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Context engineering emerges as crucial discipline for AI agent success
Industry experts identify information architecture as the determining factor between magical AI experiences and disappointing implementations.
Subscribe Who: Industry practitioners including Boris Tane, IBM VP Armand Ruiz, Microsoft executives, Google leadership, and marketing technology companies driving context engineering adoption across AI agent implementations. Why: Traditional prompt engineering proves insufficient for complex agent implementations as context quality determines performance outcomes more than model selection, requiring systematic approaches to information architecture for competitive advantage in AI-driven business environments. A LinkedIn example demonstrates how context-aware agents check calendar availability, analyze previous correspondence tone, reference recent meeting discussions, identify contact relationships, and apply customized communication preferences.
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