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How well does your AI understand your business's decision-making processes? In our latest podcast, we highlight the critical role of policies in context engineering and how they can shape AI responses effectively. Don’t let your AI miss out on this vital information! The context window is one of the most critical and constrained resources in AI. In this episode of the Agentic Mesh Podcast, we explain why context engineering—and treating policies and decision boundaries as first-class context—is essential for building reliable enterprise AI agents.We break down token limits, RAG shortcomings, and the idea of minimum viable context, using real-world examples to show how agents can operate safely, accurately, and at scale.Ideal for anyone working in agentic AI, enterprise AI, knowledge engineering, and AI governance.
By Eric Broda and John MillerHow well does your AI understand your business's decision-making processes? In our latest podcast, we highlight the critical role of policies in context engineering and how they can shape AI responses effectively. Don’t let your AI miss out on this vital information! The context window is one of the most critical and constrained resources in AI. In this episode of the Agentic Mesh Podcast, we explain why context engineering—and treating policies and decision boundaries as first-class context—is essential for building reliable enterprise AI agents.We break down token limits, RAG shortcomings, and the idea of minimum viable context, using real-world examples to show how agents can operate safely, accurately, and at scale.Ideal for anyone working in agentic AI, enterprise AI, knowledge engineering, and AI governance.