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How do we make AI smarter without constantly retraining it? This episode explores a new framework called ACE, or Agentic Context Engineering, that treats an AI’s instructions not as a static prompt, but as a dynamic, evolving “playbook.” We discuss how this method helps AI learn from its mistakes, accumulate knowledge, and even allows smaller models to compete with giants like GPT-4. Join us as we break down the problems of “brevity bias” and “context collapse” and explore a future of more efficient, self-improving AI systems.