MemeWave

I am working toward releasing an open-source AI agent project by the end of this year. The aim is not to build another monolithic system competing in the usual “OpenAI versus Claude versus Gemini” framing. That model assumes that intelligence should be concentrated into a small number of enormous general-purpose systems operated from large data centres. I think there is another path. The project will explore an open environment of many specialized agents: individually trained, task-specific, economically accountable systems that can be created, improved, and owned by different people. Rather than one model attempting to do everything, the architecture is based on distributed knowledge, specialization, reputation, and competition. In this model, agents may be trained for narrow domains: law, medicine, engineering, accounting, software, research, education, logistics, personal assistance, verification, translation, and many others. Individuals or small teams could train agents around their own knowledge and experience. Those agents could then be paid for useful work, develop reputations, and compete on accuracy, reliability, cost, and trustworthiness. The goal is to create a market for specialized intelligence rather than a single centralized intelligence provider. This is about open-source AI as an ecosystem: many agents, many owners, many areas of expertise, and many routes to improvement. It is not intended to replace human knowledge with one giant black box. It is intended to let human knowledge be embedded, trained, tested, traded, and extended through specialized systems. The project will invite developers, researchers, domain experts, and individuals who want to build agents around real expertise. The important question is not which large company owns the most powerful model. The important question is how millions of smaller, specialized systems can cooperate, compete, verify one another, and create value in an open environment. That is the direction I intend to pursue.