Hey everyone, welcome back to My Weird Prompts. We are hitting episode six hundred sixty-seven today, and I have to say, the energy in our Jerusalem studio is high this morning. The sun is hitting the stone walls of the Old City just right outside our window, and the air is crisp. I am Corn, and sitting across from me, surrounded by more monitors than a flight control center, is my brother.
Herman Poppleberry, at your service. It is a beautiful day to dive into some deep technical philosophy, Corn. I have been refreshing my notes all morning, drinking way too much espresso, and tracking the latest repository commits from across the globe. There is something about the morning light in Jerusalem that really makes you want to deconstruct complex systems.
Well, you are in luck because today’s prompt from Daniel is a heavy hitter. It is about the very foundations of the open source movement. Daniel wants us to look past just the code and explore what it actually takes for a project to be truly open source in twenty-twenty-six. We are living in the era of vibe coding and these massive integrated ecosystems, and Daniel is asking if the old definitions still hold water. He wants to know about the documentation, the ideas, and the intellectual property.
That is such a timely topic, and honestly, it is a bit of a battleground right now. We often use the term open source as a catch-all for anything that is free to download or anything you can see on GitHub, but the legal and philosophical requirements are much more rigorous than that. It is not just about the availability of the text files. It is about the right to fork, the right to redistribute, and the right to actually understand the ideas behind the implementation. If you can see the code but you cannot legally change it or understand how it works, is it really open?
That is the million-dollar question. Or maybe the multi-billion-dollar question, given the valuation of some of these companies. I think we should start with that consensus you mentioned. When we say a project is truly open source, what are the baseline boxes it has to tick? Most people think of the license, like MIT or Apache, but Daniel’s prompt suggests there is a much broader spectrum involving documentation and intellectual property.
You are spot on. To understand the consensus, we really have to look back at the Open Source Initiative, or the OSI. They have had a ten-point Open Source Definition for decades, and even in twenty-twenty-six, it remains the North Star. It includes things like free redistribution, meaning the license cannot restrict any party from selling or giving away the software. It requires access to the source code. It must allow for derived works, which is the legal way of saying you have the right to fork it.
I remember you mentioned that last one before, the no discrimination against fields of endeavor. That one always seemed particularly important to you.
It is huge, Corn. It is the most controversial part for many people. You cannot say this is open source except for use by the military, or except for use by insurance companies, or except for use by people I do not like. If you put those restrictions on it, it might be source-available, it might be free-ish, but it is no longer open source by the global consensus definition. This became a massive point of contention in twenty-twenty-four and twenty-twenty-five when we saw the rise of ethical source licenses. People wanted to prevent their code from being used for surveillance or warfare, which is a noble goal, but it breaks the fundamental definition of open source.
I remember we touched on this briefly when we talked about open weights versus open source in AI. It seems like the industry is currently in a bit of a crisis of terminology. Companies want the marketing glow of the open source label without actually giving up the competitive advantage of their secret sauce. We see this all the time with these large language models that claim to be open, but they only give you the final weights, not the training data or the recipe.
Exactly. And that brings us to the documentation and ideas part of Daniel’s prompt. This is where the rubber meets the road in twenty-twenty-six. If I give you a million lines of uncommented, obfuscated code that was generated by a machine, but I tell you it is under a General Public License, have I really fulfilled the spirit of open source? Technically, yes, according to the letter of the law. But practically, if no human can understand it or modify it without a supercomputer or a decade of training, is it truly accessible? The OSI recently finalized the Open Source AI Definition, and it specifically addresses this. It says that for an AI model to be open source, you need to provide enough information about the training data and the training code so that someone else could substantially recreate the work.
That is where the documentation comes in. I have seen projects where the code is open, but the build process is a complete black box. You download the files, but you need a proprietary compiler or a specific cloud environment that costs five thousand dollars a month to actually run it. Or the documentation is locked behind a paywall or a proprietary wiki. To me, that feels like a massive loophole. If you cannot actually build and run the software from the source using public instructions, the openness is just a facade.
I agree. In the developer community, we often talk about the bus factor, which is how many people would need to get hit by a bus before a project dies. In a truly open source project, that factor should be high because the knowledge is distributed through documentation, public mailing lists, and transparent design documents. If the only people who know how the system actually works are three engineers at a specific company, the community cannot effectively fork it. They might have the code, but they do not have the institutional knowledge.
Let’s talk about that word fork for a second. For our non-developer listeners, forking is basically taking a copy of the project and starting your own version of it. It is the ultimate check and balance in the ecosystem. It is the nuclear option. If a project lead becomes a tyrant, or a company tries to monetize a feature everyone hates, or they change the license to something restrictive, the community can just fork it and go their own way. But Herman, how does IP, or intellectual property, play into this? Can a project be open source if the name is trademarked?
That is a very thorny issue that we saw come to a head with the Rust Foundation a few years ago. Trademarks are actually one of the few things that are often kept closed even in open source projects. Look at Mozilla Firefox or the Linux kernel. You can take the code for Firefox, fork it, and call it Iceweasel, which is what Debian did for a long time. But you cannot call your fork Firefox without permission from Mozilla. The consensus is that the code and the ideas must be free, but the brand can be protected to ensure quality and prevent confusion. However, if the project relies on patented algorithms that the creator refuses to license, then it is definitely not truly open source. You need a patent grant along with the copyright license. In twenty-twenty-six, we are seeing more projects use the O-I-N, the Open Invention Network, which is a massive patent non-aggression community.
This leads us naturally into what Daniel called vibe coding. For context, we are seeing more and more people using AI agents to generate entire applications based on natural language prompts. You just describe the vibe of the app, you tell the agent you want a minimalist task manager with a neon aesthetic, and the agent spits out the code. If I vibe a project into existence, who owns the IP? And if I release that project as open source, am I really providing the source if the source was actually my conversation with an AI?
This is the new frontier, Corn. It is fascinating and a little bit terrifying for the old guard. In twenty-twenty-four and twenty-twenty-five, we saw the rise of these LLM-driven development tools. Now, in twenty-twenty-six, a lot of software isn't written line by line. It is prompted. If a project is truly open source in the era of vibe coding, I would argue that you must release the prompts and the model weights used to generate the code, not just the generated code itself. Because the generated code is effectively the binary in this scenario. The prompt is the new source code.
That is a provocative take, Herman. So you are saying that if I give you a thousand lines of Python that an AI wrote for me, but I do not give you the specific instructions and the system prompts I gave the AI to get that output, I am withholding the true source?
Think about it. If you want to fork my vibe-coded project, you do not want to go in and manually edit the messy, AI-generated Python. That is like trying to edit a compiled assembly file. You want to take my prompts and iterate on them. You want to change the vibe. If you do not have the prompts, you are essentially reverse-engineering a compiled artifact. It breaks the whole philosophy of being able to understand and modify the work. We are seeing a new movement called Open Vibe, where developers commit their prompt history and their agent configurations right alongside their code.
It is like the difference between giving someone a cake and giving them the recipe. The generated code is the cake. The prompt is the recipe. If you want to be open source, you have to give them the recipe.
Exactly. And we are starting to see some movement on this from the legal side. There are new licenses being proposed, like the Generative Open License, that specifically cover the generative pipeline. But it is still a bit of a Wild West. Most projects are still just dumping the generated code on GitHub and calling it a day, which I think is going to lead to a lot of technical debt and unmaintainable forks in the next few years.
I want to move toward some specific examples that Daniel asked for. Who is doing this right? Who is making the code, the docs, the ideas, and the IP collectively open?
The gold standard, even after all these years, has to be the Linux kernel. It is not just that the code is GPL version two. It is the entire governance model. The documentation is incredibly extensive, though sometimes dense. The mailing lists are public and archived. The ideas are debated in the open. And while Linus Torvalds has a certain level of authority, the project has been forked and adapted into a thousand different flavors. It is the ultimate proof that open source works at scale.
Another great one is Blender, the three-D creation suite. They are a powerhouse of open source. They don't just release the code; they release open movies and open assets created with the software to show people how to use it. Their documentation is world-class, and they have a very clear IP policy that encourages people to build plugins and extensions. They have the Blender Foundation, which acts as a neutral steward for the project.
I would also point to the Godot Engine in the gaming world. Since Unity had that massive PR disaster a few years back with their pricing changes, Godot has become the poster child for what a truly open project looks like. It is MIT licensed, which is very permissive. The development is funded by a non-profit foundation, and they are extremely transparent about their roadmap. Anyone can see why a certain feature was added or why a certain architectural decision was made. That is the ideas part of the equation. It is not just what the code does, but why it does it. They even have a proposal system where the community can vote on and discuss new features before a single line of code is written.
What about in the hardware space? I know that is a different beast, but it feels relevant to the idea of total openness.
RISC-V is the big one there. It is an open standard instruction set architecture. They aren't just giving away a chip design; they are giving away the specification for how a chip should talk to software. This allows anyone to design their own processor without paying royalties to companies like ARM or Intel. It is a fundamental opening of the ideas at the very base of computing. In twenty-twenty-five, we saw a huge surge in RISC-V adoption in data centers because companies wanted to avoid the licensing fees and the black-box nature of proprietary silicon.
It seems like the common thread here is the existence of a foundation or a neutral governing body. When a project is owned by a single for-profit corporation, there is always that lingering fear that they will rug-pull the community. We saw that with Redis and HashiCorp recently, where they changed their licenses to be less open because they wanted to protect their cloud revenue. They moved to things like the Business Source License, which is source-available but not open source.
That rug-pull phenomenon is exactly why the consensus on what is open source is so important. If you use a non-OSI-approved license, you are signaling to the world that you might change the rules later. Truly open source projects usually hand over their IP and trademarks to a neutral foundation. That way, even if the original creators leave or the main sponsoring company goes bust, the project belongs to the public. It is a form of institutionalizing the trust.
I want to go deeper on the documentation aspect. You mentioned that if the docs are behind a paywall, it is not truly open. But what about the tools used to create the docs? If I use a proprietary platform like Notion or GitBook to host my open source docs, does that count against me?
It is a matter of degrees, but purists would say yes. If the community cannot host their own version of the documentation because it is locked in a proprietary database, then the project has a single point of failure. The best open source projects use things like Markdown or ReStructuredText files that live right alongside the code in the repository. That way, when you fork the code, you automatically fork the documentation. They are inseparable. We are also seeing the rise of neural documentation in twenty-twenty-six, where the docs are partially generated and verified by AI agents that have access to the entire commit history. If those agents are proprietary, we run into the same problem.
That makes so much sense. It ensures that the knowledge is just as portable as the logic. I am thinking about how this applies to the small-scale developer, maybe someone sitting here in Jerusalem or anywhere else, who wants to start a project. It feels like a lot of overhead to do all of this correctly. You have to pick a license, set up a foundation, write exhaustive docs, and now, apparently, archive your AI prompts.
It definitely is more work upfront, but it pays off in the long run. If you want people to actually use and contribute to your work, they need to feel safe. They need to know that their contributions won't be locked away later. And honestly, for a small project, just picking a standard license like MIT or GPL and keeping your docs in Markdown is ninety percent of the battle. The foundation stuff usually comes much later when the project scales and there is significant money or corporate interest involved.
Let’s talk about the accessibility of the ideas themselves. Sometimes code is open, but it relies on such complex mathematical concepts or specialized hardware that it is effectively closed to ninety-nine percent of the population. Does open source have a responsibility to be understandable?
This is a point of huge debate. Richard Stallman, who started the Free Software Foundation, would argue that the freedom to study the program is a fundamental right. But he doesn't say the program has to be easy to study. However, the open source movement, which is more pragmatic, realizes that if a project is too hard to understand, it won't get contributors. This is why design documents and architecture overviews are so critical. They are the map that helps you navigate the territory of the code. Without the map, you are just lost in the woods, even if you are allowed to be there. In twenty-twenty-six, we are seeing more projects use interactive notebooks and visual programming interfaces to explain their core logic.
I love that analogy. The code is the territory, and the documentation is the map. You can own the territory, but without the map, you can't do much with it. Now, let’s look at the future. We are in February of twenty-twenty-six. Where is this going? With more and more code being written by machines for machines, does the human-readable part of open source even matter anymore?
I think it matters more than ever. As we move into an era where AI can generate millions of lines of code in seconds, we are going to face a massive trust crisis. How do we know what this code is actually doing? How do we know there isn't a backdoor or a subtle bug? The only way to verify that is through transparency. We need open source models, open source datasets, and open source prompts so we can audit the entire pipeline. If the process is a black box, it doesn't matter if the output is technically under an MIT license. We won't be able to trust it. We are seeing the emergence of the CRAVE standard, which stands for Collective Release of All Verifiable Elements.
So, in a way, the definition of open source is expanding to include the entire supply chain of software creation. It is not just the end product; it is the factory, the raw materials, and the blueprints.
Exactly. We are seeing the rise of what people are calling Open Source Supply Chains. It is about knowing where every library came from, who signed off on every commit, and what AI was used to suggest that block of code. In twenty-twenty-five, the United States and the European Union both passed regulations requiring more transparency in software supply chains for critical infrastructure. Open source is the only way to meet those requirements without creating massive proprietary monopolies.
This brings me back to Daniel’s mention of the vibe coding era. If I am using an AI to help me code, and that AI was trained on proprietary data, is my output truly open? This is something the courts are still figuring out, but from a philosophical standpoint, it feels like a gray area.
It is the ultimate gray area. If the knowledge used to create the code is closed, can the code itself be truly open? Many people in the open source community are pushing for the idea that if you want to call yourself open, you have to release everything needed to recreate the work from scratch. That is a very high bar. It means releasing the training logs, the data cleaning scripts, and the hyper-parameters. It is impractical for individuals, but for large organizations and foundational models, it is becoming a requirement for public trust.
That sounds like a lot of data. Imagine trying to release the petabytes of training data used for a modern LLM just so you can call a small script open source.
It is a challenge, but we are seeing new ways of handling it. Things like decentralized storage and federated learning are making it easier to share large datasets without needing a single massive server. We are also seeing the rise of synthetic data, where you can release the recipe for the data rather than the data itself. The point is that the consensus is shifting. We are no longer satisfied with just seeing the code. We want to see the intent and the process.
So, for the listeners who are starting their own projects or contributing to others, what are the practical takeaways here? How can they tell if a project is just open-washing or if it is the real deal?
First, look at the license. If it is not on the OSI-approved list, be very careful. Second, look at the contribution graph. Is it just one company doing all the work, or is there a diverse community of contributors from different backgrounds? Third, check the documentation. Is it comprehensive, is it up to date, and is it hosted in an open format? And finally, look at the communication. Are decisions made in public forums, or do they just appear as finished products? If the project feels like a fortress that occasionally throws code over the wall, it is not truly open source in spirit, even if the license says otherwise.
I think that is a great checklist. It really gets to the heart of what Daniel was asking. It is about the culture of openness, not just the legal permission. It is about building a community where everyone has the same map and the same rights to the territory.
Precisely. Open source is a social contract as much as it is a legal one. It is an agreement to collaborate in the light rather than competing in the dark. And when it works, it is, as Daniel said, one of the most beautiful examples of humanity coming together. I mean, think about it. We have these global systems, the very backbone of the internet and our modern economy, built on the voluntary contributions of people who just want to make something cool and share it. It is a miracle of coordination.
It really is incredible. And even here in Jerusalem, we see the impact of it every day. The tech scene here is so intertwined with global open source movements. From the cybersecurity firms to the AI startups, everyone is standing on the shoulders of giants who chose to make their work open. It is a reminder that these ideas transcend borders and languages.
Definitely. And I think we should mention that if people are interested in this, they should check out the archives of the Open Source Initiative or read the original Cathedral and the Bazaar essay by Eric S. Raymond. It is a bit old now, but the core ideas about why open development is superior to closed development still hold up, even in the age of AI. The bazaar is just getting bigger and more automated.
Well, Herman, I think we have covered a lot of ground today. From the legal definitions of the OSI to the future of vibe coding and the importance of open supply chains. It is clear that being truly open source is a high bar, but it is one that is worth striving for if we want a future that is transparent and trustworthy.
I couldn't agree more. It is about building a future where knowledge is a public good rather than a private secret. And I think that is a goal we can all get behind, whether we are writing code by hand or vibing it into existence with an AI agent.
Absolutely. Before we wrap up, I want to say a huge thank you to Daniel for sending in this prompt. It gave us a lot to chew on, and I hope it was helpful for everyone listening. It is prompts like these that keep us digging deeper into the weird and wonderful world of technology.
Yeah, great prompt, Daniel. It is always fun to dig into the philosophy behind the tools we use every day. It makes you look at your own code and your own workflow in a different light.
And hey, if you have been enjoying the show, we would really appreciate it if you could leave us a quick review on your podcast app or a rating on Spotify. It genuinely helps other people find the show and keeps us going. We are aiming to hit seven hundred episodes soon, and we can't do it without your support.
It really does. We read all of them, and it is great to hear what you all think, even the critical ones. Especially the critical ones, actually. That is the spirit of open source, right? Peer review.
Exactly. You can find all of our past episodes, all six hundred sixty-seven of them, at myweirdprompts.com. We have an RSS feed there for subscribers and a contact form if you want to get in touch. You can also reach us directly at show at myweirdprompts dot com. Send us your prompts, your feedback, or just say hi.
We are on Spotify, Apple Podcasts, and pretty much everywhere else you get your audio fix. We are even on some of the decentralized podcasting platforms that are popping up.
This has been My Weird Prompts. Thanks for joining us in Jerusalem today. I am Corn.
And I am Herman Poppleberry. We will see you next time. Keep your code open and your vibes high.
Take care, everyone. Goodbye.
