This episode explores a unified framework for adapting agentic AI systems, detailing how foundation models are specialized to plan, reason, and master external tools for complex tasks. We analyze the four adaptation paradigms—A1, A2, T1, and T2—revealing how modular tool optimization can be up to 70 times more data-efficient than traditional monolithic agent retraining. Discover the shift toward symbiotic ecosystems, where stable reasoning cores work in harmony with agile, evolving tools to drive breakthroughs in software development and scientific research.

Source: https://www.arxiv.org/pdf/2512.16301