Microsoft Foundry optimizes enterprise AI agent costs via context engineering

This blog post, part of a four-part series, details strategies for 'context engineering' within Microsoft Foundry to optimize costs and improve performance for enterprise AI agents. It explains how efficiently managing an agent's context window—the information sent to the model on each turn—is critical for reducing operating expenses and enhancing answer quality. The article introduces Foundry IQ for managed knowledge retrieval, Toolboxes for streamlined tool access, Skills for reusable procedural guidance, and Memory for persistent context across interactions. These capabilities enable engineers and architects to build more cost-effective and accurate AI agents.