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Foundational explainer on AI agents in Microsoft Foundry — what agents are, core components (model, instructions, tools), how they reason, plan, and act autonomously. Covers the agent runtime, tool integration, and multi-agent workflows.
Microsoft's blog on the agentic AI paradigm — common use cases, design patterns (reflection, tool use, planning, multi-agent collaboration), and how Azure enables enterprise-scale agent solutions.
Microsoft Learn training module covering AI agent fundamentals — what agents are, how they work, when to use them, and the Azure services that support agent development.
The Azure Architecture Center hub for AI workloads — baseline reference architectures, design patterns (RAG, agent orchestration, MLOps), and best practices across the AI solution lifecycle.
Best practices for integrating AI code assistants into daily development workflows — prompt engineering, context management, and team adoption patterns.
How to move beyond brittle Playwright selectors to self-healing, agent-driven UI tests using GitHub Copilot and MCP — intelligent page analysis, dynamic fallbacks, and adaptive coverage.
A curated library of skills for Dynamics 365 delivery teams. It covers a broad range of delivery scenarios — the AI First delivery skills specifically are located in the **D365 Configuration** section.
Official GitHub guide on running Copilot CLI inside Actions workflows — authentication, example YAML, and use cases like daily summaries, PR triage, and AI-assisted CI/CD tasks.
Azure DevOps platform overview — CI/CD pipelines, repos, boards, and test plans. A foundation for integrating AI-driven workflows into your delivery pipeline.
Agent orchestration patterns from Azure Architecture Center — from single-agent to multi-agent systems. Covers sequential, concurrent, group chat, handoff, and magentic patterns for cross-solution agentic implementations.
Microsoft's open-source multi-agent reference architecture — orchestrator patterns, agent registry, memory management, classifier integration, and MCP protocol support.
GitHub repository with foundational design patterns for agentic AI on Azure — RAG agent, code generation agent, multi-domain agent patterns with implementation guidance and reference architectures.
Official Python SDK samples for Azure OpenAI — chat completions, embeddings, function calling, and the Responses API with both API key and Entra ID authentication.
Open-source SDK for building AI agents and integrating LLMs into applications. Supports C#, Python, and Java. Being unified with AutoGen into the Microsoft Agent Framework.
How to use the Azure OpenAI Responses API — the recommended API for new projects. Covers model inference, streaming, tool use, and integration with Microsoft Foundry.
End-to-end Azure AI Foundry agentic AI lab for .NET developers — multi-agent architecture, agent service integration, tool binding, memory management, and evaluation.
Starter kit that rapidly deploys an Azure OpenAI instance with Python examples — Responses API, secure authentication, and production-ready patterns.
Comprehensive evaluation suite built on Microsoft Agent Framework (MAF) v1.0.0 for a Financial Advisor agent. Covers 7 evaluation categories — local, Azure AI Foundry cloud, multi-turn, traces, benchmarks, safety, and batch — with runnable Python scripts and step-by-step guidance for each pattern.
Web-based portal for managing AI projects — deploy models, build and test agents, run evaluations, monitor performance, and manage governance from a single pane of glass.
Python developer guide for Azure AI — SDK setup, authentication, building with Foundry Tools (language, vision, speech, document intelligence), and integrating AI services into applications.
Hands-on workshop for building a code-first agent with Azure AI Foundry Agent Service. Covers project setup, agent creation, tool binding, RAG integration, and deployment.
Comprehensive implementation guide for Microsoft Copilot Studio — covers architecture, development, security (slide 88+), monitoring, and governance for enterprise agent deployments.
Microsoft's AI learning hub — curated learning paths, certifications, and hands-on modules covering AI fundamentals, Azure AI services, generative AI, and responsible AI.
Webinar series from Microsoft's Customer Architecture Team (CAT) covering real-world AI implementation patterns, architecture decisions, and lessons learned from production deployments.
Partner-focused session on Microsoft's security differentiation for AI — positioning, competitive advantages, and go-to-market guidance for security partners.
Deep dive into Microsoft Purview capabilities for AI data governance — classification, DLP, compliance, and insider risk management for AI workloads.
How Microsoft Edge for Business integrates AI capabilities with enterprise security controls — secure browsing, data protection, and AI features.
Innovation session on security as the core primitive in the agentic era — covers platform security, app security, and agent security end-to-end.
Technical session on building secure AI agents using Microsoft's security stack — identity, threat protection, posture management, and governance patterns.
Deep dive into Microsoft Entra's agent identity and access management — covers agent registration, consent, delegated permissions, and monitoring.
Session on the Security Dashboard for AI — assess AI risk posture, discover AI assets, and monitor for misconfigurations and threats across your organization.
Simulated partner demo experience — walk through AI risk posture assessment scenarios in a guided Microsoft demo environment. Requires CDX access.
Simulated partner demo experience — walk through cloud AI platform protection scenarios in a guided Microsoft demo environment. Requires CDX access.
Simulated partner demo experience — walk through AI agent security risk prevention scenarios in a guided Microsoft demo environment. Requires CDX access.
Simulated partner demo experience — walk through AI security posture improvement scenarios in a guided Microsoft demo environment. Requires CDX access.
Latest release notes for Microsoft Foundry — new features, model catalog updates, agent evaluation improvements, SDK enhancements, and governance capabilities.
Overview of Copilot Studio capabilities in the 2025 release wave — multi-agent orchestration, generative AI enhancements, automated testing, new knowledge sources, and expanded automation.
Roadmap of planned features for Copilot Studio — multi-agent orchestration, generative AI improvements, automated testing, new data sources, security upgrades, and Python code execution.
End-to-end architecture for enterprise multi-agent workflow automation — Azure Container Apps for agent hosting, Semantic Kernel orchestration, Cosmos DB for state, and Foundry for AI reasoning.
Microsoft Developer blog on designing multi-agent intelligence — transitioning from monolithic to distributed agent systems, orchestration strategies, domain specialization, and enterprise governance.
Microsoft's end-to-end security model for AI agents — covers Agent 365, Entra, Defender, and Purview integration. Based on RSAC 2026 keynote content covering identity, posture management, threat protection, and data governance for autonomous agents.
Maps each OWASP Agentic AI Top 10 risk to specific mitigations across Agent 365, Copilot Studio, Entra, Defender, and Purview. Use this to build your threat mitigation strategy for agent deployments.
Deep technical guidance on defense-in-depth for autonomous agents — model layer, safety systems, and runtime controls. Grounded in Zero Trust principles for securing fully autonomous AI workloads.
How to build secure and governable AI agents using Microsoft Foundry — covers identity, access control, monitoring, and compliance patterns for agent development.
Security chapter of Microsoft's multi-agent reference architecture — covers agent identity, inter-agent trust, data boundaries, and threat models for multi-agent systems.
Microsoft's Cloud Adoption Framework guidance for AI governance — roles, responsibilities, risk management, policy enforcement, compliance monitoring, and alignment with NIST AI RMF.
Azure AI Content Safety service — detect and filter harmful content in text and images. Covers prompt shields, groundedness detection, protected material detection, custom categories, and content moderation APIs.
Cloud Adoption Framework reference architecture for agent governance — covers data, identity, observability, security, and development layers for enterprise-wide agent management.
Deployment model for securing and governing M365 Copilot agents using Microsoft Purview — covers data classification, DLP, and compliance controls for agent workloads.
How to detect and prevent data leakage to unauthorized AI services using Microsoft Purview — DLP policies, endpoint controls, and monitoring to protect sensitive data from shadow AI usage.
Official documentation on security and governance controls for Microsoft Copilot Studio — authentication, DLP, environment management, and audit logging for agent deployments.
Azure governance for AI platform services — policy enforcement, model governance, risk detection, Entra Agent ID integration, and operational standards for AI environments.
Cloud Adoption Framework guidance for responsible AI policies covering AI agent development, deployment, and operations. Provides a structured approach to governance, risk assessment, and accountability across the agent lifecycle.
Comprehensive security best practices for Azure AI services — covers authentication, network isolation, data protection, and monitoring for AI workloads.
Landing page for Microsoft's Security for AI documentation — covers threat protection, posture management, data security, and governance for AI workloads.
Microsoft's central hub for securing and governing AI — links to guidance on threat protection, posture management, data security, and compliance across AI workloads.
Latest announcements and updates on Microsoft's Security for AI capabilities — new features, product updates, and roadmap for securing AI workloads.
Official documentation for Copilot Studio — build, test, and deploy conversational AI agents with a low-code experience. Covers agent creation, topics, actions, plugins, deployment, and governance.
Step-by-step quickstart for creating your first Copilot Studio agent — topics, entities, actions, testing, and publishing.
Guidance documentation covering design patterns, performance optimization, security, responsible AI, and enterprise deployment best practices for Copilot Studio agents.
Copilot Studio's multi-agent orchestration capabilities announced at Build 2025 — agent delegation, handoff, shared context, and how Copilot Studio connects with Microsoft Foundry for advanced reasoning.
Official documentation hub for Microsoft Foundry — the unified platform for building, evaluating, and deploying AI models and agents. Covers project setup, SDKs, model catalog, agent service, evaluation, and governance.
Microsoft Learn training module — hands-on walkthrough of building an AI agent using the Foundry Agent Service. Covers agent creation, tool binding, testing, and deployment.
Self-paced learning paths on Microsoft Learn — from AI fundamentals to intermediate and advanced Foundry topics including model deployment, agent development, evaluation, and responsible AI.
Official documentation for Semantic Kernel — AI agent framework, plugins, planners, memory, and multi-agent orchestration for .NET, Python, and Java.
How to secure AI agents with Microsoft Entra Agent ID — unique agent identities, lifecycle management, conditional access, Zero Trust enforcement, and audit capabilities for autonomous AI workloads.
Azure's Security and Responsible AI Guide — applying Zero Trust principles, threat modeling, and governance to AI systems. Covers identity, access control, data protection, and compliance frameworks.
Entra Agent ID gives every AI agent a managed identity — enabling authentication, authorization, and audit trails for agent-to-agent and agent-to-resource interactions.
Developer-first platform for AI agent integration with Entra — covers agent registration, consent flows, and delegated access patterns for secure agent-to-service communication.
Official Agent 365 documentation — the control plane for agent identity, posture management, governance, and runtime monitoring at enterprise scale.
Assess your organization's AI risk posture with the Security Dashboard for AI — visibility into AI asset inventory, misconfigurations, and threat signals across your AI workloads.
Microsoft's six responsible AI principles — fairness, reliability & safety, privacy & security, inclusiveness, transparency, and accountability. The foundational framework for all AI development at Microsoft.
Microsoft Learn module on operationalizing responsible AI — governance, policies, impact assessments, and practical controls for safe AI deployment.
High-level overview of Microsoft's unified AI platform — what Foundry is, how it brings together models, agents, tools, and governance for enterprise-grade agentic AI solutions.
Official Microsoft partner training hub for the "Protect Cloud AI Platform and Apps" solution play — courses, certifications, and learning paths for security partners.
Central hub for Microsoft security partners — go-to-market resources, partner programs, and enablement materials for building and selling security solutions.
Latest news, events, and announcements for Microsoft security partners — product updates, webinars, and community events.