Design and implement multi-agent AI solutions

Learn how to design production-grade agentic AI solutions in Microsoft Foundry. This training covers stateful agentic loop architecture, hierarchical orchestration patterns, dynamic task decomposition strategies, and enterprise-scale agent communication ecosystems, including A2A protocol integration for cross-platform agent connectivity. AI-500

• Design stateful agentic loops with Microsoft Foundry agent service
• Implement advanced multi-agent orchestration patterns in Microsoft Foundry
• Apply task decomposition and agent collaboration strategies in Microsoft Foundry
• Design enterprise-scale agent communication with A2A in Azure

Learn how to implement the production-grade technical capabilities required to make multi-agent systems reliable, secure, and maintainable. This training helps learners advance from foundational prompting, tool consumption, and RAG patterns to designing multi-intervention guardrail architectures, building enterprise MCP servers, implementing hybrid RAG pipelines, and architecting durable agent memory systems with Azure Cosmos DB. AI-500

• Design advanced prompting strategies for production AI agents
• Build enterprise-grade tool ecosystems with MCP and Microsoft Foundry
• Implement advanced RAG pipelines with Azure AI Search and Microsoft Foundry
• Design multi-agent memory architectures with Azure Cosmos DB

Learn how to deploy multi-agent systems to Azure at enterprise scale and establish robust operational governance frameworks. Learners advance from foundational single-agent deployment and CI/CD patterns to coordinated multi-agent deployment pipelines, zero-trust security architecture across agent networks, enterprise-scale responsible AI governance, and full agent lifecycle management. AI-500

• Implement CI/CD pipelines for multi-agent systems with GitHub Actions
• Secure multi-agent systems with Azure zero-trust architecture
• Scale responsible AI governance with Azure AI Content Safety and Microsoft Foundry
• Govern the enterprise agent lifecycle in Microsoft Foundry

Learn how to operate production multi-agent solutions with comprehensive visibility, systematic quality assurance, cost control, and robust incident response. Learners advance from single-application monitoring and evaluation experiments to distributed multi-agent observability, LLM-as-judge evaluation for coordination quality, multi-agent cost optimization, enterprise human-in-the-loop approval workflows, and structured AI incident debugging procedures. AI-500

• Implement distributed observability for multi-agent solutions with OpenTelemetry
• Design evaluation frameworks for multi-agent solutions with Microsoft Foundry
• Optimize multi-agent performance and cost in Microsoft Foundry
• Design human-in-the-loop approval workflows with Power Automate and Microsoft Teams
• Debug and respond to production multi-agent incidents in Azure