More and more plainly, OpenAI and Anthropic are making plays to own (and lease) the "means of production" in software. OK - I'm a pretty happy renter right now.
As they gobble up previously open software stacks, how viable is it that these stacks remain open? It seems perfectly sensible to me that these providers and their users alike have an interest in further centralizing the dev lifecycle - eg, if Claude-Code or Codex are interfaces to cloud devenvs, then the models can get faster feedback cycles against build / test / etc tooling.
But when the tooling authors are employees of one provider or another, you can bet that those providers will be at least a few versions ahead of the public releases of those build tools, and will enjoy local economies of scale in their pipelines that may not be public at all.
I'm done pretending this is a "right tools for the right job" kind of thing, there's wrong people in the right job, and they only know python. If no one self-writes code anymore anyway, at least use a language that isn't a clusterfuck of bad design decisions, and has 1 trillion lines of code in the collective memory of people who don't know what a stack is.
Such an outcome would make me wonder regarding the wisdom of "It is better to have love and lost than to have never loved at all."
Note that uv is fast because — yes, Rust, but also because it doesn’t have to handle a lot of legacy that pip does[1], and some smart language independent design choices.
If uv became unavailable, it’d suck but the world would move on.
Like, the whole point of open source is that this thread is not a thing. The whole point is "if this software is taken on by a malevolent dictator for life, we'll just fork it and keep going with our own thing." Or like if I'm evaluating whether to open-source stuff at a startup, the question is "if this startup fails to get funding and we have to close up shop, do I want the team to still have access to these tools at my next gig?" -- there are other reasons it might be in the company's interests, like getting free feature development or hiring better devs, but that's the main reason it'd be in the employees' best interests to want to contribute to an open-source legacy rather than keep everything proprietary.
Projects - including forks - fail all the time because the leadership/product direction on a project goes missing despite the tech still being viable, which is why people are concerned about these people being locked up inside OpenAI. Successfully forking is much easier said than done.
Not disputing that it's a great and widely used tool, BTW.
This is not the point of uv or any good package manager. The point is what prevents Python to suck. For a long time package management had been horrible in Python compared what you could see in other languages.
Maybe there needs to be some nonprofit watchdog which helps identify those cases in their early stages and helps bootstrap open forks. I'd fund to a sort of open capture protection savings account if I believed it would help ensure continuity of support from the things I rely on.
- https://pypistats.org/packages/poetry - https://pypistats.org/packages/uv
In the 2024 Python developer survey, 18% of the ecosystem used Poetry. When I opened this manifold question[0], I'm pretty sure uv was about half of Poetry downloads.
Estimating from these numbers, probably about 30% of the ecosystem is using `uv` now. We'll get better numbers when the 2025 Python developer survey is published.
Also see this: https://biggo.com/news/202510140723_uv-overtakes-pip-in-ci-u...
[0]: https://manifold.markets/JeremiahEngland/will-uv-surpass-poe...
Perhaps it never grabbed me as much because I've been running basically everything in Docker for years now, which takes care of Python versioning issues and caches the dependency install steps, so they only take a long time if they've changed. I also like containers for all of the other project setup and environment scaffolding stuff they roll up, e.g. having a consistently working GDAL environment available instantly for a project I haven't worked on in a long time.
If not, do you develop software with source dependencies (go, java, node, rust, python)? If so, how do you handle acquiring those dependencies—by hand or using a tool?
Mostly no, sometimes I give up and still use pip as a separate user.
> If not, do you develop software with source dependencies (go, java, node, rust, python)? If so, how do you handle acquiring those dependencies—by hand or using a tool
I haven't felt the need to use Go, the only Java software I use is in the OS repo. I don't want to use JS software for other reasons. This is one of the reasons why I don't like Rust rewrites. Python dependencies are very often in the OS repo. If there is anything else, I compile it from source and I curse when software doesn't use or adheres to the standard of the GNU build system.
And let’s say you constrain yourself to your OS package manager. What about the people on different distros? Their package managers are unlikely to have the exact same versions of your deps that your OS has.
I favor stability and the stripping of unwanted features (e.g. telemetry) by my OS vendor over cutting edge software. If I really need that I install it into /usr/local, that it what this is for after all.
> And let’s say you constrain yourself to your OS package manager. What about the people on different distros? Their package managers are unlikely to have the exact same versions of your deps that your OS has.
This is a reason to select the OS. Software shouldn't require exact versions, but should stick to stable interfaces.
(Source: I'm an Astral employee.)
That's a point of information, not a point of order.
People need to be very careful about resisting. OpenAI wants to make everyone unemployed, works with the Pentagon, steals IP, and copyright whistleblowers end up getting killed under mysterious circumstances.
I'm on the fence about cancelling my JetBrains subscription I've had for nearly 10 years now. I just don't use it much. Zed and Claude Code cover all my needs, the only thing I need is a serious DataGrip alternative, but I might just sit down with Claude and build one for myself.
It's not perfect, but it is light-years better than what preceded it.
I jumped ship to it and have not looked back. (So have many of my clients).
It's not there yet, but it's getting there.
It's so fast in fact that we just added `ty check` to our pre-commit hooks where MyPy previously had runtimes of 150+ seconds _and_ a mess of bugs around their caching.
https://x.com/AprilNEA/status/2034209430158619084
Ironically this type of stuff really makes me doubt their AGI claims, why would they bother with this stuff if they were confident of having AGI within the next few years? They would be focused on replacing entire industries and not even make their models available at any price. Why bother with a PaaS if you think you are going to replace the entire software industry with AGI?
Is this not just the strategy of all platforms. Spy on all customers, see what works for them and copy the most valuable business models. Amazon does that with all kinds of products.
Platforms will just grow to own all the market and hike prices and lower quality, and pay close to nothing to employees. This is why we used to have monopoly regulations before being greedy became a virtue.
1. For the record: the GPL is entirely dependent on copyright.
2. If AI "clean-room" re-implementations are allow to bypass copyright/licenses, the GPL won't protect you.
This is right up there with Meta lawyers claiming that when they torrent it's totally legal but when a single person torrents it's copyright infringement.
Isn't that the same for the obligations under BSD/MIT/Apache? The problem they're trying to address is a different one from the problem of AI copyright washing. It's fair to avoid introducing additional problems while debunking another point.
2. BigCo bus Company A
3a. usually here BigCo should continue to develop Project One as GPLv3, or stop working on it and the community would fork and it and continue working on it as GPLv3
3b. BigCo does a "clean-room" reimplementation of Project One and releases it under proprietary licence. Community can still fork the older version and work on it, but BigCo can continue to develop and sell their "original" version.
patents protect ideas, copyright protects artistic expressions of ideas
Preferring GPL licensed software means that you're immune to a sudden cut off of access so it's always advisable - but it's really important to stay on top of dependencies and be willing to pay the cost if support is withdrawn. So GPL helps but it isn't a full salve.
I'm careful to not rely too heavily on VC funded open source whenever I can avoid it.
All so they could just vacuum it all up and resell it with impunity.
Feel free to prove me wrong by pointing out this massive amount of advocacy from "mega-clouds" that changed people's minds.
The ads, the mailing list posts, social media comments. Anything at all you can trace to "mega-clouds" execs.
https://choosealicense.com/about/
> "GitHub wants to help developers choose an open source license for their source code."
This was built by GitHub Inc a very very long time ago.
So long ago, in fact, that it was five years before their acquisition by Microsoft.
And, sure, djb wasn't actually likely to sue you if you went ahead and distributed modified versions of his software... but no-one else was willing to take that risk, and it ended up killing qmail, djbdns, etc stone dead. His work ended up going to waste as a result.
Agreed with the rest, though. I relied heavily on qmail for about a decade, and learned a lot from the experience, even if it was a little terrifying on occasion!
I mean philosophically and morally, sure, one can take that position ... but copyright law does not work like that, at least not for anything published in the US after 1989 [1].
The ones pushing for permissive licenses are rather companies like Apple, Android (and to some extent other parts of Google), Microsoft, Oracle. They want to push their proprietary stuff and one way to do that in the face of open source competition is by proprietary extensions.
The FOSS community at large embraced permissive licenses and it had nothing to do with the interests of big corporations.
Like having a system prompt which takes care of the project structure, languages, libraries etc
It's pretty much the first step to replacing devs, which is their current "North Star" (to be changed to the next profession after)
Once they've nailed that, the devs become even more of a tool then they're already are (from the perspective of the enterprise).
The issue that I see is that Nvidia etc. are incentivised to perpetuate that so the open source community gets the table scraps of distills, fine-tunes etc.
Plus, most users don't want to host their own models. Most users don't care that OpenAI, Anthropic and Google have a monopoly on LLMs. ChatGPT is a household name, and most of the big businesses are forcing Copilot and/or Claude onto their employees for "real work."
This is "everyone will have an email server/web server/Diaspora node/lemmy instance/Mastodon server" all over again.
It's probably a trade secret, but what's the actual per-user resource requirement to run the model?
If the open weights models are good, there are people looking to sell commodity access to it, much like a cloud provider selling you compute.
Once we start seeing Open AI and Anthropic getting into the certifications and testing they'll quickly become the gold standard. They won't even need to actually test anyone. People will simply consent to having their chat interactions analyzed.
The models collect more information about us than we could ever imagine because definitionally, those features are unknown unknowns for humans. For ML, the gaps in our thinking carry far richer information about is than our actual vocabularies, topics of interest, or stylometric idiosyncrasies.
There will come a day when you can will an entire business into existence at the press of a button. Maybe it has one or two people overseeing the business logic to make sure it doesn't go off the rails, but the point is that this is a 100x reduction in labor and a 100,000x speed up in terms of delivery.
They'll price this as a $1M button press.
Suddenly, labor capital cannot participate in the market anymore. Only financial capital can.
Suddenly, software startups are no longer viable.
This is coming.
The means of production are becoming privatized capital outlays, just like the railroads. And we will never own again.
There is nothing that says our careers must remain viable. There is nothing that says our output can remain competitive, attractive, or in demand. These are not laws.
Knowledge work may be a thing of the past in ten years' time. And the capital owners and hyperscalers will be the entirety of the market.
If we do not own these systems (and at this point is it even possible for open source to catch up?), we are fundamentally screwed.
I strongly believe that people not seeing this - downplaying this - are looking the other way while the asteroid approaches.
This. Is. The. End.
What if labor organizes around human work and consumers are willing to pay the premium?
At that point, it's an arms race against the SotA models in order to deepen the resolution and harden the security mechanisms for capturing the human-affirming signals produced during work. Also, lowering the friction around verification.
In that timeline, workers would have to wear devices to monitor their GSR and record themselves on video to track their PPG. Inconvenient, and ultimately probably doomed, but it could extend or renew the horizon for certain kinds of knowledge work.
We could start today, but sweat shops and factories dominate the items on our shelves.
But I’m sure people will draw the line at human made software…/s
As long as they keep the original projects maintained and those aren't just acqui-hires, I think this is almost as good as we can hope for.
(thinking mainly about Bun here as the other one)
Once you’re acquired you have to do what the boss says. That means prioritizing your work to benefit the company. That is often not compatible with true open source.
How frequently do acquired projects seriously maintain their independence? That is rare. They may have more resources but they also have obligations.
And this doesn’t even touch on the whole commodification and box out strategy that so many tech giants have employed.
If AGI becomes available, especially at the local and open-source level, shouldn't all these be democratized - meaning that the AGI can simply roll out the tooling you need.
After all, AGI is what all these companies are chasing.
The ecosystem will be this way for a while, if not the new normal.
Equivalent or better tools will pop up eventually, heck if AI is so fantastic then you could just make one of your own, be the change you want to see in the world, right?
Oh well. They’ll hopefully get options and make millions when the IPO happens. Everyone eventually sells out. Not everyone can be funded by MIT to live the GNU maximalist lifestyle.
Why on earth would agents ever code in as terrible a language as Python when the cost of significantly better languages is essentially free? The only advantage Python ever had was that it was easy to write
Is it? We still need meatspace humans to vet what these AI agents produce. Languages like C++ / Rust etc still require huge cognitive overhead relative to Python & that will not change anytime soon.
Unless the entire global economy can run on agents with minimal human supervision someone still has to grapple with the essential complexity of getting a computer to do useful things. At least with Python that complexity is locked away within the CPython interpreter.
Also an aside, when has a language ever gotten traction based solely on its technical merits? Popularity is driven by ease-of-use, fashion, mindshare, timing etc.
There is also a really good ecosystem of libraries, especially for scientific computing. My experience has been that Claude can write good c++ code, but it's not great about optimization. So, curated Python code can often be faster than an AI's reimplementation of an algorithm in c++.
And as someone who loves Python and has written a lot of it, I tend to agree. It's increasingly clear the way to be productive with AI coding and the way to make it reliable is to make sure AI works within strong guardrails, with testsuites, etc. that combat and corral the inherent indeterminism and problems like prompt injection as much as possible.
Getting help from the language - having the static tooling be as strict and uncompromising as possible, and delegating having to deal with the pain to AI - seems the right way.
If I ask an LLM or agentic AI to build something and don't specify what language to use, I'd wager that it'll choose python most of the time. Casual programmers like academics or students who ask ChatGPT to help them write a function to do X are likely to be using Python already.
I'm not a Python evangelist by any means but to suggest that AI is going to kill Python feels like a major stretch to me.
EDIT: when I say that Python can do anything any other language can do, that's with the adage in mind. Python is the second best language for every task.
Secondly it's non factual. Python's market share grew in 2025[1][2][3]. Probably driven by AI demand.
[0]: even truer for natural languages.
[1]: https://survey.stackoverflow.co/2025/technology#most-popular...
[2]: https://survey.stackoverflow.co/2024/technology#most-popular...
I maintain an open source project funded by the Sovereign Tech Fund. Getting there wasn't easy: the application process is long, the amounts are modest compared to a VC round, and you have to build community trust before any of that becomes possible. But the result is a project that isn't on anyone's exit timeline.
I'm not saying the startup path is without its own difficulties. But structurally, it offloads the costs onto the community that eventually comes to depend on you. By the time those costs come due, the founders have either cashed out or the company is circling the drain, and the users are left holding the bag. What's happening to Astral fits that pattern almost too neatly.
The healthier model, I think, is to build community first and then seek public or nonprofit funding: NLnet, STF, or similar. It's slower and harder, but it doesn't have a built-in betrayal baked into the structure.
Part of what makes this difficult is that public funding for open source infrastructure is still very uneven geographically. I'm based in Korea, and there's essentially nothing here comparable to what European developers can access. I had no choice but to turn to European funds, because there was simply no domestic equivalent. That's a structural problem worth taking seriously. The more countries that leave this entirely to the private sector, the more we end up watching exactly this kind of thing play out.
A lot of great open source comes out of startups because startups are really good at shipping fast and getting distribution (open source is part of this strategy). Users can try the tool immediately, and VC funding can put a lot of talent behind building something great very quickly.
The startup model absolutely creates incentive risk, but that’s true of any project that becomes important while depending on a relatively small set of maintainers or funders.
I’m not sure an acquisition is categorically different from a maintainer eventually moving on or burning out. In all of those cases, users who depend on the project take on some risk. That’s not unique to startups; it’s true of basically any software that becomes important.
There’s no perfect structure for open source here - public funding, nonprofit support, and startups all suck in their own ways.
And on the point you make about public funding being slow: yeah, talented people can’t work full-time on important things unless there’s serious funding behind it. uv got as good as it is because the funding let exceptional people work on it full-time with a level of intensity that public funding usually does not.
I would absolutely love to know more about this if you are willing to share the story?
Most of the companies that spend $$$$ with them can't use public registries for production/production-adjacent workloads due to regulations and, secondarily a desire to mitigate supply chain risk.
Artifactory is a drop-in replacement for every kind of repository they'll need to work with, and it has a nice UI. They also support "pass-through" repositories that mirror the public repositories with the customization options these customers like to have. It also has image/artifact scanning, which cybersecurity teams love to use in their remediation reporting.
It's also relatively easy to spin up and scale. I don't work there, but I had to use Artifactory for a demo I built, and getting it up and running took very little time, even without AI assistance.
Having a private package index gives you a central place where all employees can install from, without having to screen what each person is installing. Also, if I remember right, there are some large AI and ML focused packages that benefit from an index that's tuned to your specific hardware and workflows.
Plus the obvious need for a place to host proprietary internal libraries.
It was because Astral was VC funded.
https://astral.sh/blog/announcing-astral-the-company-behind-...
There seems to be a pervasive believe that the Python tooling and interpreter suck and are slow because the maintainers don’t care, or aren’t capable.
The actual problem is that there isn’t enough money to develop all of these systems properly.
Google says that Astral had 15 team members. Or course, it’s so hard to make these projections. But it wouldn’t shock me if uv and ruff are each individually multi-million dollar pieces of software.
If you’d like to invest a million dollars to improve pip, or work for free for 3 years to do it yourself, I’m not sure if anyone would object.
Either pay for the product, or use stuff that isn't dependent on VC money, this is always how it ends.
Maybe you use non-transitive pure Python dependencies, but it's likely that your tools and dependencies still rely on stuff in Rust or C (e.g.: py-cryptography and Python itself respectively).
As mentioned multiple times, since my experience with Tcl and continuously rewriting stuff in C, I tend to avoid languages that don't come with JIT, or AOT, in the reference tooling.
I tend to work with Java, .NET, node, C++, for application code.
Naturally AI now changes that, still I tend to focus on approaches that are more classical Python with pip, venv, stuff written in C or C++ that is around for years.
Consider ffmpeg. You can donate via https://www.ffmpeg.org/spi.html
How much money do they make from donations? I don't know but "In practice we frequently payed for travel and hardware."
Translation: nothing at all.
If such a fundamental project that is a revenue driver for so many companies, including midas-level rich companies like Google, can't even pay decent salaries for core devs from donations, then open source model doesn't work in terms of funding the work even at the smallest possible levels of "pay a reasonable market rate for devs".
You either get people who just work for free or businesses built around free work by providing something in addition to free software (which is hard to pull off, as we've seen with Bun and Astral and Deno and Node).
There are examples of foundations or other similar entities paying developers, like Linux, SQLite, even Zig.
Maybe the difference is some projects rely on core contributors more because external contributions are more restricted in some way.
But sure, the entire open source model doesn't work, lol
At worst, it's just Anaconda II AI Boogaloo. The ecosystems will evolve and overcome, or will die and different ecosystems rise to meet the need going forward.
I anticipate OpenAI will get bored and ignore Astral's tools. Software entropy will do its thing and we will remember an actively developed uv as the good old days until something similar to cargo gets adopted as part of Python's standard distribution.
The only thing that could prevent this is lack of ability to execute, like how Uber wanted to replace drivers with FSD vehicles.
Even if they believe that their systems will eventually tank employment and replace developers rather than augment meant, the fate of Astral doesn't matter at all in that scenario because a) nobody has a job, and b) you can build your own uv replacement for $20.
I hope those two factors mean that if things go really wrong, then the clean(ish) break with all the non standard complex legacy means an easier future for community packaging efforts.
OpenClaw notably was built around Mario Zechner's pi[0]; uv I believe was highly adapted from Armin Ronacher's rye[1], and uses indygreg's python-build-standalone[2] for distributing Python builds (both of which were eventually transferred to Astral).
[0]: https://github.com/badlogic/pi-mono
In the worst case, Astral will stop developing their tools, someone else will pick them up and will continue polishing them. In the best case, they will just continue as they did until now, and nothing will really change on that front.
Astral is doing good work, but their greatest benefit for the ecosystem so far was showing what's possible and how it's down. Now everyone can take up the quest from here and continue. So any possible harm from here out will be not that deep, at worst we will be missing out on many more cool things they could have built.
Unlike those react-game-engine guys over at Claude
We need public investment in open source, in the form of grants, not more private partnerships that somehow always seem to hurt the community.
Every interface kenneth reitz originally designed was fantastic to learn and use. I wish the influx of all these non-pythonistas changing the language over the last 10 years or so would go back and learn from his stuff.
I started using VS Codium, and it feels like using VS Code before the AI hype era. I wonder if we're going to see a commercial version of uv bloated with the things OpenAI wants us all to use, and a community version that's more like the uv we're using right now.
[1] https://github.com/platformio/platformio-vscode-ide/issues/1...
Glad to hear that I am avoiding Microsoft's spam.
Probably inevitable, and I don’t blame the team, I just wish it were someone else.
I'm not very deep in Python anymore, but every time I dip my toes back in it's a completely different set of tools, with some noticably rare exceptions (eg, numpy).
Microsoft acquires Astral
Wish comes with a cost
Sigh
It was a VC backed tool. What did you expect?
I don't really see the value for OAI/Anthropic, but it's nice to know that uv (+ ty and many others) and Bun will stay maintained!
From Astral the (fast) linter and type checker are pretty useful companions for agentic development.
I won't be surprised if the next step is to acquire CI/CD tools.
The value for Anthropic / OAI is that they have a strong interest in becoming the "default" agent.
The one that you don't need to install, because it's already provided by your package manager.
I think they're more into the extra context they can build for the LLM with ruff/ty.
Embrace, extend, extinguish. Time will tell.
There is the literal benefit of "we use the hell out of this tool, we need to make sure it stays usable for us" and then there is what they can learn from or coerce the community in to doing.
Depends if you think the bubble is going to pop, I suppose. In some sense, independence was insulation.
I didn't see a single comment of "I will fork it" type.