Most teams can build an AI agent in a weekend. Getting it to production — with version control, quality gates, multi-environment promotion, and audit trails — is where everything breaks down. Microsoft just shipped a reference architecture that treats that problem seriously.
The Problem It's Solving
AI agents have been stuck in a productionization gap. You can prototype fast. Shipping responsibly is another matter entirely. The gap isn't model quality — it's infrastructure. Who owns the deployment pipeline? How do you gate a release on evaluation scores, not just unit tests? How do you promote an agent from dev to test to prod without manual intervention and prayer?
Standard software teams have solved this with CI/CD rigour. The friction is applying that same rigour to AI agents, where the "code" is a combination of prompts, tool schemas, model versions, and evaluation thresholds. That combination doesn't fit neatly into a GitHub Actions workflow designed for stateless services.
Microsoft Foundry is Microsoft's answer to that gap. It's a fully managed platform for building, deploying, and governing AI agents at scale, with a first-class agent runtime and built-in lifecycle management — applicable whether you're building containerised hosted agents or declarative prompt-based agents.
