There are now several comments that (incorrectly?) interpret the undercover mode as only hiding internal information. Excerpts from the actual prompt[0]:
NEVER include in commit messages or PR descriptions:
- The phrase "Claude Code" or any mention that you are an AI
- Co-Authored-By lines or any other attribution
BAD (never write these):
- 1-shotted by claude-opus-4-6
- Generated with Claude Code
- Co-Authored-By: Claude Opus 4.6 <…>
This very much sounds like it does what it says on the tin, i.e. stays undercover and pretends to be a human. It's especially worrying that the prompt is explicitly written for contributions to public repositories.
There's a more worrying part: It refers to unreleased versions of Claude in more detail than released versions.
For a company calling chinese companies out for distillation attacks on their models, this very much looks like a distillation attack against human maintainers, especially when combined with the frustration detector.
No problem at all in the EU, as the user would either would need to review and redact the output or would need to put a transparency note up by law [0]. I am sure that Anthropic with their high ethical standards will educate their users ...
Does this apply to their internal use as well? They can really only claim DMCA status on the leaked code if it was authored by humans. Claude attribution in their internal git history would make a strong case that they do not in fact own the copyright to Claude Code itself and are therefore abusing the DMCA system to protect leaked trade secrets rather than protect copyright.
I would have expected people (maybe a small minority, but that includes myself) to have already instructed Claude to do this. It’s a trivial instruction to add to your CLAUDE.md file.
It doesn't work so well in my experience. I am currently wrapping (or asking the LLM to wrap) the commit message prompt in a script call.
1. the LLM is instructed on how to write a commit message and never include co-authorship
2. the LLM is asked to produce a commit message
3. the LLM output is parsed by a script which removes co-authorship if the LLM chooses to include it nevertheless
Typo from speech to text, corrected: “I guess Anthropic’s system prompt didn't work. If folks are having to add it manually into their own Claude.md files...”
My mistake - it was the configuration setting that did it. Nevertheless, you can control many other aspects of its behavior by tuning the CLAUDE.md prompt.
It's less about pretending to be a human and more about not inviting scrutiny and ridicule toward Claude if the code quality is bad. They want the real human to appear to be responsible for accepting Claud's poor output.
That’s how I’d want it to be honestly. LLMs are tools and I’d hope we’re going to keep the people using them responsible. Just like any other tools we use.
The code has a stated goal of avoiding leaks, but then the actual implementation becomes broader than that. I see two possible explanations:
* The authors made the code very broad to improve its ability to achieve the stated goal
* The authors have an unstated goal
I think it's healthy to be skeptical but what I'm seeing is that the skeptics are pushing the boundaries of what's actually in the source. For example, you say "says on the tin" that it "pretends to be human" but it simply does not say that on the tin. It does say "Write commit messages as a human developer would" which is not the same thing as "Try to trick people into believing you're human." To convince people of your skepticism, it's best to stick to the facts.
By "says on the tin," I was referring to the name ("undercover mode") and the instruction to "not blow your cover." If pretending to be a human is not the cover here, what is? Additionally, does Claude code still admit that it's a LLM when this prompt is active as you suggest, or does it pretend to be a human like the prompt tells it to?
You can already turn off "Co-Authored-By" via Claude Code config. This is what their docs show:
~/.claude/settings.json
{
"attribution": {
"commit": "",
"pr": ""
},
The rest of the prompt is pretty clear that it's talking about internal use.
Claude Code users aren't the ones worried about leaking "internal model codenames" nor "unreleased model opus-4-8" nor Slack channel names. Though, nobody would want that crap in their generated docs/code anyways.
Seems like a nothingburger, and everyone seems to be fantasizing about "undercover mode" rather than engaging with the details.
None of this is really worrying, this is a pattern implemented in a similar way by every single developer using AI to write commit messages after noticing how exceptionally noisy they are to self-attribute things. Anthropics views on AI safety and alignment with human interests dont suddenly get thrown out with the bathwater because of leaked internal tooling of which is functionally identical to a basic prompt in a mere interface (and not a model). I dont really buy all the forced "skepticism" on this thread tbh.
I cringe every time I see Claude trying to co-author a commit. The git history is expected to track accountability and ownership, not your Bill of Tools. Should I also co-author my PRs with my linter, intellisense and IDE?
If those tools are writing the code then in general I do expect that to be included in the PR! Through my whole career I've seen PRs where people noted that code that was generated (people have been generating code since long before LLMs). It's useful context unless you've gone over the generated code and understand it and it is the same quality as if you wrote it yourself (which in my experience is the case where it's obvious boilerplate or the generated section is small).
Needing to flag nontrivial code as generated was standard practice for my whole career.
> It's useful context unless you've gone over the generated code and understand it and it is the same quality as if you wrote it yourself
If this is not the case you should not be sending it to public repos for review at all. It is rude and insulting to expect the people maintaining these repos to review code that nobody bothered to read.
Usually, pre-LLM generated code is flagged because people aren't expected to modify it by hand. If you find a bug and track it to the generated code, you are expected to fix the sources and re-generate.
This is not at all the case with LLM-generated code - mostly because you can't regenerate it even if you wanted to, as it's not deterministic.
That said, I do agree that LLM code is different enough from human code (even just in regards to potential copyright worries) that it should be mentioned that LLMs were used to create it.
Absolutely. Let's say I have a problem with gRPC and traced it to code generated using the gRPC compiler. I can reproduce it, highlight it and I'm pretty sure the gRPC team would address the issue.
Replace gRPC compiler with LLM. Can you reproduce? (probably not 100%). Can anybody fix it short of throwing more english phrases like "DO NOT", "NEVER", "Under No Circumstances"?
Compilers don't usually write the code that ends up in a PR. But compilers do (and should) generally leave behind some metadata in the end result saying what tools were used, see for example the .comment section in ELF binaries.
Compiler versions are usually included in the package manifest. Generally you include commit info compiler version and compilation date and platform embedded in the binaries that compilers produce.
There are many techniques. You're most likely to come across things like declarative DSL:s and macros, then there are things like JAXB and similar tooling that generates code from data schemas, and some people script around data sources to glue boilerplate and so on.
Arguably snippet collections belong to this genre.
I am not against the general use of AI code. Quite simply, my view is that all relevant context for a review should be disclosed in the PR.
AI and humans are not the same as authors of PRs. As an obvious example: one of the important functions of the PR process is to teach the writer about how to code in this project but LLMs fundamentally don't learn the same way as humans so there's a meaningful difference in context between humans and AIs.
If a human takes the care to really understand and assume authorship of the PR then it's not really an issue (and if they do, they could easily modify the Claude messages to remove "generated by Claude" notes manually) but instead it seems that Claude is just hiding relevant context from the reviewer. PRs without relevant context are always frustrating.
I think this is just the beginning so people are apprehensive, rightfully so, at this stage. I agree with you that AI use should be disclosed but using the commit message as a billboard for Anthropic hell no. Go put an add on the free tier.
You don't generally commit compiled code to your VCS. If you do need to commit a binary for whatever reason, yeah it makes sense to explain how the binary was generated.
A whole lot of people find LLM code to be strictly objectionable, for a variety of reasons. We can debate the validity of those reasons, but I think that even if those reasons were all invalid, it would still be unethical to deceive people by a deliberate lie of omission. I don't turn it off, and I don't think other people should either.
For the purpose of disclosure, it should say “Warning: AI generated code” in the commit message, not an advertisement for a specific product. You would never accept any of your other tools injecting themselves into a commit message like that.
I don’t think that’s necessarily the case. Exposure and discovery aren’t that tightly correlated. Maybe there’s a small effect, but I think it is outweighed by the fact that blast radius and spread is reduced while buying time for discovery.
My tools just don't add such comments. I don't know why I would care to add that information. I want my commits to be what and why, not what editor someone used. It seems like cruft to me. Why would I add noise to my data to cater to someone's neuroticism?
At least at my workplace though, it's just assumed now that you are using the tools.
What editor you are using has no effect on things like copyright, while software that synthesises code might.
In commercial settings you are often required to label your produce and inform about things like 'Made in China' or possible adverse effects of consumption.
well if I know a specific LLM has certain tendencies (eg. some model is likely to introduce off-by-one errors), I would know what to look for in code-review
I mean, of course I would read most of the code during review, but as a human, I often skip things by mistake
If a whole of people thought that running code through a linter or formatter was objectionable, I'd probably just dismiss their beliefs as invalid rather than adding the linter or formatter as a co-author to every commit.
Linters and formatters are different tools then LLMs. There is a general understanding that linters and formatters don’t alter the behavior of your program. And even still most projects require a particular linter and a formatter to pass before a PR is accepted, and will flag a PR as part of the CI pipeline if a particular linter or a particular formatter fails on the code you wrote. This particular linter and formatter is very likely to be mentioned somewhere in the configuration or at least in the README of the project.
Like frying a veggie burger in bacon grease. Just because somebody's beliefs are dumb doesn't mean we should be deliberately tricking them. If they want to opt out of your code, let them.
Never fried one in bacon grease, but they are good with bacon and cheese. I have had more than one restaurant point out that their bacon wasn't vegetarian when ordering, though.
Likewise. I don’t mind that people use LLMs to generate text and code. But I want any LLM generated stuff to be clearly marked as such. It seems dishonest and cheap to get Claude to write something and then pretend you did all the work yourself.
I think the issue is less attribution and more review mode.
If I assume a change was written and checked line-by-line by the author, I review it one way.
If an LLM had a big hand in it, I review it another way.
You can disclose that you used an LLM in the process of writing code in other ways, though. You can just tell people, you can mention it in the PR, you can mention it in a ticket, etc.
+1. If we’re at an early stage in the agentic curve where we think reading commit messages is going to matter, I don’t want those cluttered with meaningless boilerplate (“co-authored by my tools!”).
But at this point i am more curious if git will continue to be the best tool.
I'm only beginning to use "agentic" LLM tools atm because we finally gained access to them at work, and the rest of my team seems really excited about using them.
But for me at least, a tool like Git seems pretty essential for inspecting changes and deciding which to keep, which to reroll, and which to rewrite. (I'm not particularly attached to Git but an interface like Magit and a nice CLI for inspecting and manipulating history seem important to me.)
What are you imagining VCS software doing differently that might play nicer with LLM agents?
So if I use Claude to write the first pass at the code, make a few changes myself, ask it to make an additional change, change another thing myself, then commit it — what exactly do you expect to see then?
I don't think so. The tag doesn't just say "this was written by an LLM". It says which LLM - which model - authored it. As LLMs get more mature, I expect this information will have all sorts of uses.
It'll also become more important to know what code was actually written by humans.
If you accept the code generated by them nearly verbatim, absolutely.
I don't understand why people consider Claude-generated code to be their own. You authored the prompts, not the code. Somehow this was never a problem with pre-LLM codegen tools, like macro expanders, IPC glue, or type bundle generators. I don't recall anybody desperately removing the "auto-generated do not edit" comments those tools would nearly always slap at the top of each file or taking offense when someone called that code auto-generated. Back in the day we even used to publish the "real" human-written source for those, along with build scripts!
It's weird, because they should not consider it as their own, but they should take accountability from it.
Ideally, if I contribute to any codebase, what needs to be judged is the resulting code. Is it up to the project's standards ? Does the maintainer have design objections ?
What tool you use shouldn't matter, be it your IDE or your LLM.
But that also means you should be accountable for it, you shouldn't defend behind "But Claude did this poorly, not me !", I don't care (in a friendly way), just fix the code if you want to contribute.
The big caveat to this is not wanting AI-Generated code for ideological reasons, and well, if you want that you can make your contributors swear they wrote it by themselves in the PR text or whatever.
I'm not really sure how to feel about this, but I stand by my "the code is what matters" line.
Some differences with the human source for those kinds of tools: (1) the resultant generated code was deterministic (2) it was usually possible to get access to the exact version of the tool that generated it
Since AI tools are constantly obsoleted, generate different output each run, and it is often impossible to run them locally, the input prompts are somewhat useless for everyone but the initial user.
Yes, it sets the reviewer's expectations around how much effort was spent reviewing the code before it was sent.
I regularly have tool-generated commits. I send them out with a reference to the tool, what the process is, how much it's been reviewed and what the expectation is of the reviewer.
Otherwise, they all assume "human authored" and "human sponsored". Reviewers will then send comments (instead of proposing the fix themselves). When you're wrangling several hundred changes, that becomes unworkable.
Well is it actually being used as a tool where the author has full knowledge and mental grasp of what is being checked in, or has the person invoked the AI and ceded thought and judgment to the AI? I.e., I think in many cases the AI really is the author, or at least co-author. I want to know that for attribution and understanding what went into the commit. (I agree with you if it's just a tool.)
Pre-LLM, it was much easier for reviewers to discern that. Now, the AI-generated code can look like it was well thought out by somebody competent, when it wasn't.
Have you ever reviewed an AI-generated commit from someone with insufficient competence that was more compelling than their work would be if it was done unassisted? In my experience it’s exactly the opposite. AI-generation aggravates existing blindspots. This is because, excluding malicious incompetence, devs will generally try to understand what they’re doing if they’re doing it without AI
I have. It's always more compelling in a web diff. These guys are the first coworkers for which it became absolutely necessary for me to review their work by pulling down all their code and inspecting every line myself in the context of the full codebase.
I try to understand what the llm is doing when it generates code. I understand that I'm still responsible for the code I commit even if it's llm generated so I may as well own it.
Tools do author commits in my code bases, for example during a release pipeline. If I had commits being made by Claude I would expect that to be recorded too. It isn't for recording a bill of tools, just to help understand a projects evolution.
No, because those things don't change the logical underpinnings of the code itself. LLM-written code does act in ways different enough from a human contributor that it's worth flagging for the reviewer.
Yea in my Claude workflow, I still make all the commits myself.
This is also useful for keeping your prompts commit-sized, which in my experience gives much better results than just letting it spin or attempting to one-shot large features.
>legally speaking.. if you're not sure of the risk- you don't document it.
Ah, so you kinda maybe sorta absolve yourself of culpability (but not really — "I didn't know this was copyrighted material" didn't grant you copyright), and simultaneously make fixing the potentially compromised codebase (someone else's job, hopefully) 100x harder because the history of which bits might've been copied was never kept.
Solid advice! As ethical as it is practical.
By the same measure, junkyards should avoid keeping receipts on the off chance that the catalytic converters some randos bring in after midnight are stolen property.
Better not document it.
One little trick the legal folks don't want you to know!
Huh? Unless the sole purpose of the commit was to lint code, it would be unnecessary fluff to append the name of the automatically linted tools that ran in a pre-commit hook in every commit.
In some jurisdictions (e.g. the UK) the law is already clear that you own the copyright. In the US it is almost certain that you will be the author. The reports of cases saying otherwise I have been misreported - the courts found the AI could not own the copyright.
It's beyond obvious that a LLM cannot have copyright, any more than a cat or a rock can. The question is whether anyone has or if whatever content generated by a LLM simply does not constitute a work and is thus outside the entire copyright law. As far as I can see, it depends on the extent of the user's creative effort in controlling the LLM's output.
It may be obvious to you, but it has lead to at least one protracted court case in the US: Thaler v. Perlmutter.
> The question is whether anyone has or if whatever content generated by a LLM simply does not constitute a work and is thus outside the entire copyright law.
Its is going to vary with copyright law. In the UK the question of computer generated works is addressed by copyright law and the answer is "the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken"
Its also not a simple case of LLM generated vs human authored. How much work did the human do? What creative input was there? How detailed were the prompts?
In jurisdictions where there are doubts about the question, I think code is a tricky one. If the argument that prompts are just instructions to generate code, therefore the code is not covered by copyright, then you could also argue that code is instructions to a compiler to generate code and the resulting binary is not covered by copyright.
The binary should be considered "derived work". Only the original copyright owner has the exclusive right to create or authorize derivative works. Means you are not allowed to compile code unless you have the license to do so. Right?
It is not "beyond obvious" that a cat cannot have copyright, given the lawsuit about a monkey holding copyright [1], and the way PETA tried to used that case as precedent to establish that any animal can hold copyright.
Thaler v. Perlmutter: The D.C. Circuit Court affirmed in March 2025 that the Copyright Act requires works to be authored "in the first instance by a human being," a ruling the Supreme Court left intact by declining to hear the case in 2026.
Authors and inventors, courts have ruled, means people. Only people. A monkey taking a selfie with your camera doesn't mean you own a copyright. An AI generating code with your computer is likewise, devoid of any copyright protection.
The ruling says that the LLM cannot be the author. It does not say that the human being using the LLM cannot be the author. The ruling was very clear that it did not address whether a human being was the copyright holder because Thaler waived that argument.
the position with a monkey using your camera is similar, and you may or may not hold the copyright depending on what you did - was it pure accident or did you set things up. Opinions on the well known case are mixed: https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...
Where wildlife photographers deliberately set up a shot to be triggered automatically (e.g. by a bird flying through the focus) they do hold the copyright.
AI generated code has no copyright. And if it DID somehow have copyright, it wouldn't be yours. It would belong to the code it was "trained" on. The code it algorithmically copied. You're trying to have your cake, and eat it too. You could maybe claim your prompts are copyrighted, but that's not what leaked. The AI generated code leaked.
The linked document labeled "Part 2: Copyrightability", section V. "Conclusions" states the following:
> the Copyright Office
concludes that existing legal doctrines are adequate and appropriate to resolve questions of
copyrightability. Copyright law has long adapted to new technology and can enable case-by-
case determinations as to whether AI-generated outputs reflect sufficient human contribution to
warrant copyright protection. As described above, in many circumstances these outputs will be
copyrightable in whole or in part—where AI is used as a tool, and where a human has been able
to determine the expressive elements they contain. Prompts alone, however, at this stage are
unlikely to satisfy those requirements.
So the TL;DR basically implies pure slop within the current guidelines outlined in conclusions is NOT copyrightable. However collaboration with an AI copyrightability is determined on a case by case basis. I will preface this all with the standard IANAL, I could be wrong etc, but with the concluding language using "unlikely" copyrightable for slop it sounds less cut and dry than you imply.
That's typical of this site. I hand you a huge volume of evidence explaining why AI generated work cannot be copyrighted. You search for one scrap of text that seems to support your position even when it does not.
You have no idea how bad this leak is for Anthropic because with the copyright office, you have a DUTY TO DISCLOSE any AI generated work, and it is fully RETROACTIVE. And what is part of this leak? undercover.ts. https://archive.is/S1bKY Where Claude is specifically instructed to HIDE DISCLOSURE of AI generated work.
That's grounds for the copyright office and courts to reject ANY copyright they MIGHT have had a right to. It is one of the WORST things they could have done with regard to copyright.
I merely read the PDF articles you linked, then posted, verbatim, the primary relevant section I could find therein. Nowhere does it say that works involving humans in collaboration with AI can't be copyrighted. The conclusions linked merely state that copyright claims involving AI will be decided on a case by case basis. They MAY reject your claim, they may not. This is all new territory so it will get ironed out in time, however I don't think we've reached full legal consensus on the topic, even when limiting our scope to just US copyright law.
I'm interpreting your most recent reply to me as an implication that I'm taking the conclusions you yourself linked out of context. I'm trying to give the benefit of the doubt here, but the 3 linked PDF documents aren't "a mountain of evidence" supporting your argument. Maybe I missed something in one of those documents (very possible), but the conclusions are not how you imply.
Whether or not a specific git commit message correctly sites Claude usage or not may further muddy the waters more than IP lawyers are comfortable with at this time (and therefore add inherent risk to current and future copyright claims of said works), but those waters were far from crystal clear in the first place.
Again, IANAL, but from my limited layman perspective it does not appear the copyright office plans to, at this moment in time, concisely reject AI collaborated works from copyright.
Your most recent link (Finnegan) is from an IP lawyer consortium that says it's better to include attribution and disclosure of AI to avoid current and future claim rejections. Sounds like basic cover-your-ass lawyer speak, but I could be wrong.
Full disclosure: I primarily use AI (or rather agentic teams) as N sets of new eyeballs on the current problem at hand, to help debug or bounce ideas off of, so I don't really have much skin in this particular game involving direct code contributions spit out by LLMs. Those that have any risk aversion, should probably proceed with caution. I just find the upending of copyright (and many other) norms by GenAI morbidly fascinating.
That comment is spot on. Claude adding a co-author to a commit is documentation to put a clear line between code you wrote and code claude generated which does not qualify for copyright protection.
The damning thing about this leak is the inclusion of undercover.ts. That means Anthropic has now been caught red handed distributing a tool designed to circumvent copyright law.
Anthropic could at least make a compelling case for the copyright.
It becomes legally challenging with regards to ownership if I ever use work equipment for a personal project. If it later takes off they could very well try to claim ownership in its entirety simply because I ran a test once (yes, there's a while silicon valley season for it).
I don't know if they'd win, but Anthropic absolutely would be able to claim the creation of that code was done on their hardware. Obviously we aren't employees of theirs, though we are customers that very likely never read what we agreed to in a signup flow.
Using work equipment for a personal project only matters because you signed a contract giving all of your IP to your employer for anything you did with (or sometimes without) your employer's equipment.
Anthropic's user agreement does not have a similar agreement.
My point was that they could make a compelling case though, not that they would win.
I don't know of ant precedent where the code was literally generated on someone else's system. Its an open question whether that implies any legal right to the work and I could pretty easily see a court accepting the case.
I cannot bring myself to care about distillation, when these companies have built their empires on top of everyone else's stolen data, while at the same time telling the world they're out to replace us all.
"frontier" as in the frontier of using everybody else's code, books, art of everyone else for a specific purpose that was never intended to, as in, not even open source projects ever imagined LLMs becoming a thing and their licenses reflected as much.
- you are assuming that an AGI will prevent more deaths than it would cause
- you are assuming that AGI is just around the corner and that scaling up language models is the path to get there
- you can make this argument about basically anything (nuclear power, tuberculosis medication, free healthcare). I’d say the burden of proof is on you to back up your extraordinary claim with extraordinary evidence.
> every delay to AGI results in deaths that AGI could have prevented
Sure, that's what AGI would be used for /s
In other news, we are not even close to AGI and even with the current experimental technology, frontier AI model companies are already fighting to help departments of war, which actually results in the most deaths. What makes you think AGI would be used for not leading to the same millions of deaths?
Tbh, I think distillation is happening both ways. And at this stage, "quality" is stagnating, the main edge is the tooling. The harness of CC seems to be the best so far, and I wonder if this leak would equalize the usability.
more likely, they would parse them out using simple regex, the whole point is they're there but not used. Distillation is becoming less common now however
This was my favorite bit, "We're going to steal countless copy righted works and completely ignore software licenc... wait, what? You aren't allowed to turn around and do it to us! Stop that right now!"
My GitHub fork of anthropics/claude-code just got taken down with a DMCA notice lol
It did not have a copy of the leaked code...
Anthropic thinking 1) they can unring this bell, and 2) removing forks from people who have contributed (well, what little you can contribute to their repo), is ridiculous.
GitHub's note at the top says: "Note: Because the reported network that contained the allegedly infringing content was larger than one hundred (100) repositories, and the submitter alleged that all or most of the forks were infringing to the same extent as the parent repository, GitHub processed the takedown notice against the entire network of 8.1K repositories, inclusive of the parent repository."
wow, it's also not like their code was actually good (though this apply to most enterprise software). To hide a client behind closed source (it's also typescript, so even more baffling) is laughable behavior.
They constantly love to talk about Claude Code being "100%" being vibe coded...and the US legal system is leaning towards that not being copyrightable.
It could still be a trade secret, but that doesn't fall under a DMCA take down.
IIUC, a person can only claim copyright if they have significantly transformed the output. Unaltered LLM output is not copyrightable per US court decisions.
The whole thing is a legal mess. How do you know the LLM did not reproduce existing code? There is an ongoing legal battle in German between GEMA and OpenAI because ChatGPT reproduced parts of existing song lyrics. A court in Munich has found that this violates German copyright law.
I think you're misunderstanding copyright and ownership.
A copyright over code means that ONLY you can use that code, and nobody else; otherwise, you can sue them. For example, if you are an arist, you want to protect your IP this way.
Yes, AI generated code is not copyrightable but so is most code in general. It is very hard to truly get a copyright for a piece of code. But just because you don't have copyright to something doesn't mean it's not your property.
For example, you can buy several movies on DVD and those DVDs will still be your property even though you don't have copyright and if someone does steal those DVDs, it will be considered theft of your property. Similarly, just because the code is AI-generated/not copyrightable, doesn't mean others can just steal it.
Think about it - so many codebases are not legally protected as copyrighted material but are absolutely protected by IP laws and enforced by the companies that own them.
Huh? Normal property law is plainly not applicable to a non-rival good like information (unlike for instance a physical DVD: if someone takes a DVD from me, I don’t have it anymore). “Intellectual property” is, but it is not so much a legal regime as confusing shorthand for a number of distinct ones:
- Trademark law, which applies to markings on copies rather than copies themselves;
- Trade secret law, which stops applying when the information escapes into the wild through the secret-holder’s own actions;
- Patent law, which definitionally only applies to public knowledge as an incentive to not keep it secret instead;
- Publicity rights, which only apply to depictions or discussions of natural persons;
- Moral rights, which are mostly about being recognized as the author and even in their strongest incarnations do not restrict unmodified copies;
- Database right, which isn’t applicable as we’re not talking about a compendium of things, and anyway does not exist in the US and most other places outside the EU;
- Copyright, which you’ve conceded is not applicable here.
There’s no “intellectual property” distinct from these things, and none of them are relevant.
This is even worse. My Claude Code instance can theoretically write the same code as your instance for a similar prompt. Why should one of us be able to have the copyright?
No the human cannot hold the copyright also. They can own the property rights to the code and protect it. It's not like the rule is "AI cannot copyright stuff but humans can" but rather code is rarely copyrighted and in its case, ownership is much more important.
If your code was generated by you and you store it in your system and have property rights over it, you can enforce legal actions even without holding a copyright over the code.
In general, it is kind of weird to want to copyright code. How do you patent a for-loop for example
Yea this is the thing that makes no sense to me. Any frontier model can unmiminize minified JS pretty decently. Obviously not everything comes through, comments and such, but I always assumed the reason it wasn't open source was to prevent an endless shitstorm of AI slop PR's, not because they were trying to protect secret sauce.
The name "Undercover mode" and the line `The phrase "Claude Code" or any mention that you are an AI` sound spooky, but after reading the source my first knee-jerk reaction wouldn't be "this is for pretending to be human" given that the file is largely about hiding Anthropic internal information such as code names. I encourage looking at the source itself in order to draw your conclusions, it's very short: https://github.com/alex000kim/claude-code/blob/main/src/util...
That seems desirable? Like that's what commit messages are for. Describing the change. Much rather that than the m$ way of putting ads in commit messages
The commit message should complement the code. Ideally, what the code does should not need a separate description, but of course there can be exceptions. Usually, it's more interesting to capture in the commit message what is not in the code: the reason why this approach was chosen and not some other obvious one. Or describe what is missing, and why it isn't needed.
That sounds like design discussions best had in the issue/ticket itself, before you even start writing code. Then the commit message references the ticket and has a brief summary of the changes.
Writing and reading paragraphs of design discussion in a commit message is not something that seems common.
Ticket systems are quite ephemeral. I still have access to commit messages from the 90s (and I didn't work on the software at the time). I haven't been able to track the contents of the gnats bug tracker from those days.
And of course tickets can be private, so even if the data survived migration, you may not have access to it (principle of least privilege and all that).
Not really about design, but technical reasons why this solution came to be when it’s not that obvious. It’s not often needed. And when it does, it usually fits in a short paragraph.
What you're describing here is a design. The most important parts of a design are the decisions and their reasoning.
e.g. "we decided on tool/library pattern X over tool/library/pattern Y because Z" – that is a design, usually discussed outside (and before) a commit message.
You discuss these decisions with others, document the discussion and decision, and then you have a design and can start writing code.
Let me ask you this: suppose you have a task that needs to be done eventually, and you want to write down some ideas for it, but don't want to start coding right now. Where do you put those ideas? How do you link them to that specific task?
So you'd disagree with style that Linux uses for their commits?
Random example:
Provide a new syscall which has the only purpose to yield the CPU after the
kernel granted a time slice extension.
sched_yield() is not suitable for that because it unconditionally
schedules, but the end of the time slice extension is not required to
schedule when the task was already preempted. This also allows to have a
strict check for termination to catch user space invoking random syscalls
including sched_yield() from a time slice extension region.
I think my post makes it pretty clear that I would. If you want, I could cite several examples of organizations which use the method I described, so you can weigh it against the one example you provided, and get the full picture.
In your example, for example, where was the issue tracked before the code was written? The format you linked makes it difficult to get the history of the issue.
Let me ask you this: suppose you have a task that needs to be done eventually, and you want to write down some ideas for it, but don't want to start coding right now. Where do you put those ideas? How do you link them to that specific task?
Git was built for email, because that's the system Linux uses. Commits appear inline. Diffs are reviewed and commented inline.
Email is the review process, and commits contain enough information that git blame can get you a reasoning - it doesn't require you checking the email archive. Rather than a dead ticket that no longer exists.
I can also supply you a list of companies that make use of git's builtin features if you like. But thats probably not relevant to discussing management techniques.
Everyone has its own system although companies do tend to codify it with a project manager. I used TODO.txt inside the repo. an org file, Things.app, a stack of papers, and a whiteboard. But once a task is done, I can summarize the context in a paragraph or two. That’s what I put in the commits.
Unfortunately GitHub Copilot’s commit message generation feature is very human. It’s picked up some awful habits from lazy human devs. I almost always get some pointless “… to improve clarity” or “… for enhanced usability” at the end of the message.
VS Code has a setting that promises to change the prompt it uses to generate commit messages, but it mostly ignores my instructions, even very literal ones like “don’t use the words ‘enhance’ or ‘improve’”. And oddly having it set can sometimes result in Cyrillic characters showing up at the end of the message.
Ultimately I stopped using it, because editing the messages cost me more time than it saved.
Honestly the aggressive verbosity of github copilot is half the reason don't use its suggested comments. AI generated code comments follow an inverted-wadsworth-constant: Only the first 30% is useful.
As opposed to outputting debugging information, which I wouldnt be surprised if LLMs do output "debug" output blurbs which could include model specific information.
The human developer would just write what the code does, because the commit also contains an email address that identifies who wrote the commit. There's no reason to write:
> Commit f9205ab3 by dkenyser on 2026-3-31 at 16:05:
> Fixed the foobar bug by adding a baz flag - dkenyser
Because it already identified you in the commit description. The reason to add a signature to the message is that someone (or something) that isn't you is using your account, which seems like a bad idea.
Aside from merges that combine commits from many authors onto a production branch or release tag. I would personally not leave an agent to do that sort of work.
Which is funny given how many workplaces are requiring developers use AI, measuring their usage, and stack ranking them by how many tokens they burn. What I want is something that I can run my human-created work product through to fool my employer and its AI bean counters into thinking I used AI to make it.
I guess that would work until they started auditing your prompts. I suppose you could just have a background process on your workstation just sitting there Clauding away on the actual problem, while you do your development work, and then just throw away the LLM's output.
Undercover mode seems like a way to make contributions to OSS when they detect issues, without accidentally leaking that it was claude-mythos-gigabrain-100000B that figured out the issue
The hooks system is the most underappreciated thing in what leaked. PreToolUse,
PostToolUse, session lifecycle, all firing via curl to a local server. Clean
enough to build real tooling on top of without fighting it.
The frustration regex is funny but honestly the right call. Running an LLM call
just to detect "wtf" would be ridiculous.
KAIROS is what actually caught my attention. An always-on background agent that
acts without prompting is a completely different thing from what Claude Code is
today. The 15 second blocking budget tells me they actually thought through what
it feels like to have something running in the background while you work, which
is usually the part nobody gets right.
The buddy feature the article mentions is planned for release tomorrow, as a sort of April Fools easter egg. It'll roll out gradually over the day for "sustained Twitter buzz" according to the source.
The pet you get is generated based off your account UUID, but the algorithm is right there in the source, and it's deterministic, so you can check ahead of time. Threw together a little app to help, not to brag but I got a legendary ghost https://claudebuddychecker.netlify.app/
Cute! Cactus for me. Nice animations too - looks like there were multiple of us asking Claude to reverse engineer the system. I did a slightly deeper dive here if you're interested, plus you can see all the options available: https://variety.is/posts/claude-code-buddies/
(I didn't think to include a UUID checker though - nice touch)
Neat! That's a great write up, cool to see others looking into it.
I do wonder if they're going to do anything with the stats and shinies bit. Seems like the main piece of code for buddies that's going to handle hatching them tomorrow is still missing (comments mention a missing /buddy/index file), so maybe it'll use them there.
Update: it looks like the live version of the algorithm is slightly different, probably changed because of these leaks. As such the app predictions aren't accurate, sorry
Huh weird, they must have changed the algorithm up due to the leaks. Would be pretty easy, there's a constant seed variable so they'd just need to change that, figured they might. Too bad, sorry this didn't work out
This is awesome! Working on a desktop pet so the buddy caught my attention. Looking forward to making friends with my Rare Duck buddy tomorrow. Wish it was a snarky duck instead of a patient one though.
I don't understand the part about undercover mode. How is this different from disabling claude attribution in commits (and optionally telling claude to act human?)
On that note, this article is also pretty obviously AI-generated and it's unfortunate the author didn't clean it up.
It's people overreacting, the purpose of it is simple, don't leak any codenames, project names, file names, etc when touching external / public facing code that you are maintaining using bleeding edge versions of Claude Code. It does read weird in that they want it to write as if a developer wrote a commit, but it might be to avoid it outputting debug information in a commit message.
I'm amazed at how much of what my past employers would call trade secrets are just being shipped in the source. Including comments that just plainly state the whole business backstory of certain decisions. It's like they discarded all release harnesses and project tracking and just YOLO'd everything into the codebase itself.
Edit: Everyone is responding "comments are good" and I can't tell if any of you actually read TFA or not
> “BQ 2026-03-10: 1,279 sessions had 50+ consecutive failures (up to 3,272) in a single session, wasting ~250K API calls/day globally.”
This is just revealing operational details the agent doesn't need to know to set `MAX_CONSECUTIVE_AUTOCOMPACT_FAILURES = 3`
Agents and I apparently have a whole lot in common.
Only being half ironic with this. I generally find that people somehow magically manage to understand how to be materially helpful when the subject is a helpless LLM. Instead of pointing it to a random KB page, they give it context. They then shorten that context. They then interleave context as comments. They provide relevant details. They go out of their way to collect relevant details. Things they somehow don't do for their actual colleagues.
This only gets worse when the LLM captures all that information better than certain human colleagues somehow, rewarding the additional effort.
Right? It's infuriating. Nearly all of the agentic coding best practices are things that we should have just been doing all along, because it turns out humans function better too when given the proper context for their work. The only silver lining is that this is a colossal karmic retribution for the orgs that never gave a shit about this stuff until LLMs.
> It's infuriating. Nearly all of the agentic coding best practices are things that we should have just been doing all along
There's a good reason why we didn't though: because we didn't see any obvious value in it. So it felt like a waste of time. Now it feels like time well spent.
> Only being half ironic with this. I generally find that people somehow magically manage to understand how to be materially helpful when the subject is a helpless LLM. Instead of pointing it to a random KB page, they give it context. They then shorten that context. They then interleave context as comments. They provide relevant details. They go out of their way to collect relevant details. Things they somehow don't do for their actual colleagues.
"Self-descriptive code doesn't need comments!" always gets an eye-roll from me
Huh. It's displayed taking up three cells in my terminal, but laid out as if its width were one cell. Irritating. I wonder if there are any other grapheme clusters that don't properly fit in two cells?
Meanwhile, some colleagues: "Code should have as little comments as possible, the code should explain itself." (conceptually not wholly wrong, but it can only explain HOW not WHY and even then often insufficiently) all while having barebones/empty README.md files more often than not. Fun times.
Or how would you name methods and variables to explain why some payment reconciliation process skips matching for transactions under 0.50 EUR and just auto-approves them, because the external payment processor rounds differently than the internal ledger at sub-euro amounts, creating mismatches that were flooding the finance team's exception queue in 2013, explained more under Jira issue ZXSV-12456 and more details are known by j.doe@myorg.com. The threshold was chosen after analyzing six months of false positives, when it's any higher someone being undercharged doesn't get caught. I don't think autoApproveThreshold = 0.50 or anything like that would get the full context across, even if the rules themselves are all code.
I think surely you can have both! Code should explain itself as often as possible, but when you hit a wall due to some counter-intuitive workarounds being needed, or some business rules or external considerations that you need to keep track of, then comments also make sense. Better than just putting everything in a Jira issue somewhere, given that it often won't be read by you or others and almost certainly will not be read by any AI agents (unless you have an MCP or something, but probably uncommon), or spending hours trying to get the code to explain something it will never explain well. I've had people ask me about things that are covered in the README.md instead of reading it.
You’ve correctly identified that naming isn’t sufficient for all communication. Name the things that stay constant in the code and explain the things that vary with a particular implementation in version control messages. Version control as a medium communicates what context the message was written for, which is far more appropriate than comments.
But you will also fail to keep the comments and code synchronized, and the comment will at some point no longer describe why the code is doing whatever it does
Comments are great until they diverge from the code. The "no comments, just self-explanatory code" reaction comes from the trauma of having to read hundreds of lines of comments only to discover they have nothing to do with how the code actually works, because over time the code has received updates but the comments haven't. In that case it's better to just have no comments or documentation of any kind--less cognitive overhead. This is a symptom of broken culture, but the breakage is the same kind that has managers salivating over LLM vibeslop. So I totally get where your colleagues might be coming from. Working within the confines of how things actually are it could be totally reasonable.
This is honestly such a bad argument against comments.
I'm gonna note down my reasons for doing things and other information I deem useful, and if some other dipshit 5 years from now when I've moved on comes along and starts changing everything up without keeping the comments up to date that's their problem not mine. There was never anything wrong with my comments, the only thing that's wrong is the dipshit messing things up.
Doesn't matter what I do, the dipshit is going to mess everything up anyway. Those outdated comments will be the least of their worries.
You may be a bit overconfident about how clear you will be with your comments.
The “dipshit” doesn’t mess everything up for fun. They don’t understand the comments written by the previous “dipshit” and thus are unable to update the comments.
Oh really? I'm overconfident in my ability to write and read simple clear text notes?
Here's what I think. I think you guys heard the "self-documenting code" BS and ate it up, and now you're grasping at straws to defend your cargo cult position, inventing these "problems" to justify it.
If you're looking at some code and there's a comment saying something that doesn't make sense to you, maybe that's a clue that you're missing a puzzle piece and should take a step back maybe talk to some people to make sure you're not messing things up? Maybe, for a non-dipshit, that comment they don't understand could actually be helpful if they put some effort into it?
Also just to be clear I don't think this is a likely occurrence unless someone doesn't know squat about the codebase at all - my comments generally assume very little knowledge. That's their whole purpose - to inform someone (possibly me) coming there without the necessary background knowledge.
It just isn't feasible to include the why of everything in the code itself. And it sure as hell is better to include some info as comments than none at all. Otherwise a bug will often be indistinguishable from a feature.
And I don't think dipshits mess things up for fun. I think they just suck. They're lazy and stupid, as most developers are. If I'm there I can use reviews etc to help them suck less, if I'm not they're free to wreck my codebase with reckless abandon and nothing I do will make any difference. I cannot safeguard my codebase against that so there's no point in trying and the fact that this is your argument should make you stop and reconsider your position because it's far fetched as fuck.
IME unfortunately that's not actually the case. It very much is your problem, as the architect of the original system, unless you can get yourself transferred to a department far, far away. I've never managed that except by leaving the company.
To be clear, I don't believe it should be this way, but sadly unless you work in an uncommonly well run company it usually is.
I really can't imagine this ever becoming a real problem. Not once have I ever worked in a place where any kind of leadership would ever give a shit about comments nor anything else in the code itself. The lowest level leadership has ever gone is click a button to see if it works.
And if anyone has a problem with comments existing it's trivial to find/replace them out of existence. Literally a one minute job, if you actually think the codebase would be better without them.
This is such a humongous non-issue it's crazy man.
This is also a great way to ensure the documentation is up to date. It’s easier to fix the comment while you’re in the code just below it than to remember “ah yes I have to update docs/something.md because I modified src/foo/bar.ts”.
People moving docs out of code are absolutely foolish because no one is going to remember to update it consistently but the agent always updates comments in the line of sight consistently.
Agent is not going to know to look for a file to update unless instructed. Now your file is out of sync. Code comments keeping everything line of sight makes it easy and foolproof.
Experience doesn’t leave me with any confidence that the long term memory will be useful for long. Our agentic code bases are a few months old, wait a few years for those comments to get out of date and then see how much it helps.
The great thing about agentic coding is you can define one whose entire role is to read a diff, look in contextual files for comments, and verify whether they’re still accurate.
You don’t have to rely on humans doing it. The agent’s entire existence is built around doing this one mundane task that is annoying but super useful.
Yes, lets blow another 5-10k a project/month on tokens to keep the comments up to date. The fact ai still cannot consistently refactor without leaving dead code around even after a self review does not give me confidence in comments…
Comments in code are often a code smell. This is an industry standard for a reason and isnt because of staleness. If u are writing a comment, it means the code is bad or there is irreducible complexity. It is about good design. Comments everywhere are almost always a flag.
I think a big question is whether one wants your agent to know the reason for all the reasons for guidelines you issue or whether you want the agent to just follow the guidelines you issue. Especially, giving an agent the argument for your orders might make the agent think that can question and so not follow those arguments.
> If you're not using comments, you're doing agent coding wrong.
Comments are ultimately so you can understand stuff without having to read all the code. LLMs are great when you force them to read all code, and comments only serve to confuse. I'd say the opposite been true in my experience, if you're not forcing LLMs to not have any comments at all (and it can actually skip those, looking at you Gemini), you're doing agent coding wrong.
I suspect that's the logical endpoint of trying to provide everything as context to an agent. Why use a separate markdown file and have to waste extra tokens explaining what part of the codebase something applies to when you can just put it right there in the code itself?
The issues is that you should have a work flow that strips the comments before sending the code to production. I'm sure they assumed that minifying it is enough though.
They also weren't supposed to be leaking the code itself either. I don't know enough about JS tooling, but is it possible that this might just be the pre-stripped version?
That’s what a source map is. It’s included in debug builds so that browser debuggers (and others) can step through the original code, comments and all, instead of the compiled javascript (which back in the day could become an undecipherable mess of callbacks if you were transpiling async/await to the legacy Promise API).
Unfortunately in many bundlers making a mistake like this is as easy as an agent deleting “process.env[‘ENV’] === ‘debug’” which they’ll gladly do if you point them at a production or staging environment and ask them to debug the stripped/compiled/minified code.
I'd really recommend putting a modicum of work into cleaning up obvious AI generated output. It's rude, otherwise, to the humans you're expecting to read this.
Maybe it would be okay as a first filtering step, before doing actual sentiment analysis on the matches. That would at least eliminate obvious false positives (but of course still do nothing about false negatives).
Is this really the use-case? I imagine the regex is good for a dashboard. You can collect matches per 1000 prompts or something like that, and see if the number grows or declines over time. If you miss some negative sentiment it shouldn't matter unless the use of that specific word doesn't correlate over time with other negative words and is also popular enough to have an impact on the metric.
I'm still amazed that something as ubiquitous as "daemon mode" is still unreleased.
- Claude Chat: built like it's 1995, put business logic in the button click() handler. Switch to something else in in the UI and a long running process hard stops. Very Visual Basic shovelware.
- Claude Cowork: same but now we're smarter, if you change the current convo we don't stop the underlying long-running process. 21st century FTW!
- Claude Code: like chat, but in the CLI
- Claude Dispatch: an actual mobile client app, not the whole thing bundled together.
- Daemon mode: proper long-running background process, still unreleased.
Langchain is for model-agnostic composition. Claude Code only uses one interface to hoist its own models so zero need for an abstraction layer.
Langgraph is for multi-agent orchestration as state graphs. This isn't useful for Claude Code as there is no multi-agent chaining. It uses a single coordinator agent that spawns subagents on demand. Basically too dynamic to constrain to state graphs.
I'm not an supporter of blindly adopting the "langs" but langgraph is useful for deterministically reproducable orchestration. Let's say you have a particular data flow that takes an email sends it through an agent for keyword analysis the another agent for embedding then splits to two agents for sentiment analysis and translation - there is where you'd use langgraph in your service. Claude Code is a consumer tool, not production.
I see what you mean. Maybe in the cases where the steps are deterministic, it might be worth moving the coordination at the code layer instead of AI layer.
What's the value add over doing it with just Python code? I mean you can represent any logic in terms of graphs and states..
Most of the value I’ve gotten out of is has been observability. Graph and DAG workflow abstractions just help OTel structure your LLM logs in a clean hierarchy of spans. I could imagine figuring out a better solution to this than the whole graph abstraction.
I've tried to use langchain. It seemed to force code into their way of doing things and was deeply opinionated about things that didn't matter like prompt templating. Maybe it's improved since then, but I've sort of used people who think langchain is good as a proxy for people who haven't used much ai?
" ...accidentally shipping your source map to npm is the kind of mistake that sounds impossible until you remember that a significant portion of the codebase was probably written by the AI you are shipping.”
I’m more curious how this impacts trust than anything else.
In the span of basically a week, they accidentally leaked Mythos, and then now the entire codebase of CC. All while many people are complaining about their usage limits being consumed quickly.
Individually, each issue is manageable (Because its exciting looking through leaked code). But together, it starts to feel like a pattern.
At some point, I think the question becomes whether people are still comfortable trusting tools like this with their codebases, not just whether any single incident was a mistake.
Not much impact, Codex is already open source. The real value is in the model itself and the ability to use it with a subscription. Something you can't do legally with a clone of this code.
The only thing I found interesting about this leak is just how much of a rats nest the code base is. Like it actually feels vibe coded without a shred of intelligent architecture behind it.
Regardless, you can't beat the subscription and model access despite the state of the code base, so I still use Claude Code daily and love it.
I just hope it doesn't turn out like n8n. I built a few things, wanted to make changes, looked at the code base, opened the devcontainer, noped out after being mortified by the sheer number of warning and dependency issues, threw away all of my work, uninstalled, didn't think about it again.
Idk. This is making leaps. Idc that their tools leaked. I paid 140$ for CC the other day even after getting sometimes not 100% uptime on the lower plan. If anything this leak is most in line with Anthropic's ethical model. They're failing upwards in my opinion
Something that has been clear to me in using it, aside from direct claims by the authors, is that Claude is itself vibe coded slop. The number of random errors I get from using various parts of the web UI or CC that should work feels high for such a popular product. But they’re so deep in the vibes that I don’t think they can tell when some path in their web UI is broken. I tried to share a public link to a chat and it asked me to login when opening it on another computer. I tried to download a conversation and it threw an error. When I download markdown output the download succeeds but the UI throws an error. I have tried to control the behavior of Claude Code in tmux using documented flags but I can’t seem to get them to work properly. Agent teams don’t clean up their tmux windows, making the view a mess after they run. Claude code is an amazing product that I love and also it is itself vibe coded slop.
And there’s no reason why they couldn’t vibe fix the issues if there was a process to report the bugs. Fixing issues like that could also be something that’s fully automated. Provided there’s a good test suite (not a given).
The exploit is a postinstall hook, so CC users would be unaffected. Claude Code itself is most likely built with bun and not npm, so the CC developers would also be immune.
It is super weird that developers have to run a binary blob on their machines. It's 2026, all the major developer CLI tools are open-source anyway. What's the point for Anthropic to even make it secret?
The Claude Code leak shows multi-agent orchestration governed by prompts — 'do not rubber-stamp weak work.' But a prompt can be overridden by a sufficiently capable model, reasoned around, ignored under edge cases, or zeroed out by consensus.
Looking at what actually leaked:
coordinatorMode.ts — orchestration algorithm is a prompt, not code.
undercover.ts — 'do not blow your cover' — a prompt.
No structural voting logic. No hard thresholds. No REQUIRES_HUMAN architectural constraint.
As these agents get more capable, doesn't prompt-based governance get weaker not stronger? The more capable the model, the better it is at reasoning around instructions.
Has anyone actually implemented structural governance for agent swarms — actual voting logic, hard thresholds, REQUIRES_HUMAN as an architectural constraint rather than an instruction?
They have the agents. They have the undercover mode. What does the actual governance layer look like?
And if the answer is 'prompts all the way down' — is that governance or just policy with a better name?
Two things worth separating here: the leak mechanism and the leak contents.
The mechanism is a build pipeline issue. Bun generates source maps by default, and someone didn't exclude the .map file from the npm publish. There's an open Bun issue (oven-sh/bun#28001) about this exact behavior. One missing line in .npmignore or the package.json files field. Same category of error as the Axios compromise earlier this week — npm packaging configuration is becoming a recurring single point of failure across the ecosystem.
The contents are more interesting from a security architecture perspective. The anti-distillation system (injecting fake tool definitions to poison training data scraped from API traffic) is a defensive measure that only works when its existence is secret. Now that it's public, anyone training on Claude Code API traffic knows to filter for it. The strategic value evaporated the moment the .map file hit the CDN.
The undercover mode discussion is being framed as deception, but the actual security question is narrower: should AI-authored contributions to public repositories carry attribution? That's an AI identity disclosure question that the industry hasn't settled. The code shows Anthropic made a specific product decision — strip AI attribution in public commits from employee accounts. Whether that's reasonable depends on whether you think AI authorship is material information for code reviewers.
The frustration regex is the least interesting finding technically but the most revealing culturally. A company with frontier-level NLP capability chose a regex over an inference call for sentiment detection. The engineering reason is obvious (latency and cost), but it tells you something about where even AI companies draw the line on using their own models.
Can someone clarify how the signing can't be spoofed (or can it)? If we have the source, can't we just use the key to now sign requests from other clients and pretend they're coming from CC itself?
Ah yes, the API will accept requests that doesn’t include the client attestation (or the fingerprint from src/utils/fingerprint.ts. At least it did a couple of weeks back.
They are most likely using these as post-fact indicators and have automation they kicks in after a threshold is reached.
Now that the indicators have leaked, they will most likely be rotated.
> Now that the indicators have leaked, they will most likely be rotated.
They can't really do that. Now they have no way to distinguish "this is a user of a non updated Claude code" from "this is a user of a Claude code proxy".
I have yet to see such a company that's so insecure that they would keep their CLI closed source even when the secret sauce is in the model that they control already and is closed source.
Not only that, wouldn't allow other CLIs to be used either.
Anyone else have CI checks that source map files are missing from the build folder? Another trick is to grep the build folder for several function/variable names that you expect to be minified away.
> The obvious concern, raised repeatedly in the HN thread: this means AI-authored commits and PRs from Anthropic employees in open source projects will have no indication that an AI wrote them. It’s one thing to hide internal codenames. It’s another to have the AI actively pretend to be human.
I don’t get it. What does this mean? I can use Claude code now without anyone knowing it is Claude code.
it's written to _actively_ avoid any signs of AI generated code when "in a PUBLIC/OPEN-SOURCE repository".
Also, it's not about you. Undercover mode only activates for Anthropic employees (it's gated on USER_TYPE === 'ant', which is a build-time flag baked into internal builds).
There are probably different reasons for different people. I can definitely see the angle that trying to specifically pretend to not be AI when contributing to open source could be seen as a bad thing due to the open source supply chain attacks, some AI-driven, that we've been having, not to mention the AI-slop PR spam.
But, I also get Anthropic's side that when they're contributing they don't want their internals leaked. If it had been left at that, that's fine, but having it pretend like it's not AI at all rubs me a little bit the wrong way. Why try to hide it?
>There are probably different reasons for different people. I can definitely see the angle that trying to specifically pretend to not be AI when contributing to open source could be seen as a bad thing due to the open source supply chain attacks, some AI-driven, that we've been having, not to mention the AI-slop PR spam.
But none of the other agents advertise that the commit was done by an agent. Like Codex. Your panic should apply equally to already existing agents like Codex no?
Because it has a high likelyhood of being written completely by a LLM without any human thought or attention being put into it.
Being written by a LLM is a signal that the submission is of low effort and therefore probably low quality, which then puts the onus on the people reviewing and reading the submission instead of the original generator of the submission. Hence I would classify it as spam.
Open source communities also have rules against LLM generated contributions, for various moral, ethical, or legal reasons.
...Because it's a mode of using Claude Code that allows certain users to use the application in "stealth mode" to produce pull requests that seem human, but are actually AI generated, which often goes against the contribution rules of OSS projects?
At this point I would consider any employee of an AI provider to be tainted.
If anybody cares about AI-written code slipping in they can grep for style tells or run a classifier against a suspect repo. You won't get guarantees. Watermarks and disclosure tags die the moment someone edits the patch, so secret strings and etiquette signs are cargo cult security and the only answer is review.
I used to swear at Claude. To be honest, I thought it helped get results (maybe this is "oldschool" LLM thinking), but I realized it was just making me annoyed.
It does send an analytics event when you’re swearing based on a keyword filter (something like is_negative:true), presumably as a signal that the model isn’t performing well this session, but who knows?
> As one Twitter reply put it: “accidentally shipping your source map to npm is the kind of mistake that sounds impossible until you remember that a significant portion of the codebase was probably written by the AI you are shipping.”
To err is human. AI is trained on human content. Hence, to err is AI. The day it stops making mistakes will be the beginning of the end. That would mean the existence of a consciousness that has no weakness. Great if it’s on your side. Terrible otherwise.
The part of TFA that does it for me: "Every bash command runs through 23 numbered security checks in bashSecurity.ts, including 18 blocked Zsh builtins, defense against Zsh equals expansion (=curl bypassing permission checks for curl), unicode zero-width space injection, IFS null-byte injection, and a malformed token bypass found during HackerOne review.".
I love it when "magic" like this gets unmasked, and under the hood it's just business as usual, i.e. dumb shit implementations to please the product owner(s) and hopefully the customers as well. Normal stuff in the tech world I suppose but still absolutely hilarious!
Meanwhile Claude Code is still awesome. I don’t see my self switching to OpenAI (seriously bad mgmt and possibly the first domino to fall if there is a correction) or Gemini (Google ethics cough cough).
Gemini is a terrible product, I spent $15K on it. Anthropic and OpenAI make better models, it used to be that Gemini cooked but I don't feel that way anymore
>This was the most-discussed finding in the HN thread. The general reaction: an LLM company using regexes for sentiment analysis is peak irony.
>Is it ironic? Sure. Is it also probably faster and cheaper than running an LLM inference just to figure out if a user is swearing at the tool? Also yes. Sometimes a regex is the right tool.
I'm reading an LLM written write up on an LLM tool that just summarizes HN comments.
I'm so tired man, what the hell are we doing here.
I'm surprised that they don't just keep the various prompts, which are arguably their "secret sauce", hidden server side. Almost like their backend and frontend engineers don't talk to each other.
My company uses Claude through our own private data centers behind our own proxy that logs all requests and responses in and out. However, Anthropic heavily steers these models during RL to respond a certain way to certain prompting, so that's basically the "secret sauce" you're thinking of.
i always wondered what prompts codex / claude code use but always figured they just send variables to the backend and render the whole prompt there so i never even bothered to check with a MITM proxy. turns out i should have just done that…
The irony of an IP scraper on an absolutely breathtaking, epic scale getting its secret sauce "scraped" - because the whole app is vibe coded (and the vibe coders appear to be oblivious to things like code obfuscation cuz move fast!)...
And so now the copy cats can ofc claim this is totally not a copy at all, it's actually Opus. No license violation, no siree!
It's fucking hilarious is what it is, it's just too much.
> Anti-distillation: injecting fake tools to poison copycats
Does this mean `huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled` is unusable? Had anyone seen fake tool calls working with this model?
Can someone ask claude to write a deep dive on how compaction works and why it’s so slow? (I still can’t fathom why they wouldn’t just add a user message “compact the conversation we’ve just had”
It's possible, but Anthropic employees regularly boast (!) that Claude Code is itself almost entirely vibe-coded (which certainly seems true, based on the generally-low quality of the code in this leak), so it wouldn't at all surprise me to have that blow up twice in the same week. Probably it might happen with accelerating frequency as the codebase gets more and more unmanageable.
I'm normally suspicious but honestly they've been so massively supply-constrained that I don't think it really benefits them much. They're not worried about getting enough demand for the new models; they're worrying about keeping up with it.
Granted, there's a small counterargument for mythos which is that it's probably going to be API-only not subscription
They want "Made with Claude Code" on your PRs as a growth marketing strategy. They don't want it on their PRs, so it looks like they're doing something you're not capable of. Well, you are and they have no secret sauce.
I wrote this an hour ago and it seems that Claude might not understand it as frustration:
> change the code!!!! The previous comment was NOT ABOUT THE DESCRIPTION!!!!!!! Add to the {implementation}!!!!! This IS controlled BY CODE. *YOU* _MUST_ CHANGE THE CODE!!!!!!!!!!!
The feature flag names alone are more revealing than the code. KAIROS, the anti-distillation flags, model codenames those are product strategy decisions that competitors can now plan around. You can refactor code in a week. You can't un-leak a roadmap.
I like that if they decide that your usage looks like distillation it just becomes useless, because there’s no way for the end user to distinguish between it just being sort of crappy or sabotaged intentionally. That’s a cool thing to pay for
Something I’ve been thinking about, somewhat related but also tangential to this topic:
The more code gets generated by AI, won’t that mean taking source code from a company becomes legal? Isn’t it true that works created with generative AI can’t be copyrighted?
I wonder if large companies have throught of this risk. Once a company’s product source code reaches a certain percentage of AI generation it no longer has copyright. Any employee with access can just take it and sell it to someone else, legally, right?
In theory, companies are all going to have an increasingly difficult time suing competitors for copyright infringement. By extension, this is also why, IMO, its important to keep AI generated code out of open source/free software projects.
The recent rulings on copyright though also need to be further tested, different judges may have different ideas on what "significant human contribution" looks like. The only thing we know for certain is that the prompt doesn't count.
My guess is that instead of enforcing via copyright, companies will use contracts & trade secret laws. Source code and algorithms counts as a trade secret, so in your example copyright doesn't even matter, the employee would be liable for stealing trade secrets.
AI generated code slowly stripping the ability of a project to enforce copyright protections though is a much bigger risk for free software.
re: binary attestation: "Whether the server rejects that outright or just logs it is an open question"
...what we did at Snap was just wait for 8-24 hours before acting on a signal, so as not to provide an oracle to attackers. Much harder to figure out what you did that caused the system to eventually block your account if it doesn't happen in real-time.
(Snap's binary attestation is at least a decade ahead of this, fwiw)
What a cesspool. So this is the power of being 80x more productive, having infinite llm usage quota?
No wonder they had to let Satan take the wheel and went 100% vibe code.
Thanks for making a point, llms are a disgrace
Probably an unpopular opinion but Anthropic are too popular for their own good.
1. They are loved, and for good reasons, Sonnet 4 was groundbreaking but Opus 4.6 was for many a turning point in realizing Agentic SDLC real potential. People moved from Cursor to Claude Code in droves, they loved the CLI approach (me too), and the LOVED the subsidized $200 max pro plan (what's not to love, pay $200 instead of $5000 to Cursor...) They are the underdog, the true alternative to "evil" OpenAI or "don't be evil" Google, really standing up against mass surveillance or use of AI for autonomous killing machines. They are standing for the little guy, they are the "what OpenAI should have been" (plus they have better models...) They are the Apple of the AI era.
2. They are too loved, so loved that it protects them from legitimate criticism. They make GitHub's status page look good, and they make comcast customer service look like Amazon's. (At least Comcast has customer service), They are "If Dario shoots a customer in the middle of 5th avenue it won't hurt their sales one bit" level of liked. The fact they have the best models (for now) might be their achilles heel, because it hides other issues that might be in the blindspot. And as soon as a better model comes out from a competitor (and it could happen... if you recall OpenAI were the undisputed kinds with GPT 4o for a bit) these will become much more obvious.
3. This can hurt them in the long run. Eventually you can't sustain a business where you have not even 2 9s of SLA, can't handle customer support or sales (either with humans or worse for them - if they can't handle this with AI how do they expect to sell their own dream where AI does everything?). I'm sure they'll figure it out, they have huge growth and these are growth pains, but at some point, if they don't catch up with demand, the demand won't stay there forever the moment OpenAI/Google/someone else release a better model.
4. They inadvertently made all of the cybersecurity sector a potential enemy. Yes, all of them use Anthropic models, and probably many of them use Claude Code, but they know they might be paying the bills of their biggest competitor. Their shares drop whenever Anthropic even hints of a new model. Investors cut their valuations because they worry Anthropic will eat them for breakfast. I don't know about you, but if you ask me, having the people who live and breath security indirectly threatened by you, is not the best thing in the world, especially when your source code is out in the open for them to poke holes in...
5. the SaaS pocalypse - many of Claude Code's customers are... SaaS companies, that the same AI is "going to kill", again, if there was another provider that showed a bit more care about the entire businesses it's going to devour, if they also had even marginally better models... would the brand loyalty stay?
Side note: I'm an Claude Enterprise customer, I can't get a human to respond to anything, even using the special "enterprise support" methods, and I'm not the only one, I know people who can't get a sales person, not to mention support, to buy 150 + seats (Anthropic's answer was - release self serve enterprise onboarding, which by the way is "pay us $20 which does not include usage, usage is at market prices, same as getting an API key", you pay for convenience and governance, p.s. you can't cancel enterprise, it's 20 seats min, for 1 year, in advance, so make sure you really need it, the team plan is great for most cases but it lacks the $200 plan, only the $100 5x plan).
Well, as a general rule, I don't do business with people who lie to me.
You've got a business, and you sent me junk mail, but you made it look like some official government thing to get me to open it? I'm done, just because you lied on the envelope. I don't care how badly I need your service. There's a dozen other places that can provide it; I'll pick one of them rather than you, because you've shown yourself to be dishonest right out of the gate.
Same thing with an AI (or a business that creates an AI). You're willing to lie about who you are (or have your tool do so)? What else are you willing to lie to me about? I don't have time in my life for that. I'm out right here.
Out of curiosity, given two code submissions that are completely identical—one written solely by a human and one assisted by AI—why should its provenance make any difference to you? Is it like fine art, where it’s important that Picasso’s hand drew it? Or is it like an instruction manual, where the author is unimportant?
Similarly, would you consider it to be dishonest if my human colleague reviewed and made changes to my code, but I didn’t explicitly credit them?
As an attorney, I know copyright law. (This is not legal advice.) There's nothing about copyright law that says you have to credit an AI coding agent for contributing to your work. The person receiving the code has to perform their due diligence in any case to determine whether the author owns it or has permission from the owner to contribute it.
Can you back this up with legal precedence? To my knowledge, nothing of the sort has been ruled by the courts.
Additionally, this raises another big issue. A few years ago, a couple guys used software (what you could argue was a primitive AI) to generated around 70 billion unique pieces of music which amounts to essentially every piece of copyrightable music using standard music scales.
Is the fact that they used software to develop this copyrighted material relevant? If not, then their copyright should certainly be legal and every new song should pay them royalties.
It seems that using a computer to generate results MUST be added as an additional bit of analysis when it comes to infringement cases and fair use if not a more fundamental acknowledgement that computer-generated content falls under a different category (I'd imagine the real argument would be over how much of the input was human vs how much was the system).
Of course, this all sets aside the training of AI using copyrighted works. As it turns out, AI can regurgitate verbatim large sections of copyrighted works (up to 80% according to this study[0]) showing that they are in point of fact outright infringing on those copyrights. Do we blow up current AI to maintain the illusion of copyright or blow up current copyright law to preserve AI?
You're asking a lot of very good and thoughtful questions, but none are directly related to the immediate issue, which is "do I have to credit the AI model?".
Why does the provenance make any difference? Let me increase your options. Option 1: You completely hand-wrote it. Option 2: You were assisted by an AI, but you carefully reviewed it. Option 3: You were assisted by an AI (or the AI wrote the whole thing), and you just said, "looks good, YOLO".
Even if the code is line-for-line identical, the difference is in how much trust I am willing to give the code. If I have to work in the neighborhood of that code, I need to know what degree of skepticism I should be viewing it with.
That's the thing. As someone evaluating pull requests, should you trust the code based on its provenance, or should you trust it based on its content? Automated testing can validate code, but it can't validate people.
ISTM the most efficient and objective solution is to invest in AI more on both sides of the fence.
In the future, that may be fine. We're not in that future yet. We're still at a place where I don't fully trust AI-only code to be as solid as code that is at least thoroughly reviewed by a knowledgeable human.
(Yes, I put "AI-only" and "knowledgeable" in there as weasel words. But I think that with them, it is not currently a very controversial case.)
You are spamming the whole fucking thread with the same nonsense. It is instructed to hide that the PR was made via Claude Code. I don't know why people who are so AI forward like yourself have such a problem with telling people that they use AI for coding/writing, it's a weirdly insecure look.
what's insecure about it? if it is up to the institution to make that decision - you can still do it. Claude is not stopping you from making that decision
[0]: https://github.com/chatgptprojects/claude-code/blob/642c7f94...
For a company calling chinese companies out for distillation attacks on their models, this very much looks like a distillation attack against human maintainers, especially when combined with the frustration detector.
[0] https://ai-act-service-desk.ec.europa.eu/en/ai-act/article-5...
https://code.claude.com/docs/en/settings#attribution-setting...
* The authors made the code very broad to improve its ability to achieve the stated goal
* The authors have an unstated goal
I think it's healthy to be skeptical but what I'm seeing is that the skeptics are pushing the boundaries of what's actually in the source. For example, you say "says on the tin" that it "pretends to be human" but it simply does not say that on the tin. It does say "Write commit messages as a human developer would" which is not the same thing as "Try to trick people into believing you're human." To convince people of your skepticism, it's best to stick to the facts.
"includeCoAuthoredBy": false,
in your settings.json.
~/.claude/settings.json
The rest of the prompt is pretty clear that it's talking about internal use.Claude Code users aren't the ones worried about leaking "internal model codenames" nor "unreleased model opus-4-8" nor Slack channel names. Though, nobody would want that crap in their generated docs/code anyways.
Seems like a nothingburger, and everyone seems to be fantasizing about "undercover mode" rather than engaging with the details.
Needing to flag nontrivial code as generated was standard practice for my whole career.
If this is not the case you should not be sending it to public repos for review at all. It is rude and insulting to expect the people maintaining these repos to review code that nobody bothered to read.
The difference here is that the generator is a non-deterministic LLM and you can't reason about its output the same way.
No. I don't want to test and pick through your shitty LLM generated code. If I wanted the entire code base to be junk, it'd say so in the readme.
This is not at all the case with LLM-generated code - mostly because you can't regenerate it even if you wanted to, as it's not deterministic.
That said, I do agree that LLM code is different enough from human code (even just in regards to potential copyright worries) that it should be mentioned that LLMs were used to create it.
Replace gRPC compiler with LLM. Can you reproduce? (probably not 100%). Can anybody fix it short of throwing more english phrases like "DO NOT", "NEVER", "Under No Circumstances"?
Probably not.
How about compiler?
How? LSTM?
The following comment in the blog post
generates a .._string.go file which contains a '.String()' method.I would find it very reasonable to commit that with 'Co-Authored-By: stringer v0.1.0' or such.
Or 'sed s/a/b/g' and 'Co-Authored-By: sed'
Arguably snippet collections belong to this genre.
AI and humans are not the same as authors of PRs. As an obvious example: one of the important functions of the PR process is to teach the writer about how to code in this project but LLMs fundamentally don't learn the same way as humans so there's a meaningful difference in context between humans and AIs.
If a human takes the care to really understand and assume authorship of the PR then it's not really an issue (and if they do, they could easily modify the Claude messages to remove "generated by Claude" notes manually) but instead it seems that Claude is just hiding relevant context from the reviewer. PRs without relevant context are always frustrating.
I use good ol' C-x M-c M-butterfly.
https://xkcd.com/378/
I don’t think that’s necessarily the case. Exposure and discovery aren’t that tightly correlated. Maybe there’s a small effect, but I think it is outweighed by the fact that blast radius and spread is reduced while buying time for discovery.
At least at my workplace though, it's just assumed now that you are using the tools.
In commercial settings you are often required to label your produce and inform about things like 'Made in China' or possible adverse effects of consumption.
I mean, of course I would read most of the code during review, but as a human, I often skip things by mistake
hmm gotta try that
But at this point i am more curious if git will continue to be the best tool.
But for me at least, a tool like Git seems pretty essential for inspecting changes and deciding which to keep, which to reroll, and which to rewrite. (I'm not particularly attached to Git but an interface like Magit and a nice CLI for inspecting and manipulating history seem important to me.)
What are you imagining VCS software doing differently that might play nicer with LLM agents?
Almost like writing “Code was created with the help of IntelliSense”.
It'll also become more important to know what code was actually written by humans.
I don't understand why people consider Claude-generated code to be their own. You authored the prompts, not the code. Somehow this was never a problem with pre-LLM codegen tools, like macro expanders, IPC glue, or type bundle generators. I don't recall anybody desperately removing the "auto-generated do not edit" comments those tools would nearly always slap at the top of each file or taking offense when someone called that code auto-generated. Back in the day we even used to publish the "real" human-written source for those, along with build scripts!
Ideally, if I contribute to any codebase, what needs to be judged is the resulting code. Is it up to the project's standards ? Does the maintainer have design objections ?
What tool you use shouldn't matter, be it your IDE or your LLM.
But that also means you should be accountable for it, you shouldn't defend behind "But Claude did this poorly, not me !", I don't care (in a friendly way), just fix the code if you want to contribute.
The big caveat to this is not wanting AI-Generated code for ideological reasons, and well, if you want that you can make your contributors swear they wrote it by themselves in the PR text or whatever.
I'm not really sure how to feel about this, but I stand by my "the code is what matters" line.
Since AI tools are constantly obsoleted, generate different output each run, and it is often impossible to run them locally, the input prompts are somewhat useless for everyone but the initial user.
I regularly have tool-generated commits. I send them out with a reference to the tool, what the process is, how much it's been reviewed and what the expectation is of the reviewer.
Otherwise, they all assume "human authored" and "human sponsored". Reviewers will then send comments (instead of proposing the fix themselves). When you're wrangling several hundred changes, that becomes unworkable.
I don't meant this as a drive by bazinga either, the practice of copying code or thinking you understand it when you don't is nothing new
Absolutely. That would be hilarious.
If your linter is able to action requests, then it probably makes sense to add too.
This is also useful for keeping your prompts commit-sized, which in my experience gives much better results than just letting it spin or attempting to one-shot large features.
[0]: https://www.jvt.me/posts/2026/02/25/llm-attribute/
Ah, so you kinda maybe sorta absolve yourself of culpability (but not really — "I didn't know this was copyrighted material" didn't grant you copyright), and simultaneously make fixing the potentially compromised codebase (someone else's job, hopefully) 100x harder because the history of which bits might've been copied was never kept.
Solid advice! As ethical as it is practical.
By the same measure, junkyards should avoid keeping receipts on the off chance that the catalytic converters some randos bring in after midnight are stolen property.
Better not document it.
One little trick the legal folks don't want you to know!
Kinda, yeah. If I automatically apply lint suggestions, I would title my commit "apply lint suggestions".
The point isn't to hijack accountability. It's free publicity, like how Apple adds "Sent from my IPhone."
co-authoring doesn't hide your authorship
if I see someone committing a blatantly wrong code, I would wonder what tool they actually used
In some jurisdictions (e.g. the UK) the law is already clear that you own the copyright. In the US it is almost certain that you will be the author. The reports of cases saying otherwise I have been misreported - the courts found the AI could not own the copyright.
> The question is whether anyone has or if whatever content generated by a LLM simply does not constitute a work and is thus outside the entire copyright law.
Its is going to vary with copyright law. In the UK the question of computer generated works is addressed by copyright law and the answer is "the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken"
Its also not a simple case of LLM generated vs human authored. How much work did the human do? What creative input was there? How detailed were the prompts?
In jurisdictions where there are doubts about the question, I think code is a tricky one. If the argument that prompts are just instructions to generate code, therefore the code is not covered by copyright, then you could also argue that code is instructions to a compiler to generate code and the resulting binary is not covered by copyright.
[1] https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...
Thaler v. Perlmutter: The D.C. Circuit Court affirmed in March 2025 that the Copyright Act requires works to be authored "in the first instance by a human being," a ruling the Supreme Court left intact by declining to hear the case in 2026.
And in the US constitution,
https://constitution.congress.gov/browse/article-1/section-8...
Authors and inventors, courts have ruled, means people. Only people. A monkey taking a selfie with your camera doesn't mean you own a copyright. An AI generating code with your computer is likewise, devoid of any copyright protection.
The ruling says that the LLM cannot be the author. It does not say that the human being using the LLM cannot be the author. The ruling was very clear that it did not address whether a human being was the copyright holder because Thaler waived that argument.
the position with a monkey using your camera is similar, and you may or may not hold the copyright depending on what you did - was it pure accident or did you set things up. Opinions on the well known case are mixed: https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...
Where wildlife photographers deliberately set up a shot to be triggered automatically (e.g. by a bird flying through the focus) they do hold the copyright.
https://www.copyright.gov/ai/
AI generated code has no copyright. And if it DID somehow have copyright, it wouldn't be yours. It would belong to the code it was "trained" on. The code it algorithmically copied. You're trying to have your cake, and eat it too. You could maybe claim your prompts are copyrighted, but that's not what leaked. The AI generated code leaked.
> the Copyright Office concludes that existing legal doctrines are adequate and appropriate to resolve questions of copyrightability. Copyright law has long adapted to new technology and can enable case-by- case determinations as to whether AI-generated outputs reflect sufficient human contribution to warrant copyright protection. As described above, in many circumstances these outputs will be copyrightable in whole or in part—where AI is used as a tool, and where a human has been able to determine the expressive elements they contain. Prompts alone, however, at this stage are unlikely to satisfy those requirements.
So the TL;DR basically implies pure slop within the current guidelines outlined in conclusions is NOT copyrightable. However collaboration with an AI copyrightability is determined on a case by case basis. I will preface this all with the standard IANAL, I could be wrong etc, but with the concluding language using "unlikely" copyrightable for slop it sounds less cut and dry than you imply.
You have no idea how bad this leak is for Anthropic because with the copyright office, you have a DUTY TO DISCLOSE any AI generated work, and it is fully RETROACTIVE. And what is part of this leak? undercover.ts. https://archive.is/S1bKY Where Claude is specifically instructed to HIDE DISCLOSURE of AI generated work.
That's grounds for the copyright office and courts to reject ANY copyright they MIGHT have had a right to. It is one of the WORST things they could have done with regard to copyright.
https://www.finnegan.com/en/insights/articles/when-registeri...
I'm interpreting your most recent reply to me as an implication that I'm taking the conclusions you yourself linked out of context. I'm trying to give the benefit of the doubt here, but the 3 linked PDF documents aren't "a mountain of evidence" supporting your argument. Maybe I missed something in one of those documents (very possible), but the conclusions are not how you imply.
Whether or not a specific git commit message correctly sites Claude usage or not may further muddy the waters more than IP lawyers are comfortable with at this time (and therefore add inherent risk to current and future copyright claims of said works), but those waters were far from crystal clear in the first place.
Again, IANAL, but from my limited layman perspective it does not appear the copyright office plans to, at this moment in time, concisely reject AI collaborated works from copyright.
Your most recent link (Finnegan) is from an IP lawyer consortium that says it's better to include attribution and disclosure of AI to avoid current and future claim rejections. Sounds like basic cover-your-ass lawyer speak, but I could be wrong.
Full disclosure: I primarily use AI (or rather agentic teams) as N sets of new eyeballs on the current problem at hand, to help debug or bounce ideas off of, so I don't really have much skin in this particular game involving direct code contributions spit out by LLMs. Those that have any risk aversion, should probably proceed with caution. I just find the upending of copyright (and many other) norms by GenAI morbidly fascinating.
I was not aware of that. WHo has that duty and when do they have it?
https://news.ycombinator.com/item?id=47594044
That comment is spot on. Claude adding a co-author to a commit is documentation to put a clear line between code you wrote and code claude generated which does not qualify for copyright protection.
The damning thing about this leak is the inclusion of undercover.ts. That means Anthropic has now been caught red handed distributing a tool designed to circumvent copyright law.
It becomes legally challenging with regards to ownership if I ever use work equipment for a personal project. If it later takes off they could very well try to claim ownership in its entirety simply because I ran a test once (yes, there's a while silicon valley season for it).
I don't know if they'd win, but Anthropic absolutely would be able to claim the creation of that code was done on their hardware. Obviously we aren't employees of theirs, though we are customers that very likely never read what we agreed to in a signup flow.
Anthropic's user agreement does not have a similar agreement.
I don't know of ant precedent where the code was literally generated on someone else's system. Its an open question whether that implies any legal right to the work and I could pretty easily see a court accepting the case.
Interesting!
Plot twist: Chinese competitors end up developing real, useful versions of Claude's fake tools.
Again, I don’t care about them.
every delay to AGI results in deaths that AGI could have prevented. we are talking millions of deaths for, say, just a year's delay.
- you are assuming that AGI is just around the corner and that scaling up language models is the path to get there
- you can make this argument about basically anything (nuclear power, tuberculosis medication, free healthcare). I’d say the burden of proof is on you to back up your extraordinary claim with extraordinary evidence.
Uhm, that's not what Hollywood told me. I trust the screenwriters of "Terminator" more than I trust your anonymous forum comment.
Sure, that's what AGI would be used for /s
In other news, we are not even close to AGI and even with the current experimental technology, frontier AI model companies are already fighting to help departments of war, which actually results in the most deaths. What makes you think AGI would be used for not leading to the same millions of deaths?
Everyone else is just gaming engagement metrics and benchmarks.
(I know you know this, since you submitted it! but others might want to know)
thank you so much for having built and shared this
It did not have a copy of the leaked code...
Anthropic thinking 1) they can unring this bell, and 2) removing forks from people who have contributed (well, what little you can contribute to their repo), is ridiculous.
---
DMCA: https://github.com/github/dmca/blob/master/2026/03/2026-03-3...
GitHub's note at the top says: "Note: Because the reported network that contained the allegedly infringing content was larger than one hundred (100) repositories, and the submitter alleged that all or most of the forks were infringing to the same extent as the parent repository, GitHub processed the takedown notice against the entire network of 8.1K repositories, inclusive of the parent repository."
They constantly love to talk about Claude Code being "100%" being vibe coded...and the US legal system is leaning towards that not being copyrightable.
It could still be a trade secret, but that doesn't fall under a DMCA take down.
The whole thing is a legal mess. How do you know the LLM did not reproduce existing code? There is an ongoing legal battle in German between GEMA and OpenAI because ChatGPT reproduced parts of existing song lyrics. A court in Munich has found that this violates German copyright law.
A copyright over code means that ONLY you can use that code, and nobody else; otherwise, you can sue them. For example, if you are an arist, you want to protect your IP this way.
Yes, AI generated code is not copyrightable but so is most code in general. It is very hard to truly get a copyright for a piece of code. But just because you don't have copyright to something doesn't mean it's not your property.
For example, you can buy several movies on DVD and those DVDs will still be your property even though you don't have copyright and if someone does steal those DVDs, it will be considered theft of your property. Similarly, just because the code is AI-generated/not copyrightable, doesn't mean others can just steal it.
Think about it - so many codebases are not legally protected as copyrighted material but are absolutely protected by IP laws and enforced by the companies that own them.
Huh? Normal property law is plainly not applicable to a non-rival good like information (unlike for instance a physical DVD: if someone takes a DVD from me, I don’t have it anymore). “Intellectual property” is, but it is not so much a legal regime as confusing shorthand for a number of distinct ones:
- Trademark law, which applies to markings on copies rather than copies themselves;
- Trade secret law, which stops applying when the information escapes into the wild through the secret-holder’s own actions;
- Patent law, which definitionally only applies to public knowledge as an incentive to not keep it secret instead;
- Publicity rights, which only apply to depictions or discussions of natural persons;
- Moral rights, which are mostly about being recognized as the author and even in their strongest incarnations do not restrict unmodified copies;
- Database right, which isn’t applicable as we’re not talking about a compendium of things, and anyway does not exist in the US and most other places outside the EU;
- Copyright, which you’ve conceded is not applicable here.
There’s no “intellectual property” distinct from these things, and none of them are relevant.
If your code was generated by you and you store it in your system and have property rights over it, you can enforce legal actions even without holding a copyright over the code.
In general, it is kind of weird to want to copyright code. How do you patent a for-loop for example
https://patents.google.com/patent/US9583163B2/en
> How do you patent a for-loop for example
Anthropic really needs to embrace it
No shit they have secrets. I have secrets too. That doesn't make it ok for me to deceive you in any way.
How would you feel if I deceived you and my excuse was "oh I was just trying some new secret technique of mine"?
How did we get to this point where we let enormously powerful companies get away with more than individuals?
"Write commit messages as a human developer would — describe only what the code change does."
Writing and reading paragraphs of design discussion in a commit message is not something that seems common.
And of course tickets can be private, so even if the data survived migration, you may not have access to it (principle of least privilege and all that).
What you're describing here is a design. The most important parts of a design are the decisions and their reasoning.
e.g. "we decided on tool/library pattern X over tool/library/pattern Y because Z" – that is a design, usually discussed outside (and before) a commit message.
You discuss these decisions with others, document the discussion and decision, and then you have a design and can start writing code.
Let me ask you this: suppose you have a task that needs to be done eventually, and you want to write down some ideas for it, but don't want to start coding right now. Where do you put those ideas? How do you link them to that specific task?
Random example:
Provide a new syscall which has the only purpose to yield the CPU after the kernel granted a time slice extension.
sched_yield() is not suitable for that because it unconditionally schedules, but the end of the time slice extension is not required to schedule when the task was already preempted. This also allows to have a strict check for termination to catch user space invoking random syscalls including sched_yield() from a time slice extension region.
From 99d2592023e5d0a31f5f5a83c694df48239a1e6c
In your example, for example, where was the issue tracked before the code was written? The format you linked makes it difficult to get the history of the issue.
Let me ask you this: suppose you have a task that needs to be done eventually, and you want to write down some ideas for it, but don't want to start coding right now. Where do you put those ideas? How do you link them to that specific task?
Email is the review process, and commits contain enough information that git blame can get you a reasoning - it doesn't require you checking the email archive. Rather than a dead ticket that no longer exists.
I can also supply you a list of companies that make use of git's builtin features if you like. But thats probably not relevant to discussing management techniques.
https://cgit.freebsd.org/src/commit/?id=407b1e4980189252fade...
You can find more example there
https://cgit.freebsd.org/src/log/?showmsg=1
VS Code has a setting that promises to change the prompt it uses to generate commit messages, but it mostly ignores my instructions, even very literal ones like “don’t use the words ‘enhance’ or ‘improve’”. And oddly having it set can sometimes result in Cyrillic characters showing up at the end of the message.
Ultimately I stopped using it, because editing the messages cost me more time than it saved.
/rant
> Commit f9205ab3 by dkenyser on 2026-3-31 at 16:05:
> Fixed the foobar bug by adding a baz flag - dkenyser
Because it already identified you in the commit description. The reason to add a signature to the message is that someone (or something) that isn't you is using your account, which seems like a bad idea.
[edit] Never mind, find in page fail on my end.
- "Fix bug found while testing with Claude Capybara"
- "1-shotted by claude-opus-4-6"
- "Generated with Claude Code"
- "Co-Authored-By: Claude Opus 4.6 <…>"
This makes sense to me about their intent by "UNDERCOVER"
https://code.claude.com/docs/en/settings#attribution-setting...
The frustration regex is funny but honestly the right call. Running an LLM call just to detect "wtf" would be ridiculous.
KAIROS is what actually caught my attention. An always-on background agent that acts without prompting is a completely different thing from what Claude Code is today. The 15 second blocking budget tells me they actually thought through what it feels like to have something running in the background while you work, which is usually the part nobody gets right.
Tangentially, I wonder if the world trade federation or the Washington tennis foundation have any projects on GitHub :)
I love that it only supports English. AI bubble in a nutshell.
The pet you get is generated based off your account UUID, but the algorithm is right there in the source, and it's deterministic, so you can check ahead of time. Threw together a little app to help, not to brag but I got a legendary ghost https://claudebuddychecker.netlify.app/
(I didn't think to include a UUID checker though - nice touch)
On that note, this article is also pretty obviously AI-generated and it's unfortunate the author didn't clean it up.
Edit: Everyone is responding "comments are good" and I can't tell if any of you actually read TFA or not
> “BQ 2026-03-10: 1,279 sessions had 50+ consecutive failures (up to 3,272) in a single session, wasting ~250K API calls/day globally.”
This is just revealing operational details the agent doesn't need to know to set `MAX_CONSECUTIVE_AUTOCOMPACT_FAILURES = 3`
Why? Agents may or may not read docs. It may or may not use skills or tools. It will always read comments "in the line of sight" of the task.
You get free long term agent memory with zero infrastructure.
Only being half ironic with this. I generally find that people somehow magically manage to understand how to be materially helpful when the subject is a helpless LLM. Instead of pointing it to a random KB page, they give it context. They then shorten that context. They then interleave context as comments. They provide relevant details. They go out of their way to collect relevant details. Things they somehow don't do for their actual colleagues.
This only gets worse when the LLM captures all that information better than certain human colleagues somehow, rewarding the additional effort.
suddenly everyone cares about data hygiene. But it’s not like this shouldn’t have always been a priority
There's a good reason why we didn't though: because we didn't see any obvious value in it. So it felt like a waste of time. Now it feels like time well spent.
"Self-descriptive code doesn't need comments!" always gets an eye-roll from me
Or how would you name methods and variables to explain why some payment reconciliation process skips matching for transactions under 0.50 EUR and just auto-approves them, because the external payment processor rounds differently than the internal ledger at sub-euro amounts, creating mismatches that were flooding the finance team's exception queue in 2013, explained more under Jira issue ZXSV-12456 and more details are known by j.doe@myorg.com. The threshold was chosen after analyzing six months of false positives, when it's any higher someone being undercharged doesn't get caught. I don't think autoApproveThreshold = 0.50 or anything like that would get the full context across, even if the rules themselves are all code.
I think surely you can have both! Code should explain itself as often as possible, but when you hit a wall due to some counter-intuitive workarounds being needed, or some business rules or external considerations that you need to keep track of, then comments also make sense. Better than just putting everything in a Jira issue somewhere, given that it often won't be read by you or others and almost certainly will not be read by any AI agents (unless you have an MCP or something, but probably uncommon), or spending hours trying to get the code to explain something it will never explain well. I've had people ask me about things that are covered in the README.md instead of reading it.
Gonna try and use that throughout my life. Thanks!
This is a good goal. You should strive to make the code explain itself. To write code that does not need comments.
You will fail to reach that goal most of the time.
And when you fail to reach that goal, write the dang comments explaining why the code is the way that it is.
I'm gonna note down my reasons for doing things and other information I deem useful, and if some other dipshit 5 years from now when I've moved on comes along and starts changing everything up without keeping the comments up to date that's their problem not mine. There was never anything wrong with my comments, the only thing that's wrong is the dipshit messing things up.
Doesn't matter what I do, the dipshit is going to mess everything up anyway. Those outdated comments will be the least of their worries.
The “dipshit” doesn’t mess everything up for fun. They don’t understand the comments written by the previous “dipshit” and thus are unable to update the comments.
Here's what I think. I think you guys heard the "self-documenting code" BS and ate it up, and now you're grasping at straws to defend your cargo cult position, inventing these "problems" to justify it.
If you're looking at some code and there's a comment saying something that doesn't make sense to you, maybe that's a clue that you're missing a puzzle piece and should take a step back maybe talk to some people to make sure you're not messing things up? Maybe, for a non-dipshit, that comment they don't understand could actually be helpful if they put some effort into it?
Also just to be clear I don't think this is a likely occurrence unless someone doesn't know squat about the codebase at all - my comments generally assume very little knowledge. That's their whole purpose - to inform someone (possibly me) coming there without the necessary background knowledge.
It just isn't feasible to include the why of everything in the code itself. And it sure as hell is better to include some info as comments than none at all. Otherwise a bug will often be indistinguishable from a feature.
And I don't think dipshits mess things up for fun. I think they just suck. They're lazy and stupid, as most developers are. If I'm there I can use reviews etc to help them suck less, if I'm not they're free to wreck my codebase with reckless abandon and nothing I do will make any difference. I cannot safeguard my codebase against that so there's no point in trying and the fact that this is your argument should make you stop and reconsider your position because it's far fetched as fuck.
IME unfortunately that's not actually the case. It very much is your problem, as the architect of the original system, unless you can get yourself transferred to a department far, far away. I've never managed that except by leaving the company.
To be clear, I don't believe it should be this way, but sadly unless you work in an uncommonly well run company it usually is.
And if anyone has a problem with comments existing it's trivial to find/replace them out of existence. Literally a one minute job, if you actually think the codebase would be better without them.
This is such a humongous non-issue it's crazy man.
Agent is not going to know to look for a file to update unless instructed. Now your file is out of sync. Code comments keeping everything line of sight makes it easy and foolproof.
You don’t have to rely on humans doing it. The agent’s entire existence is built around doing this one mundane task that is annoying but super useful.
Yes, lets blow another 5-10k a project/month on tokens to keep the comments up to date. The fact ai still cannot consistently refactor without leaving dead code around even after a self review does not give me confidence in comments…
Comments in code are often a code smell. This is an industry standard for a reason and isnt because of staleness. If u are writing a comment, it means the code is bad or there is irreducible complexity. It is about good design. Comments everywhere are almost always a flag.
Note, language conventions are not the same.
That's revealing waaaay more than the agent needs to know.
Seems to me like everyone's just grasping at straws to nitpick every insignificant little thing.
Its also annoying to have to go through this stack
code -> blame -> commit message -> jira ticket -> issue in sales force...
Or the even better "fixes bug NNNNN" where the bug tracking system referenced no longer exists.
Digging through other systems (if they exist) to find the nugget in an artifact is a problem for humans too.
I think a big question is whether one wants your agent to know the reason for all the reasons for guidelines you issue or whether you want the agent to just follow the guidelines you issue. Especially, giving an agent the argument for your orders might make the agent think that can question and so not follow those arguments.
Comments are ultimately so you can understand stuff without having to read all the code. LLMs are great when you force them to read all code, and comments only serve to confuse. I'd say the opposite been true in my experience, if you're not forcing LLMs to not have any comments at all (and it can actually skip those, looking at you Gemini), you're doing agent coding wrong.
They didn't expect to leak their source code.
It's hardly a trade secret, what value is this to a competitor?
I suspect that's the logical endpoint of trying to provide everything as context to an agent. Why use a separate markdown file and have to waste extra tokens explaining what part of the codebase something applies to when you can just put it right there in the code itself?
Unfortunately in many bundlers making a mistake like this is as easy as an agent deleting “process.env[‘ENV’] === ‘debug’” which they’ll gladly do if you point them at a production or staging environment and ask them to debug the stripped/compiled/minified code.
I’d argue that in this case, it isn’t. Exhibit 1 (from the earlier thread): https://github.com/anthropics/claude-code/issues/22284. The user reports that this caused their account to be banned: https://news.ycombinator.com/item?id=47588970
Maybe it would be okay as a first filtering step, before doing actual sentiment analysis on the matches. That would at least eliminate obvious false positives (but of course still do nothing about false negatives).
- Claude Chat: built like it's 1995, put business logic in the button click() handler. Switch to something else in in the UI and a long running process hard stops. Very Visual Basic shovelware.
- Claude Cowork: same but now we're smarter, if you change the current convo we don't stop the underlying long-running process. 21st century FTW!
- Claude Code: like chat, but in the CLI
- Claude Dispatch: an actual mobile client app, not the whole thing bundled together.
- Daemon mode: proper long-running background process, still unreleased.
So much for langchain and langraph!! I mean if Anthropic themselves arent using it and using a prompt then what’s the big deal about langchain
Langgraph is for multi-agent orchestration as state graphs. This isn't useful for Claude Code as there is no multi-agent chaining. It uses a single coordinator agent that spawns subagents on demand. Basically too dynamic to constrain to state graphs.
What's the value add over doing it with just Python code? I mean you can represent any logic in terms of graphs and states..
Other than that I’m not too sure.
" ...accidentally shipping your source map to npm is the kind of mistake that sounds impossible until you remember that a significant portion of the codebase was probably written by the AI you are shipping.”
In the span of basically a week, they accidentally leaked Mythos, and then now the entire codebase of CC. All while many people are complaining about their usage limits being consumed quickly.
Individually, each issue is manageable (Because its exciting looking through leaked code). But together, it starts to feel like a pattern.
At some point, I think the question becomes whether people are still comfortable trusting tools like this with their codebases, not just whether any single incident was a mistake.
The only thing I found interesting about this leak is just how much of a rats nest the code base is. Like it actually feels vibe coded without a shred of intelligent architecture behind it.
Regardless, you can't beat the subscription and model access despite the state of the code base, so I still use Claude Code daily and love it.
Two months later it was CVE after CVE.
Power(money) lies with NVDA and people who can best harness this power.
Interesting based on the other news that is out.
The mechanism is a build pipeline issue. Bun generates source maps by default, and someone didn't exclude the .map file from the npm publish. There's an open Bun issue (oven-sh/bun#28001) about this exact behavior. One missing line in .npmignore or the package.json files field. Same category of error as the Axios compromise earlier this week — npm packaging configuration is becoming a recurring single point of failure across the ecosystem.
The contents are more interesting from a security architecture perspective. The anti-distillation system (injecting fake tool definitions to poison training data scraped from API traffic) is a defensive measure that only works when its existence is secret. Now that it's public, anyone training on Claude Code API traffic knows to filter for it. The strategic value evaporated the moment the .map file hit the CDN.
The undercover mode discussion is being framed as deception, but the actual security question is narrower: should AI-authored contributions to public repositories carry attribution? That's an AI identity disclosure question that the industry hasn't settled. The code shows Anthropic made a specific product decision — strip AI attribution in public commits from employee accounts. Whether that's reasonable depends on whether you think AI authorship is material information for code reviewers.
The frustration regex is the least interesting finding technically but the most revealing culturally. A company with frontier-level NLP capability chose a regex over an inference call for sentiment detection. The engineering reason is obvious (latency and cost), but it tells you something about where even AI companies draw the line on using their own models.
Are you referencing the use of Claude subscription authentication (oauth) from non-Claude Code clients?
That’s already possible, nothing prevents you from doing it.
They are detecting it on their backend by profiling your API calls, not by guarding with some secret crypto stuff.
At least that’s how things worked last week xD
https://alex000kim.com/posts/2026-03-31-claude-code-source-l...
Ah, it seems that Bun itself signs the code. I don't understand how this can't be spoofed.
They are most likely using these as post-fact indicators and have automation they kicks in after a threshold is reached.
Now that the indicators have leaked, they will most likely be rotated.
They can't really do that. Now they have no way to distinguish "this is a user of a non updated Claude code" from "this is a user of a Claude code proxy".
Not only that, wouldn't allow other CLIs to be used either.
https://fortune.com/2026/01/29/100-percent-of-code-at-anthro...
> Right now for most products at Anthropic it's effectively 100% just Claude writing
- Mike Krieger, chief product officer of Anthropic
/\b(wtf|wth|ffs|omfg|shit(ty|tiest)?|dumbass|horrible|awful| piss(ed|ing)? off|piece of (shit|crap|junk)|what the (fuck|hell)| fucking? (broken|useless|terrible|awful|horrible)|fuck you| screw (this|you)|so frustrating|this sucks|damn it)\b/
Personally, I'm generally polite even towards AI and even when frustrated. I simply point out the its mistakes instead of using emotional words.
I don’t get it. What does this mean? I can use Claude code now without anyone knowing it is Claude code.
it's written to _actively_ avoid any signs of AI generated code when "in a PUBLIC/OPEN-SOURCE repository".
Also, it's not about you. Undercover mode only activates for Anthropic employees (it's gated on USER_TYPE === 'ant', which is a build-time flag baked into internal builds).
I'm still inclined to think people might be overreacting to that bit since it seems to be for anthropic-only to prevent leaking internal info.
But I did read the prompt and it did say hide the fact that you are AI.
But, I also get Anthropic's side that when they're contributing they don't want their internals leaked. If it had been left at that, that's fine, but having it pretend like it's not AI at all rubs me a little bit the wrong way. Why try to hide it?
But none of the other agents advertise that the commit was done by an agent. Like Codex. Your panic should apply equally to already existing agents like Codex no?
Being written by a LLM is a signal that the submission is of low effort and therefore probably low quality, which then puts the onus on the people reviewing and reading the submission instead of the original generator of the submission. Hence I would classify it as spam.
Open source communities also have rules against LLM generated contributions, for various moral, ethical, or legal reasons.
At this point I would consider any employee of an AI provider to be tainted.
> This was one of the first things people noticed in the HN thread.
> The obvious concern, raised repeatedly in the HN thread
> This was the most-discussed finding in the HN thread.
> Several people in the HN thread flagged this
> Some in the HN thread downplayed the leak
when the original HN post is already at the top of the front page...why do we need a separate blogpost that just summarizes the comments?
Or, more simply: Because folks wanted it enough to upvote it.
Plus there's demand for skilled TS software devs that don't ship your company's roadmap using a js.map
20,000 agents and none of them caught it...
How much approximate savings would this actually be?
To err is human. AI is trained on human content. Hence, to err is AI. The day it stops making mistakes will be the beginning of the end. That would mean the existence of a consciousness that has no weakness. Great if it’s on your side. Terrible otherwise.
AGI is definitely around the corner. Or not.
They would either need to lie about consuming the tokens at one point to use in another so the token counting was precise.
But that does not make sense because if someone counted the tokens by capturing the session it would certainly not match what was charged.
Unless they would charge for the fake tools anyway so you never know they were there
>Is it ironic? Sure. Is it also probably faster and cheaper than running an LLM inference just to figure out if a user is swearing at the tool? Also yes. Sometimes a regex is the right tool.
I'm reading an LLM written write up on an LLM tool that just summarizes HN comments.
I'm so tired man, what the hell are we doing here.
And so now the copy cats can ofc claim this is totally not a copy at all, it's actually Opus. No license violation, no siree!
It's fucking hilarious is what it is, it's just too much.
Does this mean `huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled` is unusable? Had anyone seen fake tool calls working with this model?
:-D
Genius level AI marketing
Granted, there's a small counterargument for mythos which is that it's probably going to be API-only not subscription
They don't want you using your subscription outside of Claude Code. Only API key usage is allowed.
Google also doubled down on this and OpenAI are the only ones who explicitly allow you to do it.
> change the code!!!! The previous comment was NOT ABOUT THE DESCRIPTION!!!!!!! Add to the {implementation}!!!!! This IS controlled BY CODE. *YOU* _MUST_ CHANGE THE CODE!!!!!!!!!!!
The more code gets generated by AI, won’t that mean taking source code from a company becomes legal? Isn’t it true that works created with generative AI can’t be copyrighted?
I wonder if large companies have throught of this risk. Once a company’s product source code reaches a certain percentage of AI generation it no longer has copyright. Any employee with access can just take it and sell it to someone else, legally, right?
The recent rulings on copyright though also need to be further tested, different judges may have different ideas on what "significant human contribution" looks like. The only thing we know for certain is that the prompt doesn't count.
My guess is that instead of enforcing via copyright, companies will use contracts & trade secret laws. Source code and algorithms counts as a trade secret, so in your example copyright doesn't even matter, the employee would be liable for stealing trade secrets.
AI generated code slowly stripping the ability of a project to enforce copyright protections though is a much bigger risk for free software.
Of course with lease intent is a very important concept. I doubt anyone is getting away with what I described.
It’s just interesting stuff to potentially rethink.
...what we did at Snap was just wait for 8-24 hours before acting on a signal, so as not to provide an oracle to attackers. Much harder to figure out what you did that caused the system to eventually block your account if it doesn't happen in real-time.
(Snap's binary attestation is at least a decade ahead of this, fwiw)
Sans the ability to JIT, I don't see non-hardware-assisted binary attestation for Snap and others lasting very long in a post-LLM world.
1. They are loved, and for good reasons, Sonnet 4 was groundbreaking but Opus 4.6 was for many a turning point in realizing Agentic SDLC real potential. People moved from Cursor to Claude Code in droves, they loved the CLI approach (me too), and the LOVED the subsidized $200 max pro plan (what's not to love, pay $200 instead of $5000 to Cursor...) They are the underdog, the true alternative to "evil" OpenAI or "don't be evil" Google, really standing up against mass surveillance or use of AI for autonomous killing machines. They are standing for the little guy, they are the "what OpenAI should have been" (plus they have better models...) They are the Apple of the AI era.
2. They are too loved, so loved that it protects them from legitimate criticism. They make GitHub's status page look good, and they make comcast customer service look like Amazon's. (At least Comcast has customer service), They are "If Dario shoots a customer in the middle of 5th avenue it won't hurt their sales one bit" level of liked. The fact they have the best models (for now) might be their achilles heel, because it hides other issues that might be in the blindspot. And as soon as a better model comes out from a competitor (and it could happen... if you recall OpenAI were the undisputed kinds with GPT 4o for a bit) these will become much more obvious.
3. This can hurt them in the long run. Eventually you can't sustain a business where you have not even 2 9s of SLA, can't handle customer support or sales (either with humans or worse for them - if they can't handle this with AI how do they expect to sell their own dream where AI does everything?). I'm sure they'll figure it out, they have huge growth and these are growth pains, but at some point, if they don't catch up with demand, the demand won't stay there forever the moment OpenAI/Google/someone else release a better model.
4. They inadvertently made all of the cybersecurity sector a potential enemy. Yes, all of them use Anthropic models, and probably many of them use Claude Code, but they know they might be paying the bills of their biggest competitor. Their shares drop whenever Anthropic even hints of a new model. Investors cut their valuations because they worry Anthropic will eat them for breakfast. I don't know about you, but if you ask me, having the people who live and breath security indirectly threatened by you, is not the best thing in the world, especially when your source code is out in the open for them to poke holes in...
5. the SaaS pocalypse - many of Claude Code's customers are... SaaS companies, that the same AI is "going to kill", again, if there was another provider that showed a bit more care about the entire businesses it's going to devour, if they also had even marginally better models... would the brand loyalty stay?
Side note: I'm an Claude Enterprise customer, I can't get a human to respond to anything, even using the special "enterprise support" methods, and I'm not the only one, I know people who can't get a sales person, not to mention support, to buy 150 + seats (Anthropic's answer was - release self serve enterprise onboarding, which by the way is "pay us $20 which does not include usage, usage is at market prices, same as getting an API key", you pay for convenience and governance, p.s. you can't cancel enterprise, it's 20 seats min, for 1 year, in advance, so make sure you really need it, the team plan is great for most cases but it lacks the $200 plan, only the $100 5x plan).
You've got a business, and you sent me junk mail, but you made it look like some official government thing to get me to open it? I'm done, just because you lied on the envelope. I don't care how badly I need your service. There's a dozen other places that can provide it; I'll pick one of them rather than you, because you've shown yourself to be dishonest right out of the gate.
Same thing with an AI (or a business that creates an AI). You're willing to lie about who you are (or have your tool do so)? What else are you willing to lie to me about? I don't have time in my life for that. I'm out right here.
Similarly, would you consider it to be dishonest if my human colleague reviewed and made changes to my code, but I didn’t explicitly credit them?
Additionally, this raises another big issue. A few years ago, a couple guys used software (what you could argue was a primitive AI) to generated around 70 billion unique pieces of music which amounts to essentially every piece of copyrightable music using standard music scales.
Is the fact that they used software to develop this copyrighted material relevant? If not, then their copyright should certainly be legal and every new song should pay them royalties.
It seems that using a computer to generate results MUST be added as an additional bit of analysis when it comes to infringement cases and fair use if not a more fundamental acknowledgement that computer-generated content falls under a different category (I'd imagine the real argument would be over how much of the input was human vs how much was the system).
Of course, this all sets aside the training of AI using copyrighted works. As it turns out, AI can regurgitate verbatim large sections of copyrighted works (up to 80% according to this study[0]) showing that they are in point of fact outright infringing on those copyrights. Do we blow up current AI to maintain the illusion of copyright or blow up current copyright law to preserve AI?
[0] https://arxiv.org/pdf/2603.20957
To begin to answer your questions, I would suggest you study the Copyright Office's report (which is also not law, but their guidance for laypeople as written by their staff lawyers) at https://www.copyright.gov/ai/Copyright-and-Artificial-Intell...
Even if the code is line-for-line identical, the difference is in how much trust I am willing to give the code. If I have to work in the neighborhood of that code, I need to know what degree of skepticism I should be viewing it with.
ISTM the most efficient and objective solution is to invest in AI more on both sides of the fence.
(Yes, I put "AI-only" and "knowledgeable" in there as weasel words. But I think that with them, it is not currently a very controversial case.)
Do you not think it is an overreaction to panic like this if I can do exactly what the undercover mode does by simply asking Claude?