New talk on the open model economy. I wanted to break down the case of where open model builders should steer the economics of the industry, if we want to avoid being swallowed by OpenAI and Anthropic in due time. This rests fully on being able to drive the cost of inference down dramatically on specialized, repetitive tasks, rather than trying to compete on cost with the frontier labs in any general agent. A core piece of it is how the open model economy is very fragmented, leaving an interesting puzzle we need to solve to get revenue from applications to feed back into the next model cycle. This is a very near-term problem as closed labs scale rapidly. This talk investigates: Are people using open models? How close are open models to the frontier? Mapping the open model economy How open models win This is a practice recording of my talk "How Open Models Win" for Fireworks Forge 2026 in San Francisco (3 November 2026), which will have improvements over this one.