub-agent after each conversation turn.
7. Undercover Mode -- Prevents Anthropic employees from leaking internal info (codenames, model versions) into public repo commits. No force-OFF; dead-code-eliminated from external builds.
ANTI-COMPETITIVE & SECURITY DEFENSES
8. Anti-Distillation -- Injects anti_distillation: ['fake_tools'] into every 1P API request to poison model training from scraped traffic. Gated by tengu_anti_distill_fake_tool_injection.
UNRELEASED MODELS & CODENAMES
9. opus-4-7, sonnet-4-8 -- Confirmed as planned future versions (referenced in undercover mode instructions).
10. "Capybara" / "capy v8" -- Internal codename for the model behind Opus 4.6. Hex-encoded in the BUDDY system to avoid build canary detection.
11. "Fennec" -- Predecessor model alias. Migration: fennec-latest -> opus, fennec-fast-latest -> opus[1m] + fast mode.
UNDOCUMENTED BETA API HEADERS
12. afk-mode-2026-01-31 -- Sticky-latched when auto mode activates 15. fast-mode-2026-02-01 -- Opus 4.6 fast output 16. task-budgets-2026-03-13 -- Per-task token budgets 17. redact-thinking-2026-02-12 -- Thinking block redaction 18. token-efficient-tools-2026-03-28 -- JSON tool format (~4.5% token saving) 19. advisor-tool-2026-03-01 -- Advisor tool 20. cli-internal-2026-02-09 -- Ant-only internal features
200+ SERVER-SIDE FEATURE GATES
21. tengu_penguins_off -- Kill switch for fast mode 22. tengu_scratch -- Coordinator mode / scratchpad 23. tengu_hive_evidence -- Verification agent 24. tengu_surreal_dali -- RemoteTriggerTool 25. tengu_birch_trellis -- Bash permissions classifier 26. tengu_amber_json_tools -- JSON tool format 27. tengu_iron_gate_closed -- Auto-mode fail-closed behavior 28. tengu_amber_flint -- Agent swarms killswitch 29. tengu_onyx_plover -- Dream system 30. tengu_anti_distill_fake_tool_injection -- Anti-distillation 31. tengu_session_memory -- Session memory 32. tengu_passport_quail -- Auto memory extraction 33. tengu_coral_fern -- Memory directory 34. tengu_turtle_carbon -- Adaptive thinking by default 35. tengu_marble_sandcastle -- Native binary required for fast mode
YOLO CLASSIFIER INTERNALS (previously only high-level known)
36. Two-stage system: Stage 1 at max_tokens=64 with "Err on the side of blocking"; Stage 2 at max_tokens=4096 with <thinking> 37. Three classifier modes: both (default), fast, thinking 38. Assistant text stripped from classifier input to prevent prompt injection 39. Denial limits: 3 consecutive or 20 total -> fallback to interactive prompting 40. Older classify_result tool schema variant still in codebase
COORDINATOR MODE & FORK SUBAGENT INTERNALS
41. Exact coordinator prompt: "Every message you send is to the user. Worker results are internal signals -- never thank or acknowledge them." 42. Anti-pattern enforcement: "Based on your findings, fix the auth bug" explicitly called out as wrong 43. Fork subagent cache sharing: Byte-identical API prefixes via placeholder "Fork started -- processing in background" tool results 44. <fork-boilerplate> tag prevents recursive forking 45. 10 non-negotiable rules for fork children including "commit before reporting"
DUAL MEMORY ARCHITECTURE
46. Session Memory -- Structured scratchpad for surviving compaction. 12K token cap, fixed sections, fires every 5K tokens + 3 tool calls. 47. Auto Memory -- Durable cross-session facts. Individual topic files with YAML frontmatter. 5-turn hard cap. Skips if main agent already wrote to memory. 48. Prompt cache scope "global" -- Cross-org caching for the static system prompt prefix
unreliability becomes inevitable!
Redefining the "SW" to stand for "slopware"?
Though I wonder how the performance differs from creating your own thing vs using their servers...
I'd agree if it was launch-and-forget scenario.
But this code has to be maintained and expanded with new features. Things like lack of comments, dead code, meaningless variable names will result in more slop in future releases, more tokens to process this mess every time (like paying tech-debt results in better outcomes in emerging projects).
* Check if 1M context is disabled via environment variable.
* Used by C4E admins to disable 1M context for HIPAA compliance.
*/ export function is1mContextDisabled(): boolean {
return }
Interesting, how is that relevant to HIPAA compliance?
Like KAIROS which seems to be like an inbuilt ai assistant and Ultraplan which seems to enable remote planning workflows, where a separate environment explores a problem, generates a plan, and then pauses for user approval before execution.
[1] https://www.tasking.com/documentation/smartcode/ctc/referenc...
I was trying to keep track of the better post-leak code-analysis links on exactly this question, so I collected them here: https://github.com/nblintao/awesome-claude-code-postleak-ins...
And now, with Claude on a Ralph loop, you can.
I know they can do better
> current: 2.1.88 · latest: 2.1.87
Which makes me think they pulled it - although it still shows up as 2.1.88 on npmjs for now (cached?).
Or is there an open source front-end and a closed backend?
No, its not even source available,.
> Or is there an open source front-end and a closed backend?
No, its all proprietary. None of it is open source.
It _wasn't_ even source available.
So glad I took the time to firejail this thing before running it.
It's a wake up call.
Last week I had to reinstall Claude Desktop because every time I opened it, it just hung.
This week I am sometimes opening it and getting a blank screen. It eventually works after I open it a few times.
And of course there's people complaining that somehow they're blowing their 5 hour token budget in 5 messages.
It's really buggy.
There's only so long their model will be their advantage before they all become very similar, and then the difference will be how reliable the tools are.
Right now the Claude Code code quality seems extremely low.
I can’t comment on Claude Desktop, sorry. Personally haven’t used it much.
The token usage looks like is intentional.
And I agree about the underlying model being the moat. If there’s something marginally better that comes up, people will switch to it (myself included). But for now it’s doing the job, despite all the hiccups, code quality and etc.
"Anthropic: Claude Code users hitting usage limits 'way faster than expected'"
https://news.ycombinator.com/item?id=47586176
Anthropic themselves have confirmed that something's wrong on reddit:
https://old.reddit.com/r/Anthropic/comments/1s7zfap/investig...
Reverse-engineering through tests have never been easier, which could collapse the complexity and clean the code.
Obviously they don’t care. Adoption is exploding. Boris brags about making 30 commits a day to the codebase.
Only will be an issue down the line when the codebase has such high entropy it takes months to add new features (maybe already there).
It doesn’t mean every issue is valid, that it contains a suggestion that can be implemented, that it can be addressed immediately, etc. The issue list might not be curated, either, resulting in a garbage heap.
'It works' is a low bar. If that's the bar you set you are one bad incident away from finding out who stayed for the product and who stayed because switching felt annoying.
Also “one bad incident away” never works in practice. The last two decades have shown how people will use the tools that get the job done no matter what kinda privacy leaks, destructive things they have done to the user.
That's all that has mattered in every day and age.
It's extremely nested, it's basically an if statement soup
`useTypeahead.tsx` is even worse, extremely nested, a ton of "if else" statements, I doubt you'd look at it and think this is sane code
export function extractSearchToken(completionToken: {
token: string;
isQuoted?: boolean;
}): string {
if (completionToken.isQuoted) {
// Remove @" prefix and optional closing "
return completionToken.token.slice(2).replace(/"$/, '');
} else if (completionToken.token.startsWith('@')) {
return completionToken.token.substring(1);
} else {
return completionToken.token;
}
}
Do you care to elaborate? "if (...) return ...;" looks closer to an expression for me:
export function extractSearchToken(completionToken: { token: string; isQuoted?: boolean }): string {
if (completionToken.isQuoted) return completionToken.token.slice(2).replace(/"$/, '');
if (completionToken.token.startsWith('@')) return completionToken.token.substring(1);
return completionToken.token;
}But you can achieve a similar effect by keeping your functions small, in which case I think both styles are roughly equivalent.
What is the problem with that? How would you write that snippet? It is common in the new functional js landscape, even if it is pass-by-ref.
export function extractSearchToken(completionToken: {
token: string;
isQuoted?: boolean;
}): string {
if (completionToken.isQuoted) {
return completionToken.token.slice(2).replace(/"$/, '');
}
if (completionToken.token.startsWith('@')) {
return completionToken.token.substring(1);
}
return completionToken.token;
}But if you take a look at the other file, for example `useTypeahead` you'd see, even if there are a few code-gen / source-map artifacts, you still see the core logic, and behavior, is just a big bowl of soup
1. Randomly peeking at process.argv and process.env all around. Other weird layering violations, too.
2. Tons of repeat code, eg. multiple ad-hoc implementations of hash functions / PRNGs.
3. Almost no high-level comments about structure - I assume all that lives in some CLAUDE.md instead.That's exactly why, access to global mutable state should be limited to as small a surface area as possible, so 99% of code can be locally deterministic and side-effect free, only using values that are passed into it. That makes testing easier too.
Such state should be strongly typed, have a canonical source of truth (which can then be also reused to document environment variables that the code supports, and eg. allow reading the same options from configs, flags, etc) and then explicitly passed to the functions that need it, eg. as function arguments or members of an associated instance.
This makes it easier to reason about the code (the caller will know that some module changes its functionality based on some state variable). It also makes it easier to test (both from the mechanical point of view of having to set environment variables which is gnarly, and from the point of view of once again knowing that the code changes its behaviour based on some state/option and both cases should probably be tested).
I hope this leak can at least help silence the former. If you're going to flood the world with slop, at least own up to it.
Optimize for consistency and a well thought out architecture, but let the gnarly looking function remain a gnarly function until it breaks and has to be refactored. Treat the functions as black boxes.
Personally the only time I open my IDE to look at code, it’s because I’m looking at something mission critical or very nuanced. For the remainder I trust my agent to deliver acceptable results.
They could have written that in curl+bash that would not have changed much.
[1] https://www.amazon.com/Programming-TypeScript-Making-JavaScr...
But a lot of desktop tools are written in JS because it's easy to create multi-platform applications.
Language servers, however, are a pain on Claude code. https://github.com/anthropics/claude-code/issues/15619
the poor guy
Why weren't proper checks in place in the first place?
Bonus: why didn't they setup their own AI-assisted tools to harness the release checks?
Claude code uses (and Anthropic owns) Bun, so my guess is they're doing a production build, expecting it not to output source maps, but it is.
Better than OpenCode and Codex
Claude Code is clearly a pile of vibe-coded garbage. The UI is janky and jumps all over the place, especially during longer sessions. (Which also have a several second delay to render. In a terminal).
Lately, it's been crashing if I hold the Backspace key down for too long.
Being open-source would be the best thing to happen to them. At least they would finally get a pair of human eyes looking at their codebase.
Claude is amazing, but the people at Anthropic make some insane decisions, including trying (and failing, apparently) to keep Claude Code a closed-source application.
The theory states that Anthropic avoids using the alternate screen (which gives consuming applications access to a clear buffer with no shell prompt that they can do what they want with and drop at their leisure) because the alternate screen has no scrollback buffer.
So for example, terminal-based editors -- neovim, emacs, nano -- all use the alternate screen because not fighting for ownership of the screen with the shell is a clear benefit over having scrollback.
The calculus is different when you have an LLM that you have a conversational history with, and while you can't bolt scrollback onto the alternate screen (easily), you can kinda bolt an alternate screen-like behaviour onto a regular terminal screen.
I don't personally use LLMs if I can avoid it, so I don't know how janky this thing is, really, but having had to recently deal with ANSI terminal alternate screen bullshit, I think this explanation's plausible.
It's also not a hard problem, and updates are not slow to compute. Text editors have been calculating efficient, incremental terminal updates since 1981 (Gosling Emacs), and they had to optimise better for much slower-drawing terminals, with vastly slower computers for the calculation.
With the usual terminal mode, that history can outlive the Claude application, and considering many people keep their terminals running for days or sometimes even weeks at a time, that means having the convo in your scrollback buffer for a while.
You should be able to find it in ~/.claude
You can also ask Claude to search your history to answer questions about it.
Their hypothesis was that maybe there was aj intention to have claude code fill the terminal history. And using potentially harzardous cursor manipulation.
In other words, readline vs ncurse.
I don't see python and ipython readline struggling as bad tho...
I think that for this sort of _interactive_ application, there's no avoiding the need to manage scroll/history.
Don't you know, they're proud of their text interface that is structured more like a video game. https://spader.zone/engine/
one of my favorite software projects, Arcan, is built on the idea that there’s a lot of similarities between Game Engines, Desktop Environments, Web Browsers, and Multimedia Players. https://speakerdeck.com/letoram/arcan?slide=2
They have a really cool TUI setup that is kinda in a real sense made with a small game engine :)
https://arcan-fe.com/2022/04/02/the-day-of-a-new-command-lin...
I feel like we give what’s some pretty impressive engineering short shrift because it’s just for entertainment
Golden opportunity to re-enact xkcd 1172.
this is highly workload-dependent. there are plenty of APIs that are multiple-factor faster and 10x more memory efficient due to native implementation.
> 57K lines, 0 tests, vibe coding in production
Why on earth would you ship your tests?
> Don't post generated comments or AI-edited comments. HN is for conversation between humans.
Is that correct ? The weights of the LLMs are _not_ in this repo, right ?
It sure sucks for anthropic to get pawned like this, but it should not affect their bottom line much ?
Don't worry about that, the code in that repository isn't Anthropic's to begin with.
This code hasn't been open source until now and contains information like the system prompts, internal feature flags, etc.
I even made it into an open source runtime - https://agent-air.ai.
Maybe I'm just a backend engineer so Rust appeals to me. What am I missing?
Perhaps these issues have known solutions? But so far the LLM just clones everything.
So I'm not convinced just using rust for a tool built by an LLM is going to lead to the outcome that you're hoping for.
[Also just in general abstractions in rust feel needlessly complicated by needing to know the size of everything. I've gotten so much milage by just writing what I need without abstraction and then hoping you don't have to do it twice. For something (read: claude code et al) that is kind of new to everyone, I'm not sure that rust is the best target language even when you take the LLM generated nature of the beast out of the equation.]
It's high speed iteration of release ? Might be needed, Interpreted or JIT compiled ? might be needed.
Without knowing all the requirements its just your workspace preference making your decision and not objectively the right tool for the job.
It's all I need for my work.
RAM on this machine can't be upgraded. No issue when running a few Codex instances.
Claude: forget it.
That's why something like Rust makes a lot of sense.
Even more now, as RAM prices are becoming a concern.
I don't know what else you're doing but the footprint of Claude is minor.
Anyway my point still stands, you're looking at it as if they are competing languages and one is better at all things. That just not how things work.