Context Optimization and Orchestration

As agentic AI applications that interact with large language models move from prototype to production, the gap between a demo that impresses in a notebook and a system that performs reliably at enterprise scale is almost always a context problem.

What you'll learn
As agentic AI applications that interact with large language models move from prototype to production, the gap between a demo that impresses in a notebook and a system that performs reliably at enterprise scale is almost always a context problem.
In this course, Context Optimization and Orchestration, you will learn the skills of a practitioner who can design, deploy, debug, and continuously improve the retrieval and orchestration infrastructure that determines what an AI system knows at the moment it needs to respond.

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