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How Microsoft Ships Thousands of Production AI Agents
Microsoft’s Foundry platform demonstrates that successful AI agents require 'harnesses'—robust layers for context, identity, and continuous rubric-based evaluation—not just powerful models.
What: VP Marco Casalaina outlines that Microsoft handles agent scale by treating retrieval as an agentic sub-loop (Foundry IQ), assigning agents unique Entra identities, and monitoring performance via automated rubric checks.
Why it matters: The industry is moving from simple RAG to agentic workflows where agents iteratively plan queries, manage identities, and undergo continuous evaluation to prevent drift in production.
Takeaway: Design your agentic retrieval as a multi-source, retry-capable loop that recovers from failures rather than assuming a single-shot lookup will suffice.
Decoder
- Foundry: Microsoft’s platform for building, deploying, and running enterprise AI agents and copilots.
- Entra: Microsoft's unified identity and access management platform.
- Rubric-based evaluation: A testing method using specific, use-case-tied checks to verify that an agent follows correct behavioral patterns, rather than just returning a plausible-sounding answer.
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