AI agents can now build their own thinking process, making them smarter and smaller

AI agents can now adapt their reasoning methods on the fly, rather than following rigid, pre-set instructions. This means they become much better at complex tasks and make fewer mistakes, even if they are smaller models.

Current AI agents often struggle with complex problems because their thinking steps are fixed in advance. This new approach allows an AI to figure out the best way to think about a problem as it goes. This means AI can tackle more complex, real-world problems without needing specific, step-by-step programming for each scenario. It also means smaller, cheaper AI models can perform as well as or better than much larger ones, changing the economics of AI deployment.