Generative AI for Beginners - Full Videos Series Released!
With so many new technologies, tools and terms in the world of Generative AI, it can be hard to know where to start or what to learn next. "Generative AI for Beginners" is designed to help you on your learning journey no matter where you are now. We are happy announce that the "Generative AI for Beginners" course has received a major refresh - 18 new videos for each lesson.How to Build AI Agents in 10 Lessons
Microsoft has released an excellent learning resource for anyone looking to dive into the world of AI agents: "AI Agents for Beginners". This comprehensive course is available free on GitHub. It is designed to teach the fundamentals of building AI agents, even if you are just starting out. What You'll Learn The course is structured into 10 lessons, covering a wide range of essential topics including: Agentic Frameworks: Understand the core structures and components used to build AI agents. Design Patterns: Learn proven approaches for designing effective and efficient AI agents. Retrieval Augmented Generation (RAG): Enhance AI agents by incorporating external knowledge. Building Trustworthy AI Agents: Discover techniques for creating AI agents that are reliable and safe. AI Agents in Production: Get insights into deploying and managing AI agents in real-world applications. Hands-On Experience The course includes practical code examples that utilize: Azure AI Foundry GitHub Models These examples help you learn how to interact with Language Models and use AI Agent frameworks and services from Microsoft, such as: Azure AI Agent Service Semantic Kernel Agent Framework AutoGen - A framework for building AI agents and applications Getting Started To get started, make sure you have the proper set-up. Here are the 10 lessons Intro to AI Agents and Agent Use Cases Exploring AI Agent Frameworks Understanding AI Agentic Design Principles Tool Use Design Pattern Agentic RAG Building Trustworthy AI Agents Planning Design Multi-Agent Design Patterns Metacognition in AI Agents AI Agents in Production Multi-Language Support To make learning accessible to a global audience, the course offers multi-language support. Get Started Today! If you are eager to learn about AI agents, this course is an excellent starting point. You can find the complete course materials on GitHub at AI Agents for Beginners.Essential Microsoft Resources for MVPs & the Tech Community from the AI Tour
Unlock the power of Microsoft AI with redeliverable technical presentations, hands-on workshops, and open-source curriculum from the Microsoft AI Tour! Whether you’re a Microsoft MVP, Developer, or IT Professional, these expertly crafted resources empower you to teach, train, and lead AI adoption in your community. Explore top breakout sessions covering GitHub Copilot, Azure AI, Generative AI, and security best practices—designed to simplify AI integration and accelerate digital transformation. Dive into interactive workshops that provide real-world applications of AI technologies. Take it a step further with Microsoft’s Open-Source AI Curriculum, offering beginner-friendly courses on AI, Machine Learning, Data Science, Cybersecurity, and GitHub Copilot—perfect for upskilling teams and fostering innovation. Don’t just learn—lead. Access these resources, host impactful training sessions, and drive AI adoption in your organization. Start sharing today! Explore now: Microsoft AI Tour Resources.Introducing DiskANN Vector Index in Azure Database for PostgreSQL
We're thrilled to announce the preview of DiskANN, a leading vector indexing algorithm, on Azure Database for PostgreSQL - Flexible Server! Developed by Microsoft Research and used extensively at Microsoft in global services such as Bing and Microsoft 365, DiskANN enables developers to build highly accurate, performant and scalable Generative AI applications surpassing pgvector’s HNSW and IVFFlat in both latency and accuracy. DiskANN also overcomes a long-standing limitation of pgvector in filtered vector search, where it occasionally returns incorrect results.Building Intelligent Applications with Local RAG in .NET and Phi-3: A Hands-On Guide
Let's learn how to do Retrieval Augmented Generation (RAG) using local resources in .NET! In this post, we’ll show you how to combine the Phi-3 language model, Local Embeddings, and Semantic Kernel to create a RAG scenario.Building the Ultimate Nerdland Podcast Chatbot with RAG and LLM: Step-by-Step Guide
Large Language Models (LLMs) are popular in tech. In Belgium and the Netherlands, the podcast "Nerdland" is a favorite for tech and science fans. It covers topics like bioscience, space, robotics, and AI. With over 100 episodes, "Nerdland" is a goldmine of information. So, why not create a chatbot for "Nerdland" fans? This chatbot uses podcast content to engage and inform users. It allows the "Nerdland" community to interact with the content in new ways and makes the information accessible in many languages, thanks to LLMs' multi-language capabilities. This blog post explains the project's technical details, including the LLMs used, integration process, and deployment on Azure.🤖 Agent Loop Demos 🤖
We announced the public preview of agent loop at Build 2025. Agent Loop is a new feature in Logic Apps to build AI Agents for use cases that span across industry domains and patterns. Here are some resources to learn more about them Logic Apps Labs - https://aka.ms/lalabs Agent in a day workshop - https://aka.ms/la-agent-in-a-day In this article, share with you use cases implemented in Logic Apps using agent loop and other features. This video shows a conversational agent that answers questions about Health Plans and their coverage. The demo features document ingestion of policy documents in AI Search and then retrieving them in Agent loop using natural language This video shows an autonomous agent that generates sales report. The demo features Python Code Interpreter which analyzed excel data and aggregates it for the LLM to reason on it This video shows a conversational agent that helps recruiters with candidate screening and interview scheduling. The demo features OBO (On-Behalf-Of) where agent uses tools in the security context of user. This video shows a conversational agent for a Utility company. The demo features multi agent orchestration using handoff, and a native chat client that supports multi turn conversations and streaming, and is secured via Entra for user authentication This video shows an autonomous Loan Approval Agent specifically that handles auto loans for a bank. The demo features an AI Agent that uses an Azure Open AI model, company's policies, and several tools to process loan application. For edge cases, huma in involved via Teams connector. This video shows an autonomous Product Return Agent for Fourth Coffee company. The returns are processed by agent based on company policy, and other criterions. In this case also, a human is involved when decisions are outside the agent's boundaries This video shows a commercial agent that grants credits for purchases of groceries and other products, for Northwind Stores. The Agent extracts financial information from an IBM Mainframe and an IBM i system to assess each requestor and updates the internal Northwind systems with the approved customers information. Multi-Agent scenario including both a codeful and declarative method of implementation. Note: This is pre-release functionality and is subject to change. If you are interested in further discussing Logic Apps codeful Agents, please fill out the following feedback form. Operations Agent (part 1): In this conversational agent, we will perform Logic Apps operations such as repair and resubmit to ensure our integration platform is healthy and processing transactions. To ensure of compliance we will ensure all operational activities are logged in ServiceNow. Operations Agent (part 2): In this autonomous agent, we will perform Logic Apps operations such as repair and resubmit to ensure our integration platform is healthy and processing transactions. To ensure of compliance we will ensure all operational activities are logged in ServiceNow.🎉Announcing General Availability of Agent Loop in Azure Logic Apps
Transforming Business Automation with Intelligent, Collaborative Multi-Agentic workflows! Agent Loop is now Generally Available in Azure Logic Apps Standard, turning Logic Apps platform into a complete multi-agentic automation system. Build AI agents that work alongside workflows and humans, secured with enterprise-grade identity and access controls, deployed using your existing CI/CD pipelines. Thousands of customers have already built tens of thousands of agents—now you can take them to production with confidence. Get Started | Workshop | Demo Videos | Ignite 2025 Session | After an incredible journey since we introduced Agent Loop at Build earlier this year, we're thrilled to announce that Agent Loop is now generally available in Azure Logic Apps. This milestone represents more than just a feature release—it's the culmination of learnings from thousands of customers who have been pushing the boundaries of what's possible with agentic workflows. Agent Loop transforms Azure Logic Apps into a complete multi-agentic business process automation platform, where AI agents, automated workflows, and human expertise collaborate seamlessly to solve complex business challenges. With GA, we're delivering enterprise-grade capabilities that organizations need to confidently deploy intelligent automation at scale. The Journey to GA: Proven by Customers, Built for Production Since our preview launch at Build, the response has been extraordinary. Thousands of customers—from innovative startups to Fortune 500 enterprises—have embraced Agent Loop, building thousands of active agents that have collectively processed billions of tokens every month for the past six months. The growth of agents, executions, and token usage has accelerated significantly, doubling month over month. Since the launch of Conversational Agents in September, they already account for nearly 30% of all agentic workflows. Across the platform, agentic workflows now consume billions of tokens, with overall token usage increasing at nearly 3× month over month. Cyderes: 5X Faster Security Investigation Cycles Cyderes leveraged Agent Loop to automate triage and handling of security alerts, leading to faster investigation cycles and significant cost savings. "We were drowning in data—processing over 10,000 alerts daily while analysts spent more time chasing noise than connecting narratives. Agent Loop changed everything. By empowering our team to design and deploy their own AI agents through low-code orchestration, we've achieved 5X faster investigation cycles and significant cost savings, all while keeping pace with increasingly sophisticated cyber threats that now leverage AI to operate 25X faster than traditional attacks." – Eric Summers, Engineering Manager - AI & SOAR Vertex Pharmaceuticals: Hours Condensed to Minutes Vertex Pharmaceuticals unlocked knowledge trapped across dozens of systems via a team of agents. VAIDA, built with Logic Apps and Agent Loop, orchestrates multiple AI agents and helps employees find information faster, while maintaining compliance and supporting multiple languages. "We had knowledge trapped across dozens of systems—ServiceNow, documentation, training materials—and teams were spending valuable time hunting for answers. Logic Apps Agent Loop changed that. VAIDA now orchestrates multiple AI agents to summarize, search, and analyze this knowledge, then routes approvals right in Teams and Outlook. We've condensed hours into minutes while maintaining compliance and delivering content in multiple languages." – Pratik Shinde, Director, Digital Infrastructure & GenAI Platforms Where Customers Are Deploying Agent Loop Customers across industries are using Agent Loop to build AI applications that power both everyday tasks and mission-critical business processes across Healthcare, Retail, Energy, Financial Services, and beyond. These applications drive impact across a wide range of scenarios: Developer Productivity: Write code, generate unit tests, create workflows, map data between systems, automate source control, deployment and release pipelines IT Operations: Incident management, ticket and issue handling, policy review and enforcement, triage, resource management, cost optimization, issue remediation Business Process Automation: Empower sales specialists, retail assistants, order processing/approval flows, and healthcare assistants for intake and scheduling Customer & Stakeholder Support: Project planning and estimation, content generation, automated communication, and streamlined customer service workflows Proven Internally at Microsoft Agent Loop is also powering Microsoft and Logic Apps team's own operations, demonstrating its versatility and real-world impact: IcM Automation Team: Transforming Microsoft's internal incident automation platform into an agent studio that leverages Logic Apps' Agent Loop, enabling teams across Microsoft to build agentic live site incident automations Logic Apps Team Use Cases: Release & Deployment Agent: Streamlines deployment and release management for the Logic Apps platform Incident Management Agent: An extension of our SRE Agent, leveraging Agent Loop to accelerate incident response and remediation Analyst Agent: Assists teams in exploring product usage and health data, generating insights directly from analytics What's Generally Available Today Core Agent Loop Capabilities (GA) Agent Loop in Logic Apps Standard SKU - Support for both Autonomous and Conversational workflows Autonomous workflows run agents automatically based on triggers and conditions Conversational workflows use A2A to enable interactive chat experiences with agents On-Behalf-Of Authentication - Per-user authentication for 1st-party and 3rd-party connectors Agent Hand-Off - Enable seamless collaboration in multi-agent workflows Python Code Interpreter - Execute Python code dynamically for data analysis and computation Nested Agent Action - Use agents as tools within other agents for sophisticated orchestration User ACLs Support - Fine-grained document access control for knowledge Exciting New Agent Loop Features in Public Preview We've also released several groundbreaking features in Public Preview: New Designer Experience - Redesigned interface optimized for building agentic workflows Agent Loop in Consumption SKU - Deploy agents in the serverless Consumption tier MCP Support - Integrate Model Context Protocol servers as tools, enabling agents to access standardized tool ecosystems AI Gateway Integration - Use Azure AI Gateway as a model source for unified governance and monitoring Teams/M365 Deployment - Deploy conversational agents directly in Microsoft Teams and Microsoft 365 Okta Identity Provider - Use Okta as the identity provider for conversational agents Here’s our Announcement Blog for these new capabilities Built on a Platform You Already Trust Azure Logic Apps is already a proven iPaaS platform with thousands of customers using it for automation – ranging from startups to 100% of Fortune 500 companies. Agent Loop doesn't create a separate "agentic workflow automation platform" you have to learn and operate. Instead, it makes Azure Logic Apps itself your agentic platform: Workflows orchestrate triggers, approvals, retries, and branching Agent Loop, powered by LLMs, handle reasoning, planning, and tool selection Humans stay in control through approvals, exceptions, and guided hand-offs Agent Loop runs inside your Logic Apps Standard environment, so you get the same benefits you already know: enterprise SLAs, VNET integration, data residency controls, hybrid hosting options, and integration with your existing deployment pipelines and governance model. Enterprise Ready - Secure, User-Aware Agents by Design Bringing agents into the enterprise only works if security and compliance are first-class. With Agent Loop in Azure Logic Apps, security is built into every layer of the stack. Per-User Actions with On-Behalf-Of (OBO) and Delegated Permissions Many agent scenarios require tools to act in the context of the signed-in user. Agent Loop supports the OAuth 2.0 On-Behalf-Of (OBO) flow so that supported connector actions can run with delegated, per-user connections rather than a broad app-only identity. That means when an agent sends mail, reads SharePoint, or updates a service desk system, it does so as the user (where supported), respecting that user's licenses, permissions, and data boundaries. This is critical for scenarios like IT operations, HR requests, and finance approvals where "who did what" must be auditable. Document-Level Security with Microsoft Entra-Based Access Control Agents should only see the content a user is entitled to see. With Azure AI Search's Entra-based document-level security, your retrieval-augmented workflows can enforce ACLs and RBAC directly in the index so that queries are automatically trimmed to documents the user has access to. Secured Chat Entry Point with Easy Auth and Entra ID The built-in chat client and your custom clients can be protected using App Service Authentication (Easy Auth) and Microsoft Entra ID, so only authorized users and apps can invoke your conversational endpoints. Together, OBO, document-level security, and Easy Auth give you end-to-end identity and access control—from the chat surface, through the agent, down to your data and systems. An Open Toolbox: Connectors, Workflows, MCP Servers, and External Agents Agent Loop inherits the full power of the Logic Apps ecosystem and more - 1,400+ connectors for SaaS, on-premises, and custom APIs Workflows and agents as tools - compose sophisticated multi-step capabilities MCP server support - integrate with the Model Context Protocol for standardized tool access (Preview) A2A protocol support - enable agent-to-agent communication across platforms Multi-model flexibility - use Azure OpenAI, Azure AI Foundry hosted models, or bring your own model on any endpoint via AI gateway You're not locked into a single vendor or model provider. Agent Loop gives you an open, extensible framework that works with your existing investments and lets you choose the right tools for each job. Run Agents Wherever You Run Logic Apps Agent Loop is native to Logic Apps Standard, so your agentic workflows run consistently across cloud, on-premises, or hybrid environments. They inherit the same deployment, scaling, and networking capabilities as your workflows, bringing adaptive, AI-driven automation to wherever your systems and data live. Getting Started with Agent Loop We're in very exciting times, and we can't wait to see our customers go to production and realize the benefits of these capabilities for their business outcomes and success. Here are some useful links to get started on your AI journey with Logic Apps! Logic Apps Labs - https://aka.ms/LALabs Workshop - https://aka.ms/la-agent-in-a-day Demos - https://aka.ms/agentloopdemos
