Open-source AI needs more than open model weights

Tim O’Reilly argues that open-source AI will be shaped less by whether model weights are downloadable than by whether developers can control, extend, and swap the pieces around them. Using Apache’s rise over Netscape and Microsoft as the historical analogy, he points to open protocols such as MCP, modifiable agent harnesses, portable memory, and shared interfaces as the architecture that keeps innovation distributed. The practical stakes are choice and adaptability: without separable models, tools, context, and applications, a few labs can turn AI from infrastructure people build with into appliances they rent.