The Cathedral, the Bazaar & the AI Economy
Two documentaries I watched in college helped inspire me to become an entrepreneur.
The first was Triumph of the Nerds, Robert X. Cringely’s history of the personal computer industry. It showed how hobbyists, programmers, and self-described nerds turned computers from machines owned by governments, universities, and giant corporations into products ordinary people could buy.
The second was Revolution OS, the story of Linux, free software and open source. Richard Stallman, Linus Torvalds, and Eric Raymond explained how people distributed around the world could collectively build software that competed with the largest technology companies.
Together, the films gave me a way to see technology markets. Something powerful gets built inside a company, university, or government. Eventually the cost falls, access expands, and a new group of builders arrives. Many of the biggest businesses emerge from that change.
I have spent much of my career making some version of this bet. When we started Percolate in 2011, cloud infrastructure and SaaS were still moving into the enterprise. Alephic is based on a similar belief: AI enables companies to build differentiated software that makes them titans of their industry.
The part I understand more clearly now is that open and closed systems are not opponents. The personal-computing revolution needed both, and the AI revolution will too.
The Cathedral Inside the Bazaar
Eric Raymond was a programmer and one of the early advocates for what became known as open source. In 1997, he presented The Cathedral and the Bazaar, an essay he later expanded into a book.
The book was part software case study, part management theory, and part manifesto. Raymond was trying to explain something the commercial software industry found difficult to believe: Linux was being built in public by people distributed around the world, yet it was becoming a serious operating system.
Raymond contrasted two development models. The cathedral model assumed that complex software required a small group of experts working privately against a master plan. Users received finished releases but had little visibility into how the software was built.
The bazaar model released software early and often. Users could inspect it, test it, report problems, and contribute improvements. They became part of the development process.
Raymond’s thesis was more specific than “open beats closed.” He argued that complexity could be managed by widening participation, as long as the project had leadership capable of setting direction and filtering contributions. His famous observation was that “given enough eyeballs, all bugs are shallow.” More people looking at a problem increased the likelihood that somebody would understand it.
At the time, operating systems were primarily cathedrals. Microsoft built Windows internally. Apple controlled Macintosh. Even Sun, IBM, and HP maintained their own versions of Unix. Small groups made the decisions and handed finished releases to users.
Linux, on the other hand, followed the bazaar model. Developers could inspect the source code, test it on different hardware, and submit improvements. But Linux was never leaderless. Linus Torvalds decided what entered the kernel, and maintainers determined which contributions were accepted. The project was open without being a free-for-all.
The wider PC industry developed through similar combinations. Microsoft controlled Windows but distributed it across an enormous ecosystem of hardware manufacturers and software developers. Apple maintained tighter control over the complete product, then later built its modern operating systems on Unix and then, most famously, the App Store. Linux relied on open participation, strong maintainers, corporate funding, and companies that turned community software into enterprise products.
The PC era never settled the argument bet
ween cathedrals and bazaars. Its most important ecosystems combined them. Open source did not destroy the software business either. It made foundational technology available to more builders, moving value into applications, services, cloud infrastructure, and problems the original creators would never have pursued.
Kimi K3 and the Same Pattern
Kimi K3 was recently released, and it compresses this history into a new and very impressive model.
Moonshot AI built a 2.8-trillion-parameter model with native vision and a one-million-token context window. At launch, Artificial Analysis ranked it fourth among 187 comparable models. That would be impressive for any lab. It is even more notable coming from an organization other than Google, OpenAI, Anthropic, and the handful of American companies most people assume own the frontier.
At the same time, K3 was built like a cathedral. Training a model of this size requires concentrated compute, capital, data, and engineering. Moonshot made the architectural decisions, coordinated the training run, and absorbed the risk.
Moonshot now plans to release the full weights. At the time of writing, that release is still a promise, but we should assume it will happen. Once the weights are available, developers will be able to host, optimize, and adapt the model. Researchers will find weaknesses. Enterprises will connect it to their own data. Entrepreneurs will apply it to problems Moonshot would never pursue itself.
Linux was built in the bazaar from the beginning. K3 is taking a different route: cathedral first, bazaar second. That may become one of the defining patterns of AI. Cathedrals will concentrate the resources required to push the frontier. Bazaars will spread those advances and discover more uses for them.
The open-model debate on Twitter/X often jumps from frontier companies are going to take over the world to frontier labs will collapse because of rapid open-source commoditization. I think that misses the economic mechanism of how these markets will develop. Open models can make today’s capability common and put pressure on prices at the model layer. But cheaper intelligence increases use. More use creates new applications, more infrastructure demand, more feedback, and a larger market for the frontier to continue to invest forward.
The AI Economy Needs Both
Open-model progress will put pressure on frontier companies, but it will not commoditize them away. Kimi K3 does not make Anthropic a bad business, any more than Linux made Windows or the Mac irrelevant. It makes powerful intelligence cheaper and more available. That leads to more use, more products and a larger market.
That larger market pulls both sides forward. Open models push down costs and spread access. Proprietary labs push the frontier and give everyone else new capabilities to work with. At the model layer, cathedrals and bazaars compete. At the market level, they compound.
For companies and builders, this is all good news. They get better models at lower prices and can build downstream from trillions of dollars in investment. Their durable advantage comes from customer knowledge, proprietary context, workflows, distribution, and trust.
Kevin Kelly’s line is: “Technology wants to be free. Not free as in free beer, but free as in freedom.” In AI, that freedom means more people can use, adapt and build with powerful intelligence. The question changes from “Can I get access?” to “What can I build now that this exists?”
AI will need cathedrals capable of concentrating capital, compute and talent. It will need bazaars to spread those advances and discover uses their creators never imagined. AI will become more powerful, and more valuable, because both exist.