AI4S research today: self-evolving loops, multi-agent systems, agent skills, science benchmarks etc. --> all to make literature review, hypothesis generation, and autonomous experimentation better. Much of today's AI4S research tries to compensate for weaknesses that frontier models are rapidly eliminating anyway. Now it's become boring... While the first half of the AI4S races on how to build individual, brilliant AI scientists The true speed limit of science isn't the brilliance of the individual scientist — it is the ecosystem they work within: how knowledge is represented, shared, verified, accumulated, and reused across generations of researchers. Making every AI scientist 10x smarter while leaving the ecosystem unchanged is like putting a Formula 1 engine on a dirt road The second half of AI4S must shift from scaling agent intelligence to build an AI-Native scientific ecosystem from first principles. Read more ⬇️