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Training Savants: the Art and Science of Context Engineering for Agentic AI

About this Research Note

Training Savants: the Art and Science of Context Engineering for Agentic AI

Region: Global
Authors: Kevin Petrie and Florian Bigelmaier
Publishing: July 2026

AI agents know just enough to be dangerous. They can perform impressive but misguided calculations that run your business off the rails. Context engineering aims to fix this problem by helping agentic applications make safe, reliable decisions based on diverse inputs and rich metadata. But building trustworthy context requires careful workflow design, implementation, and refinement.

This research note explains why and how context engineering will propel the next wave of AI innovation. It assesses adoption patterns, requirements, use cases, and best practices based on new primary research, then explores enabling architectural approaches. We conclude by recommending principles for success

Data and AI leaders should read this report to learn:

  • What context engineering is and how it relates to semantics, metadata, and cataloging
  • How context engineering supports AI model training, inference, and RAG
  • What leading adopters can teach the rest of the market

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