Define policy forbidding use of AI code generators

It's happening slowly all around. It's not obvious because people producing high quality stuff have no incentive at all to mark their changes as AI-generated. But there are also local tools generated faster than you could adjust existing tools to do what you want. I'm running 3 things now just for myself that I generated from scratch instead of trying to send feature requests to existing apps I can buy.

It's only going to get more pervasive from now on.

Can you show these 3 things to us?

For some reason these fully functional ai generated projects that the authors vibe out while playing guitar and clipping their toenails are never open source.

Only the simplest one is open (and before you discount it as too trivial, somehow none of the other ones did what I wanted) https://github.com/viraptor/pomodoro

The others are just too specific for me to be useful for anyone else: an android app for automatic processing of some text messages and a work scheduling/prioritising thing. The time to make them generic enough to share would be much longer than creating my specific version in the first place.

Not sure about parent but you could argue Jetbrains fancy auto complete is AI and generates a substantial portion of code. It runs using a local model and, in my experience, does pretty good at guessing the rest of the line with minimal input (so you could argue 80% of each line was AI generated)

Except this one is (see your sibling).

> the authors vibe out while playing guitar and clipping their toenails

I don't think anyone is claiming that. If you submit changes to a FOSS project and an LLM assisted you in writing them how would anyone know? Assuming at least that you are an otherwise competent developer and that you carefully review all code before you commit it.

The (admittedly still controversial) claim being made is that developers with LLM assistance are more productive than those without. Further, that there is little incentive for such developers to advertise this assistance. Less trouble for all involved to represent it as 100% your own unassisted work.

Not OP, but:

I'm getting towards the end of a vibe coded ZFS storage backend to ganeti that includes the ability to live migrate VMs to another host by: taking snapshot and replicating it to target, pausing VM, taking another incremental snapshot and replicating it, and then unpausing the VM on the new destination machine. https://github.com/linsomniac/ganeti/tree/newzfs

Other LLM tools I've built this week:

This afternoon I built a web-based SQL query editor/runner with results display, for dev/ops people to run read-only queries against our production database. To replace an existing super simple one, and add query syntax highlighting, snippet library, and other modern features. I can probably release this though I'd need to verify that it won't leak anything. Targets SQL Server.

A couple CLI Jira tools to pull a list of tickets I'm working on (with cache so I can get an immediate response, then get updates after Jira response comes back), and tickets with tags that indicate I have to handle them specially.

An icinga CLI that downtimes hosts, for when we do sweeping machine maintenances like rebooting a VM host with dozens of monitored children.

An Ansible module that is a "swiss army knife" for filesystem manipulation, merging the functions of copy, template, file, so you can loop over a list and: create a directory, template a couple files into it, doing a notify on one and a when on another, ensure a file exists if it doesn't already, to reduce duplication of boilerplate when doing a bunch of file deploys. This I will release as a ansible galaxy module once I have it tested a little more.

I vibe-coded my own MySQL-compatible database that performs better than MariaDB, after my agent optimized it for 12 hours. It is also a time-traveling DB and performs better on all benchmarks and the AI says it is completely byzantine-fault-tolerant. Programmers, you had a nice run. /s

Why would you need to carefully review code? That is so 2024. You’re bottlenecking the process and are at a disadvantage when the AI could be working 24/7. We have AI agents that have been trained to review thousands of PRs that are produced by other, generative agents, and together they have already churned out much more software than human teams can write in a year.

AI “assistance” is a short intermediate phase, like the “centaurs” that Garry Kasparov was very fond of (human + computer beat both a human and a computer by itself… until the computer-only became better).

https://en.wikipedia.org/wiki/Advanced_chess

Looks like two commits:

https://github.com/linsomniac/ganeti/commit/e91766bfb42c67ab...

https://github.com/linsomniac/ganeti/commit/f52f6d689c242e3e...

Thanks, I hadn't pushed from my test cluster, check again. "This branch is 12 commits ahead of, 4 commits behind ganeti/ganeti:master"

> We have AI agents that have been trained to review thousands of PRs that are produced by other, generative agents, and together they have already churned out much more software than human teams can write in a year.

Was your comment tongue-in-cheek? If not, where is this huge mass of AI-generated software?

> It's not obvious because people producing high quality stuff have no incentive at all to mark their changes as AI-generated

I feel like we'd be hearing from business that crushed their competition by delivering faster or with fewer people. Where are those businesses?

> But there are also local tools generated

This is really not the same thing as the original claim ("Software projects that somehow are 100% human developed will not be competitive with AI assisted or written projects").

None of this seems relevant to the original claim: "Software projects that somehow are 100% human developed will not be competitive with AI assisted or written projects"

I don't feel like it's meaningful to discuss the "competitiveness" of a handful of bespoke local or internal tools.

All around you, just that it doesn’t make sense for developers to reveal that a lot of their work is now about chunking and refining the specifications written by the product owner.

Admitting such is like admitting you are overpaid for your job, and that a 20 USD AI-agent can do better and faster than you for 75% of the work.

Is it easy to admit that you have learnt skills for 10+ years that are progressively already getting replaced by a machine ? (like thousands of jobs in the past).

More and more, developer is going to be a monkey job where your only task is to make sure there is enough coal in the steam machine.

Compilers destroyed the jobs of developers writing assembler code, they had to adapt. They insisted that hand-written assembler was better.

Here is the same, except you write code in natural language. It may not be optimal in all situations but it often gets the job done.

This is happening right now and it won’t be obvious until the liquidity events provide enough cover for victory lap story telling.

The very knowledge that an organization is experiencing hyper acceleration due to its successful adoption of AI across the enterprise is proprietary.

There are no HBS case studies about businesses that successfully established and implemented strategic pillars for AI because the pillars were likely written in the past four months.

> I feel like we'd be hearing from business that crushed their competition by delivering faster or with fewer people. Where are those businesses?

As if tech part was the major part of getting the product to market.

Those businesses are probably everywhere. They just aren't open about admitting they're using AI to speed up their marketing/product design/programming/project management/graphics design, because a) it's not normal outside some tech startup sphere to brag about how you're improving your internal process, and b) because almost everyone else is doing that too, so it partially cancels out - that is what competition on the market means, and c) admitting to use of AI in current climate is kind of a questionable PR move.

WRT. those who fail to leverage the new tools and are destined to be outcompeted, this process takes extended time, because companies have inertia.

>> But there are also local tools generated

> This is really not the same thing as the original claim

Point is that such wins compound. You get yak shaving done faster by fashioning your own tools on the fly, and it also cuts cost and a huge burden of maintaining relationships with third parties[0]

--

[0] - Because each account you create, each subscription you take, even each online tool you kinda track and hope hope hope won't disappear on you - each such case comes with a cognitive tax of a business relationship you probably didn't want, that often costs you money directly, and that you need to keep track of.

Mine is. And it is awesome: https://github.com/banagale/FileKitty

The most recent release includes a MacOS build in a dmg signed by Apple: https://github.com/banagale/FileKitty/releases/tag/v0.2.3

I vibed that workflow just so more people could have access to this tool. It was a pain and it actually took time away from toenail clipping.

And while I didn't lay hands on a guitar much during this period, I did manage to build this while bouncing between playing Civil War tunes on a 3D-printed violin and generating music in Suno for a soundtrack to “Back on That Crust,” the missing and one true spiritual successor to ToeJam & Earl: https://suno.com/song/e5b6dc04-ffab-4310-b9ef-815bdf742ecb

Good luck debugging

Going by the standard of "But there are also local tools generated faster than you could adjust existing tools to do what you want", here's a random one of mine that's in regular use by my wife:

https://github.com/TeMPOraL/qr-code-generator

Built with Aider and either Sonnet 3.5 or Gemini 2.5 Pro (I forgot to note that down in this project), and recently modified with Claude Code because I had to test it on something.

Getting the first version of this up was literally both faster and easier than finding a QR code generator that I'm sure is not bloated, not bullshit, not loaded with trackers, that's not using shorteners or its own URL (it's always a stupid idea to use URL shorteners you don't control), not showing ads, mining bitcoin and shit, one that my wife can use in her workflow without being distracted too much. Static page, domain I own, a bit of fiddling with LLMs.

What I can't link to is half a dozen single-use tools or faux tools created on the fly as part of working on something. But this happens to me couple times a month.

To anchor another vertex in this parameter space, I found it easier and faster to ask LLM to build me a "breathing timer" (one that counts down N seconds and resets, repeatedly) with analog indicator by requesting it, because a search query to Google/Kagi would be of comparable length, and then I'd have to click on results!

EDIT: Okay, another example:

https://github.com/TeMPOraL/tampermonkey-scripts/blob/master...

It overlays a trivial UI to set up looping over a segment of any YouTube video, and automatically persists the setting by video ID. It solves the trivial annoyance of channel jingles and other bullshit at start/end of videos that I use repeatedly as background music.

This was mostly done zero-shot by Claude, with maybe two or three requests for corrections/extra features, total development time maybe 15 minutes. I use it every day all the time ever since.

You could say, "but SponsorBlock" or whatever, but per what GP wrote, I just needed a small fraction of functionality of the tools I know exist, and it was trivial to generate that with AI.

> and before you discount it as too trivial, somehow none of the other ones did what I wanted

No offense, it's really great that you are able to make apps that do exactly what you want, but your examples are not very good to show that "software projects that somehow are 100% human developed will not be competitive with AI assisted or written projects" (as someone else suggested above). Complex real world software is different from pomodoro timers and TODO lists.

> All around you, just that it doesn’t make sense for developers to reveal that

OK, but I asked for evidence and people just keep not providing any.

"God is all around you; he just works in mysterious ways"

OK, good luck with that.

> This is happening right now and it won’t be obvious until

I asked for evidence and, as always, lots of people are popping out of the woodwork to swear that it's true but I can't see the evidence yet.

OK, then. Good luck with that.

> Those businesses are probably everywhere. They just aren't open about admitting

"Where's the evidence?" "Probably everywhere."

OK, good luck, have fun

I have a complete proof that P=NP but it doesn't make sense to reveal to the world that now I'm god. It would crush their little hearts.

Yup. Or, "Just look around!".

Your QR generator is actually a project written by humans repackaged:

https://github.com/neocotic/qrious

All the hard work was made by humans.

I can do `npm install` without having to pay for AI, thanks.

If it was self-evident then I wouldn’t need to ask for evidence. And I imagine you wouldn’t need to be waving your hands making excuses for the lack of evidence.

> The time to make them generic enough to share would be much longer than creating my specific version in the first place

Welcome to the reality of software development. "Works on my machine" is often not good enough to make the cut.

This app is concatenating files with an extra line of metadata added? You know this could be done in a few lines of shell script? You can then make it a finder action extension so it’s part of the system file manager app.

Sic transit gloria mundi

Here's Armin Ronacher describing his open-source "sloppy XML" parser that he had AI write with his guidance from this week: https://lucumr.pocoo.org/2025/6/21/my-first-ai-library/

It doesn't matter that my thing doesn't generalise if someone can build their own customised solution quickly. But also, if I wanted to sell it or distribute it, I'd ensure it was more generic from the beginning.

Cut it out with patronising, I work with complex software, which is why I specifically mentioned the only example I published was simple.

> but your examples are not very good to show that "software projects that somehow are 100% human developed will not be competitive with AI assisted or written projects"

Here's the thing though - it's already the case, because I wouldn't create those tools but hand otherwise. I just don't have the time, and they're too personal/edge-case to pay anyone to make them. So the comparison in this case is between 100% human developed non-existent software and AI generated project which exists. The latter wins in every category by default.

I am reminded of a meme about musicians. Not well enough to find it, but it was something like this:

  Real musicians don’t mix loops they bought.
  Real musicians make their own synth patches.
  Real musicians build their own instruments.
  Real musicians hand-forge every metal component in their instruments.
  …
  They say real musicians raise goats for the leather for the drum-skins, but I wouldn't know because I haven’t made any music in months and the goats smell funny.

There's two points here:

1) even though most of people on here know what npm is, many of us are not web developers and don't really know how to turn a random package into a useful webapp.

2) The AI is faster than googling a finished product that already exists, not just as an NPM package, but as a complete website.

Especially because search results require you to go through all the popups everyone stuffs everywhere because cookies, ads, before you even find out if it was actually a scam where the website you went to first doesn't actually do the right thing (or perhaps *anything*) anyway.

It is also, for many of us, the same price: free.

And because from the outside everything looks worse than ever. Worse quality, no more support, established companies going crazy to cut costs. AI slop is replacing thoughtful content across the web. Engineering morale is probably at an all time low for my 20 years watching this industry...

So my question is: if so many people should be bragging to me and celebrating how much better things are, why does it look to me like they are worse and everyone is miserable about it...?

P = NP is less "crush their little hearts", more "may cause widespread heart attacks across every industry due to cryptography failing, depending on if the polynomial exponent is small enough".

A very very big if.

Also a sufficiently good exponential solver would do the same thing.

> They just aren't open about admitting they're using AI to speed up their marketing/product design/programming/project management/graphics design

Sure… they'd hate to get money thrown at them from investors.

I don't think they're being patronizing, it's that "simple personal app that was barely worth making" is nice to have but not at all what they want evidence of.

Billions of people believe in god(s). In fact, 75 to 85% of the world population, btw.

Whether it was worth making is for me to judge since it is a personal app. It improves my life and work, so yes, it was very much worth it.

And?

All the features you mentioned are not coming from the AI.

Here it is invoking the actual zfs commands:

https://github.com/ganeti/ganeti/compare/master...linsomniac...

All the extra python boilerplate just makes it harder to understand IMHO.

You need to put your money where your mouth is.

If you comment about AI generated code in a thread about qemu (mission-critical project that many industries rely upon), a pomodoro app is not going to do the trick.

And no, it doesn't "show that is possible". qemu is not only more complex, it's a whole different problem space.

> I am reminded of a meme about musicians. Not well enough to find it

You only need to search for “loops goat skin”. You’re butchering the quote and its meaning quite a bit. The widely circulated version is:

> I thought using loops was cheating, so I programmed my own using samples. I then thought using samples was cheating, so I recorded real drums. I then thought that programming it was cheating, so I learned to play drums for real. I then thought using bought drums was cheating, so I learned to make my own. I then thought using premade skins was cheating, so I killed a goat and skinned it. I then thought that that was cheating too, so I grew my own goat from a baby goat. I also think that is cheating, but I’m not sure where to go from here. I haven’t made any music lately, what with the goat farming and all.

It’s not about “real musicians”¹ but a personal reflection on dependencies and abstractions and the nature of creative work and remixing. Your interpretation of it is backwards.

¹ https://en.wikipedia.org/wiki/No_true_Scotsman

Ice Ice Baby getting the bass riff of Under Pressure is sampling. Making a cover is covering. Milli Vanilli is another completely different situation.

I am sorry, none of your points are made. Makes no sense.

The LLM work sounds dumb, and the suggestion that it made "a qr code generator" is disingenuous. The LLM barely did a frontend for it. Barely.

Regarding the "free" price, read the comment I replied on again:

> Built with Aider and either Sonnet 3.5 or Gemini 2.5 Pro

Paid tools.

It sounds like the author payed for `npm install`, and thinks he's on top of things and being smart.

> To be clear: this isn't an endorsement of using models for serious Open Source libraries. This was an experiment to see how far I could get with minimal manual effort, and to unstick myself from an annoying blocker. The result is good enough for my immediate use case and I also felt good enough to publish it to PyPI in case someone else has the same problem.

By their own admission, this is just kind of OK. They don’t even know how good or bad it is, just that it kind of solved an immediate problem. That’s not how you create sustainable and reliable software. Which is OK, sometimes you just need to crap something out to do a quick job, but that doesn’t really feel like what your parent comment is talking about.

Schroedingers AI. It's everywhere, but you can't point to it cause it's apparently indistinguishable from humans, except for the shitty AI which is just shitty AI.

It's a thought terminating cliche.

> Assuming at least that you are an otherwise competent developer and that you carefully review all code before you commit it.

That is a big assumption. If everyone were doing that, this wouldn’t be a major issue. But as the curl developer has noted, people are using LLMs without thinking and wasting everyone’s time and resources.

https://www.linkedin.com/posts/danielstenberg_hackerone-curl...

I can attest to that. Just the other day I got a bug report, clearly written with the assistance of an LLM, for software which has been stable and used in several places for years. This person, when faced with an error on their first try, instead of pondering “what am I doing wrong” instead opened a bug report with a “fix”. Of course, they were using the software wrong. They did not follow the very short and simple instructions and essentially invented steps (probably suggested by an LLM) that caused the problem.

Waste of time for everyone involved, and one more notch on the road to causing burnout. Some of the worst kind of users are those who think “bug” means “anything which doesn’t immediately behave the way I thought it would”. LLMs empower them, to the detriment of everyone else.

And not that long ago, the majority of the population believed the Earth is flat, and that cigarettes are good for your health. Radioactive toys were being sold to children.

Wide belief does not equal truth.

My llm-consortium project was vibe coded. Some notes on how I did that in the announcement tweet if you click through https://x.com/karpathy/status/1870692546969735361

The parent claim was that devs don’t open-source their personal AI tools. FileKitty is mine and it is MIT-licensed on GitHub.

It began as an experiment in AI-assisted app design and a cross-platform “cat these files” utility.

Since then it has picked up:

- Snapshot history (and change flags) for any file selection

- A rendered folder tree that LLMs can digest, with per-prompt ignore filters

- String-based ignore rules for both tree and file output, so prompts stay surgical

My recent focus is making that generated context modular, so additional inputs (logs, design docs, architecture notes) can plug in cleanly. Apple’s new on-device foundation models could pair nicely with that.

The bigger point: most AI tooling hides the exact nature of context. FileKitty puts that step in the open and keeps the programmer in the loop.

I continue to believe LLMs can solve big problems with appropriate context and that intentionality in context prep is important step in evaluating ideas and implementation suggestions found in LLM outputs.

There's a Homebrew build available and I'd be happy to take contributions: https://github.com/banagale/FileKitty

You said you wouldn't have made it if it took longer, isn't that a barely?

But either way it's not an example of what they wanted.

I can't imagine they ever even looked at what they checked in, because it includes code that the LLM was using to investigate other code.

You are just not listening to the right places.

fly.pieter.com made a fortune while he live vide coded it on Twitter. One made making a modern multiplayer game.

Or Michael Luo, who got a legal notice after making a much cheaper app that did the same as docusign https://analyticsindiamag.com/ai-news-updates/vibe-coder-get...

There are others, but if you have found a gold mine, why would you inform the world?

> Complex real world software is different from pomodoro timers and TODO lists.

Simplistic Pomodoro timer with no features, sure, but a full blown modern Todo app that syncs to configurable backend(s), has a website, mobile apps, an electron app, CLI/TUI, web hooks, other integrations? Add a login system and allow users to assign todos to each other, and have todos depend on other todos and visualizations and it starts looking like JIRA, which is totally complex real world software.

The weakness of LLMs is that they can't do anything that's not in their training data. But they've got so much training data that say you had a box of Lego bricks but could only use those bricks to build models. If you had a brick copier, and one copy of every single brick type on the Internet, the fact that you couldn't invent new pieces from scratch would be a limitation, but given the number of bricks on all the Internet, that covers a lot of area. Most (but not all) software is some flavor of CRUD app, and if LLMs could only write every CRUD app ever that would still be tremendous value.

We'll have to see how it pans out for Cloudflare. They published an oauth thing and all the prompts used to create it.

https://github.com/cloudflare/workers-oauth-provider/

Billions of people _say_ they believe in god. It's very different.

--

When you analyze church attendance, it drops to roughly 50% instead of 85% of the population:

https://en.wikipedia.org/wiki/Church_attendance#Demographics

If you start to investigate many aspects of religious belief, like how many christians read the bible, the numbers drop drastically to less than 15%

https://www.statista.com/statistics/299433/bible-readership-...

This demonstrates that we cannot rely on self-reporting to understand religious belief. In practice, most people are closer to atheists than believers.

Sure I won't disagree that those people also exist but I don't think that's who the claim is being made about. Pointing out that subpar developers exist doesn't refute that good ones exist.

That's rather silly. Neither of those things is a requirement for belief.

Obviously it's the basis for a religion. We're to have faith in the ability of LLMs. To ask for evidence of that is to question the divine. You can ask a model itself for the relevant tenants pertaining to any given situation.

You can believe all you want, but practice is what actually matters.

It's the same thing with AI.

My apologies, I didn't want to sound patronizing and wasn't making assumptions about your work and experience based on your examples, I am happy that generative AI allows you to make such apps. However, they are very similar to the demos that are always presented as showcases.

> The LLM work sounds dumb, and the suggestion that it made "a qr code generator" is disingenuous. The LLM barely did a frontend for it. Barely.

Yes, and?

The goal wasn't "write me a QR library" it was "here's my pain point, solve it".

> It sounds like the author payed for `npm install`, and thinks he's on top of things and being smart.

I can put this another way if you prefer:

  Running `npm install qrious`: trivial.
  Knowing qrious exists and how to integrate it into a page: expensive.

https://www.snopes.com/fact-check/know-where-man/

> > Built with Aider and either Sonnet 3.5 or Gemini 2.5 Pro

> Paid tools.

I get Sonnet 4 for free at https://claude.ai — I know version numbers are weird in this domain, but I kinda expect that means Sonnet 3.5 was free at some point? Was it not? I mean, 3.7 is also a smaller version number but listed as "pro", so IDK…

Also I get Gemini 2.5 Pro for free at https://aistudio.google.com

Just out of curiosity, I've just tried using Gemini 2.5 Pro (for free) myself to try this. The result points to a CDN of qrcodejs, which I assume is this, but don't know my JS libraries so can't confirm this isn't just two different ones with the same name: https://github.com/davidshimjs/qrcodejs

My biggest issue with this kind of thing in coding is the same as my problem with libraries in general: you're responsible for the result even if you don't read what the library (/AI) is doing. So, I expect some future equivalent of the npm left-pad incident — memetic monoculture, lots of things fail at the same time.

> Knowing qrious exists and how to integrate it into a page: expensive.

qrious literally has it integrated already:

https://github.com/davidshimjs/qrcodejs/blob/master/index.ht...

I see many issues. The main one is that none of this is relevant to the qemu discussion. It's on another whole level of project.

I kind of regret asking the poor guy to show his stuff. None of these tutorial projects come even close to what an AI contribution to qemu would look like. It's pointless.

The very first part of the quotation is "Knowing qrious exists".

So the fact they've already got the example is great if you do in fact already have that knowledge, and *completely useless* if you don't.