M365.FM - Modern work, security, and productivity with Microsoft 365

The End of Prompting: How to Build the Copilot Agent Fabric

1 h 14 min · 1. Juni 2026
Episode The End of Prompting: How to Build the Copilot Agent Fabric Cover

Beschreibung

The era of prompt engineering is rapidly coming to an end. For years, organizations have focused on crafting better prompts, refining instructions, and teaching employees how to interact with AI tools. While that approach delivered early productivity gains, it is becoming increasingly clear that prompting is not the future of enterprise AI. The next evolution is agent orchestration—an intelligent ecosystem where specialized AI agents collaborate, reason, and execute workflows autonomously.In this episode of M365FM, we explore why the traditional chatbot model has reached its limits and how Microsoft's emerging Copilot ecosystem is paving the way for a new operating model built around autonomous agents. We dive deep into the concept of the Copilot Agent Fabric, a framework that moves organizations from manual prompting toward outcome-driven automation powered by AI orchestration.WHY PROMPTING IS NO LONGER ENOUGH Most organizations still treat Copilot as a smarter search box. Users ask questions, receive answers, and manually decide what to do next. While useful, this model creates a productivity ceiling because every workflow depends on human supervision and prompt quality.Key challenges with the chatbot model include: * Prompt quality varies dramatically between users * AI adoption often plateaus after initial excitement * Workflows remain dependent on manual intervention * Organizations struggle to scale AI outcomes consistently * Productivity gains fail to compound over time The future isn't about asking better questions. It's about designing systems where AI agents own and execute complete business outcomes. UNDERSTANDING THE COPILOT AGENT FABRIC The Copilot Agent Fabric represents a fundamental architectural shift. Instead of relying on a single AI assistant to handle everything, organizations deploy specialized agents focused on specific business domains and outcomes.Within this model: * Agents own clearly defined responsibilities * Work is routed intelligently between specialists * Context is isolated to improve reasoning quality * Business workflows become autonomous * Outcomes become measurable and repeatable This approach transforms AI from a reactive assistant into an operational layer that continuously executes business processes. THE THREE PILLARS OF AGENT ORCHESTRATION The Copilot Agent Fabric is built upon three foundational components: EVENTS Events act as triggers that initiate workflows.Examples include: * New customer inquiries * Incoming emails * Contract requests * Approval deadlines * Service tickets REASONINGSpecialized agents process information within their domain of expertise.Benefits include: * Reduced hallucinations * Improved decision quality * Better governance * Stronger compliance controls * Domain-specific optimization ORCHESTRATION A parent agent coordinates the workflow and delegates work to specialists.Key orchestration capabilities include: * Agent selection * Context routing * Workflow coordination * Human escalation * Process monitoring WHY DATA ARCHITECTURE MATTERS MORE THAN PROMPTS One of the biggest insights from this episode is that AI performance is directly tied to data quality.Organizations that simply migrate file shares into SharePoint often discover that Copilot struggles to reason effectively because the underlying information architecture lacks semantic structure.To enable intelligent reasoning, organizations must focus on: * Metadata design * Relationship mapping * Knowledge modeling * Structured records * Governance frameworks The future belongs to organizations that design for answerability rather than storage. MODEL CONTEXT PROTOCOL (MCP): THE USB-C FOR AI A critical component of the emerging AI ecosystem is the Model Context Protocol (MCP).MCP provides a universal standard for connecting AI agents to enterprise systems, including: * CRM platforms * ERP solutions * Data warehouses * Knowledge bases * Internal business applications Instead of building custom integrations for every AI use case, organizations can leverage MCP as a standardized tool layer that dramatically simplifies connectivity and governance. AGENT-TO-AGENT (A2A) COLLABORATION The most powerful AI systems will not be single agents.They will be networks of specialized agents collaborating through Agent-to-Agent (A2A) protocols.Examples include: * HR agents managing employee workflows * Finance agents handling approvals * Sales agents generating proposals * Compliance agents validating policies * IT agents orchestrating infrastructure tasks A parent orchestrator coordinates these specialists to deliver complete business outcomes. BUILDING AI SKILLS WITH THE DBS FRAMEWORK The episode introduces the DBS Framework, a practical approach to building scalable AI capabilities.DIRECTIONDefines workflow logic and operational intent. BLUEPRINTS Stores reference materials such as: * Brand guidelines * Policies * Compliance rules * Procedures * Standards SOLUTIONSContains executable integrations and automation components.Examples include: * APIs * Scripts * Calculations * Connectors * External services This separation allows organizations to evolve rapidly without constantly redesigning workflows. REAL-WORLD EXAMPLE: THE 100X QUOTING WORKFLOW A powerful example discussed in the episode compares traditional quoting processes with agent-driven orchestration.Traditional quote generation often requires: * Customer research * Pricing validation * Inventory checks * Discount approvals * Compliance reviews * Executive signoff This process can take 60–90 minutes.With agent orchestration, the same workflow can be completed in approximately three minutes while maintaining compliance, consistency, and governance.The result is: * Faster deal velocity * Improved accuracy * Better customer experiences * Reduced operational costs * Greater organizational scalability GOVERNANCE, SECURITY, AND THE FUTURE OF WORK As organizations deploy more agents, governance becomes essential.Successful AI architectures require: * Least-privilege access controls * Human approval workflows * Audit trails * Agent ownership models * Centralized governance frameworks The organizations that succeed will empower departments to build specialized agents while maintaining strong security and operational oversight. KEY TAKEAWAYS If you remember only a few things from this episode, make them these: * Prompt engineering is being replaced by agent orchestration * Copilot is evolving from assistant to autonomous workflow engine * Data quality determines AI reasoning quality * MCP provides the foundation for enterprise AI connectivity * Specialized agents outperform monolithic AI systems * Governance is a business requirement, not a technical afterthought * The future belongs to agent-operated organizations The shift is already underway. The question is no longer whether organizations will adopt agent-based systems. The real question is whether they'll build the architecture, governance, and data foundations necessary to make them successful.If you're a Microsoft 365 architect, Copilot strategist, IT leader, or digital transformation professional, this episode provides a practical roadmap for moving beyond prompting and into the next era of enterprise AI. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

Kommentare

0

Sei die erste Person, die kommentiert

Melde dich jetzt an und werde Teil der M365.FM - Modern work, security, and productivity with Microsoft 365-Community!

Loslegen

2 Monate für 1 €

Dann 4,99 € / Monat · Jederzeit kündbar.

  • Podcasts nur bei Podimo
  • 20 Stunden Hörbücher / Monat
  • Alle kostenlosen Podcasts

Alle Folgen

657 Folgen

Episode From Project Online to AI-Powered Project Delivery: The Evolution of Dynamics 365 Project Operations with Joe Griffin [MVP] Cover

From Project Online to AI-Powered Project Delivery: The Evolution of Dynamics 365 Project Operations with Joe Griffin [MVP]

In this insightful episode of the M365 Podcast, host Mirko Peters welcomes Joe Griffin, Microsoft MVP, CEO of proMX UK, Microsoft Certified Trainer, and one of the most recognized experts in Dynamics 365 Project Operations. With more than 40 Microsoft certifications covering Dynamics 365, Power Platform, Azure, Artificial Intelligence, and the broader Microsoft Cloud ecosystem, Joe brings a unique blend of technical expertise, business leadership, and real-world implementation experience.The conversation explores one of the most important transitions currently happening in the Microsoft project management landscape: the retirement of Microsoft Project Online and the growing adoption of Dynamics 365 Project Operations. Joe explains why organizations should start preparing now, what migration paths are available, and how businesses can use this moment as an opportunity to modernize not only their technology stack but also their project delivery processes. UNDERSTANDING DYNAMICS 365 PROJECT OPERATIONS Joe provides a comprehensive overview of Dynamics 365 Project Operations and explains why it has become a strategic platform for project-based organizations. Unlike traditional project management tools that focus solely on task management and scheduling, Project Operations combines project planning, resource allocation, budgeting, financial management, time tracking, expense management, invoicing, and AI-driven insights into a single solution built on Microsoft Dataverse.The discussion highlights how organizations can gain end-to-end visibility across project lifecycles while improving resource utilization and financial performance. Joe also explains how Project Operations leverages familiar Microsoft technologies such as Planner, Power Platform, and Dataverse to create a connected and scalable project management environment. KEY TAKEAWAYS: * What Dynamics 365 Project Operations actually does * Who should consider adopting the platform * How it differs from traditional project management tools * Why professional services organizations benefit the most * The role of Dataverse and Power Platform PROJECT ONLINE RETIREMENT AND MIGRATION STRATEGIES A major focus of the episode is Microsoft's planned retirement of Project Online. Joe explains what the announcement means for existing customers and outlines the options available for organizations currently relying on Project Online for project planning and portfolio management.Drawing from real-world migration projects, Joe shares practical advice on preparing data, simplifying project structures, and avoiding common migration pitfalls. He also discusses the importance of reviewing legacy processes and using the migration as an opportunity to modernize project management practices.The conversation dives into technical considerations such as Project Desktop files, Scheduler APIs, resource mapping, testing environments, and large-scale migration automation. MIGRATION TOPICS COVERED: * Project Online retirement implications * Migration planning and assessment * Common data migration challenges * Managing complex project portfolios * Best practices for successful adoption HOW AI IS CHANGING PROJECT MANAGEMENT Artificial Intelligence is rapidly transforming business applications, and Dynamics 365 Project Operations is no exception. Joe explores how Microsoft is embedding AI across the platform and shares practical examples of AI-powered capabilities available today.One particularly interesting example is the Time Entry Agent, which can automatically generate draft timesheets based on calendars, resource assignments, and previous activities. Instead of chasing employees for timesheet submissions, organizations can leverage AI to automate much of the process while maintaining human oversight.The discussion also covers AI-generated project status reports, intelligent resource recommendations, project risk identification, and the future potential of autonomous project management capabilities. AI IN PROJECT OPERATIONS: * Automated time entry generation * AI-powered status reporting * Intelligent resource recommendations * Risk detection and forecasting * Future project management agents POWER PLATFORM AND AZURE INTEGRATION Joe explains why the real power of Dynamics 365 Project Operations comes from its integration with the wider Microsoft ecosystem. Because the platform is built on Dataverse, organizations can extend functionality using Power Apps, Power Automate, Power BI, Power Pages, and Azure services.Listeners will learn how companies can create custom project experiences, automate business processes, build advanced reporting solutions, and integrate Project Operations with external ERP systems. Joe also discusses how Azure Service Bus, Azure Functions, and modern integration architectures help organizations scale complex project environments.The episode provides valuable guidance for solution architects and technical leaders looking to design enterprise-grade project management solutions that remain scalable and maintainable over time. ARCHITECTURE AND EXTENSIBILITY TOPICS: * Power Apps customization strategies * Power Automate workflows * Power BI reporting and analytics * Azure integration patterns * Enterprise architecture best practices THE ROLE OF MICROSOFT FABRIC AND AI FOUNDRY Looking ahead, the conversation explores emerging technologies such as Microsoft Fabric and Azure AI Foundry. Joe explains how Fabric can serve as a centralized data foundation for AI initiatives by bringing together information from Dynamics 365, Power Platform, and other business systems.The discussion highlights how organizations that establish strong data foundations today will be better positioned to take advantage of future AI capabilities. Joe also shares his perspective on AI Foundry, model selection, fine-tuning opportunities, and the growing importance of enterprise-ready AI governance. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

17. Juni 202643 min
Episode Indirect Injection: The Silent Killer of Enterprise AI Cover

Indirect Injection: The Silent Killer of Enterprise AI

Most organizations believe their biggest AI risk is hallucination. It isn't. The real threat is something far more dangerous. A vulnerability that hides inside trusted documents. A vulnerability that bypasses access controls. A vulnerability that transforms ordinary business content into executable instructions. It's called Indirect Prompt Injection. And if your Microsoft 365 Copilot, Azure AI Foundry implementation, Power Platform solution, or enterprise AI assistant relies on Retrieval-Augmented Generation (RAG), you may already be exposed. In this episode, we explore one of the fastest-growing threats in enterprise AI security and why the architecture behind modern Copilots may contain a fundamental design flaw. We examine how poisoned documents, hidden instructions, malicious metadata, and compromised knowledge bases can manipulate AI systems without ever breaching a firewall or exploiting a traditional software vulnerability. From Microsoft 365 Copilot and SharePoint to Teams, Outlook, Power Platform, Azure OpenAI, and vector databases, we explain why organizations must stop thinking about documents as passive data and start treating them as executable code. If your organization is building AI-powered solutions on proprietary enterprise data, this episode may be one of the most important security discussions you'll hear this year. THE RAG REVOLUTION THAT CHANGED EVERYTHING Retrieval-Augmented Generation transformed enterprise AI. Instead of retraining massive models on internal data, organizations simply connect AI systems to existing knowledge repositories. We explore: * Retrieval-Augmented Generation (RAG) * Microsoft 365 Copilot architecture * Microsoft Graph integration * SharePoint knowledge retrieval * Outlook and Teams context * Vector databases * Semantic search RAG solved the enterprise knowledge problem. It also created a completely new attack surface. WHY DATA IS NO LONGER JUST DATA Traditional software separates data from code. Large Language Models do not. Every piece of text retrieved from a knowledge base becomes part of the model's prompt. The AI cannot reliably distinguish: * Facts * Instructions * Policies * Commands * Metadata * Context Everything becomes tokens. Everything influences behavior. This episode explains why the phrase "Data is Code" has become one of the most important concepts in modern AI security. UNDERSTANDING INDIRECT PROMPT INJECTION Most organizations understand direct attacks. Few understand indirect ones. Direct prompt injection occurs when an attacker interacts directly with the AI system. Indirect prompt injection happens when malicious instructions are embedded inside content the AI retrieves. We examine: * Hidden instructions * Poisoned documents * Embedded commands * Context manipulation * Retrieval abuse * Prompt hijacking The attacker never talks to the AI. The document does it for them. WHY SYSTEM PROMPTS ARE NOT A FIREWALL One of the most dangerous misconceptions in enterprise AI is the belief that system prompts provide security boundaries. They don't. We discuss: * Prompt hierarchy failures * Instruction conflicts * Context competition * Attention mechanisms * System prompt limitations * Safety override scenarios Your AI's security policies are ultimately competing with every document it reads. And sometimes the documents win. THE OWASP NUMBER ONE AI SECURITY RISK Prompt injection consistently ranks as one of the most serious risks facing AI systems today. This episode explores: * OWASP GenAI Top 10 * LLM01 Prompt Injection * AI threat modeling * Enterprise AI vulnerabilities * Security community guidance * Emerging attack patterns Prompt injection isn't theoretical. It's increasingly recognized as the primary security challenge for enterprise AI deployments. POISONING THE KNOWLEDGE BASE Attackers no longer need to compromise the model. They only need to compromise the content. We examine how adversaries weaponize: * SharePoint documents * PDFs * Wiki pages * Email archives * Teams conversations * Knowledge repositories Learn how a single poisoned document can influence thousands of future Copilot interactions. HIDDEN TEXT, METADATA, AND INVISIBLE INSTRUCTIONS The most dangerous attacks aren't visible. Organizations often review documents visually. AI systems don't. We explore: * White-on-white text * Hidden paragraphs * PDF metadata * Document properties * Embedded comments * Unicode manipulation * Invisible instructions The content humans ignore may be the content the AI obeys. THE SLEEPER AGENT PROBLEM Some attacks don't activate immediately. They wait. A poisoned document can remain dormant for months before triggering under specific conditions. We discuss: * Trigger-based attacks * Delayed activation * Backdoor behavior * Conditional instructions * Query-based triggers * Long-term persistence The attack may already exist in your environment. It simply hasn't been activated yet. MICROSOFT 365 ATTACK SURFACES YOU AREN'T MONITORING Enterprise AI reads more than most organizations realize. Potential attack vectors include: * SharePoint Online * OneDrive * Teams Chats * Outlook Email * Calendar Invites * Wiki Pages * Power Platform Data Sources * Microsoft Graph Content Every repository becomes part of the AI security perimeter. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

17. Juni 20261 h 18 min
Episode From SharePoint Developer to Power Platform Architect: Building Secure and Scalable Solutions with Michel Mendes [MVP] Cover

From SharePoint Developer to Power Platform Architect: Building Secure and Scalable Solutions with Michel Mendes [MVP]

In this episode of the M365 Podcast, Mirko Peters sits down with Microsoft MVP Michel Mendes to explore his remarkable journey from traditional SharePoint development to becoming a leading Power Platform Architect. Michel shares how he started his Microsoft technology career in Brazil, transitioned from C# and SharePoint development into the modern Power Platform ecosystem, and eventually moved to Ireland to continue building enterprise-grade solutions for organizations worldwide.Throughout the conversation, Michel provides valuable insights into how the Microsoft ecosystem has evolved over the years, the growing role of AI in software development, and why understanding architecture, governance, and security remains critical even in a low-code world. Whether you're a developer, solution architect, IT leader, or Power Platform enthusiast, this episode delivers practical guidance for building scalable and maintainable business applications. POWER PLATFORM EVOLUTION AND THE FUTURE OF DEVELOPMENT Michel discusses how Power Platform has transformed application development by enabling both professional developers and technically minded business users to build solutions faster than ever before. He also shares his perspective on how AI-powered development tools such as GitHub Copilot are changing the way applications are designed, prototyped, and maintained.Key topics include:• The transition from traditional development to low-code solutions • How AI is accelerating software delivery • Why developers who embrace AI will thrive • The future of Power Apps, Power Pages, and pro-code development • The importance of understanding business problems before building technology BUILDING ENTERPRISE POWER APPS THAT SCALE Creating an app is easy. Creating an app that remains maintainable, performant, and scalable for years is much harder.Michel explains the architectural principles that separate successful Power Platform implementations from those that struggle over time. He shares practical advice on designing reusable components, improving performance, and creating solutions that can grow alongside business requirements.Topics covered:• Power Apps design best practices • Building maintainable applications • Performance optimization strategies • Reusable components and architecture patterns • Measuring business value and user adoption DATAVERSE AS THE FOUNDATION OF MODERN BUSINESS APPLICATIONS A major part of the discussion focuses on Microsoft Dataverse and its role as the foundation for enterprise-grade Power Platform solutions.Michel explains why Dataverse is much more than a database and how it provides built-in governance, security, authentication, and scalability capabilities that help organizations avoid reinventing the wheel.Learn about:• Dataverse architecture fundamentals • Security and governance advantages • Building scalable business applications • Plugins versus Power Automate flows • Designing efficient data models POWER PAGES AND EXTERNAL BUSINESS SOLUTIONS Michel is widely recognized for his expertise in Power Pages, and this episode dives deep into how organizations can create secure, modern, and scalable external-facing websites powered by Dataverse.The conversation explores when Power Pages is the right choice, how it differs from Power Apps, and how recent innovations are making the platform even more attractive for professional developers.Highlights include:• Power Pages fundamentals • External portals and customer-facing applications • React and Angular-based SPA experiences • AI-assisted website development • Modern Power Pages architecture SECURITY, GOVERNANCE, AND WEB API BEST PRACTICES One of the most valuable sections of the episode focuses on security.Michel explains common mistakes developers make when exposing Dataverse data through Power Pages and outlines practical approaches for protecting sensitive information while maintaining usability.Topics include:• Dataverse table permissions • Column-level security • Power Pages Web API security • Common security vulnerabilities • Governance and compliance best practices • Penetration testing and security reviews COMMUNITY, CAREER GROWTH, AND MVP INSIGHTS Michel also shares his experiences as a Microsoft MVP and discusses the importance of contributing back to the Microsoft community through blogging, conference speaking, GitHub projects, and social media engagement.For professionals starting their Power Platform journey, he provides actionable advice on certifications, learning paths, and developing a long-term career strategy within the Microsoft ecosystem.This episode is packed with real-world experience, technical insights, and practical guidance for anyone looking to build secure, scalable, and future-ready solutions with Microsoft Power Platform.Whether you're a SharePoint veteran, a Power Platform developer, a solution architect, or simply curious about the future of low-code and AI-powered development, this conversation with Michel Mendes delivers valuable lessons from someone who has successfully navigated every stage of that journey. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

Gestern44 min
Episode STOP BUILDING SILOED AGENTS: The Logic App Nervous System Cover

STOP BUILDING SILOED AGENTS: The Logic App Nervous System

Everyone is building AI agents.Very few organizations are building agent architectures.Across Microsoft 365, Copilot Studio, Azure OpenAI, Power Platform, and custom AI solutions, enterprises are racing to deploy copilots, bots, assistants, and autonomous workflows. Teams are creating agents for customer service, IT support, HR onboarding, knowledge discovery, incident management, and business operations.Most of them work.At least in the demo.But something very different happens when organizations move beyond a single agent and attempt to coordinate dozens of AI-powered systems across multiple business units, multiple platforms, and multiple Microsoft 365 tenants.The result is often chaos.Disconnected bots. Duplicate integrations. Credential sprawl. Governance gaps. Broken workflows. Untraceable actions. And increasingly, AI agents that cannot collaborate because they were never designed to operate as part of a larger system.In this episode, we explore why enterprise AI is repeating the same architectural mistakes organizations made during the early API revolution, why point-to-point agent integrations are becoming unsustainable, and how Azure Logic Apps is emerging as the orchestration layer that connects reasoning, execution, governance, identity, and automation into a single enterprise nervous system.If your organization is investing in Copilot Studio, Azure OpenAI, Microsoft 365 Copilot, Power Platform, or custom AI agents, this episode provides a blueprint for building agent ecosystems that actually scale. THE CHATBOT MIRAGE Most enterprise AI projects begin with a simple success story.A team creates a bot.The bot answers questions.The demo works.The project gets funded.Then another department builds another bot.And another.And another.Soon the organization has dozens of isolated AI systems solving local problems but creating enterprise-wide complexity.We explore: * Why AI demos rarely reveal architectural weaknesses * The difference between local optimization and enterprise orchestration * How siloed agents create operational debt * Why successful pilots often fail at scale * The hidden cost of disconnected automation The problem isn't the agents.The problem is the architecture beneath them. THE POINT-TO-POINT INTEGRATION TRAP Every agent needs data.Most agents get it the wrong way.Organizations frequently allow agents to connect directly to APIs, databases, SaaS platforms, and Microsoft Graph endpoints.Initially this feels efficient.Eventually it becomes unmanageable.This episode examines: * Point-to-point integration sprawl * Credential proliferation * Duplicate business logic * Decentralized error handling * Governance fragmentation * Observability challenges The more agents you deploy, the more dangerous direct integration becomes. WHY AGENTS FAIL AT ENTERPRISE SCALE The most advanced language model in the world cannot compensate for poor architecture.We discuss why: * Reasoning is not orchestration * Intelligence is not governance * Conversation is not workflow management * Tool calling is not process execution * AI is not a replacement for enterprise integration Enterprise success depends less on model sophistication and more on execution architecture. THE STATEFUL GAPOne of the most important concepts in this episode is the distinction between reasoning and memory.Most AI agents are stateless.Enterprise processes are not.We explore: * Stateless automation * Stateful orchestration * Long-running workflows * Process persistence * Workflow recovery * Correlation and context management An employee onboarding process may last days or weeks.A chatbot conversation may last minutes.These are fundamentally different workloads. WHY COPILOTS NEED A NERVOUS SYSTEM Human brains don't directly control every muscle individually.The nervous system coordinates actions.Enterprise AI requires the same model.This episode introduces the Logic App Nervous System architecture where: * Agents reason * Logic Apps orchestrate * Connectors execute * Policies govern * Identity secures * Observability monitors The result is coordinated intelligence instead of isolated automation. AZURE LOGIC APPS AS THE ORCHESTRATION LAYER Azure Logic Apps was originally designed for enterprise integration.It is rapidly becoming one of the most important foundations for agentic workflows.We examine: * HTTP-triggered orchestrations * Event-driven automation * Workflow persistence * Long-running process support * Enterprise connectors * Business process orchestration Logic Apps becomes the central coordination layer between agents and enterprise systems. STANDARD VS CONSUMPTION ot all Logic Apps are equal.Choosing the wrong hosting model can limit scalability before your architecture even launches.We compare: * Logic Apps Consumption * Logic Apps Standard * Stateful workflows * Stateless workflows * DevOps integration * Networking capabilities * Performance characteristics For serious agent orchestration, the answer becomes increasingly clear. STATEFUL WORKFLOWS: THE MEMORY LAYER Memory is what transforms automation into orchestration.Stateful workflows provide: * Checkpointing * Persistence * Recovery * Waiting states * Approval handling * Cross-system coordination We explain why workflow memory is often more important than model memory. THE AGENT LOOP ACTION One of Microsoft's most important innovations for agentic workflows is the Agent Loop action.This episode explores: * Think-Act-Learn cycles * Tool execution * Iterative reasoning * Memory retention * AI-assisted orchestration * Workflow-native agents Rather than bolting AI onto workflows, Agent Loop embeds reasoning directly into the orchestration layer. CONNECTORS AS NEURAL PATHWAY SIn the nervous system analogy, connectors become the nerves.They connect orchestration to execution.We discuss: * Microsoft Graph * SharePoint * Teams * Outlook * Dataverse * Dynamics 365 * Azure Services * Custom APIs The orchestrator becomes the central intelligence that routes activity across the enterprise. CUSTOM CONNECTORS AND LOGIC-IN-API Modern enterprises cannot expose proprietary business logic directly to agents.Instead, they need contracts.We explore: * OpenAPI specifications * Custom connectors * Internal APIs * Enterprise service layers * Reusable business capabilities * Governance boundaries Custom connectors become the contract layer between AI and enterprise systems. THE CROSS-TENANT CHALLENGE Most organizations no longer operate in a single Microsoft 365 tenant.Mergers, acquisitions, regional operations, and regulatory requirements have changed the landscape.This episode examines: * Multi-tenant architectures * Cross-tenant identity * Microsoft Entra collaboration * Sovereign boundaries * Tenant isolation * Enterprise coordination Cross-tenant orchestration is becoming the default, not the exception. MANAGED IDENTITIES EXPLAINED Secrets are one of the biggest weaknesses in enterprise automation.We explain how managed identities eliminate: * Client secrets * Credential sprawl * Manual rotation * Shared credentials * Configuration risk Identity becomes a platform capability instead of an operational burden. WORKLOAD IDENTITY FEDERATION Cross-tenant automation introduces a new challenge.How do workloads authenticate without secrets?This episode explores: * Workload identity federation * Azure AD Token Exchange * Federated credentials * Cross-tenant trust * Secretless authentication * Zero Trust architectures This becomes one of the most important building blocks for enterprise-scale agent ecosystems. MICROSOFT ENTRA AGENT ID Identity is becoming a first-class concern for AI agents.We examine how Microsoft Entra Agent ID enables: * Agent governance * Agent identities * Blueprint-driven permissions * Security boundaries * Authorization controls * AI accountability The future of AI governance begins with identity. ERROR HANDLING AS INTELLIGENCE Failures are inevitable.Resilience is optional.We explore advanced orchestration patterns including: * Scoped error handling * Adaptive retries * Compensating transactions * AI-assisted error triage * Self-healing workflows * Recovery orchestration The goal is not preventing failure.The goal is surviving failure intelligently. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

Gestern1 h 18 min
Episode Building Multi-Agent AI Systems with Copilot Studio: From Ideas to Intelligent Automation with David Lorenzo Lopez [MVP] Cover

Building Multi-Agent AI Systems with Copilot Studio: From Ideas to Intelligent Automation with David Lorenzo Lopez [MVP]

Artificial Intelligence is rapidly evolving from simple chatbots into sophisticated multi-agent systems capable of automating complex business processes, collaborating across services, and delivering real business value. In this episode of the M365 Podcast, Mirko Peters sits down with Microsoft MVP David Lorenzo Lopez to explore the future of intelligent automation and how organizations can leverage Microsoft Copilot Studio, Azure AI Foundry, and the Microsoft Agent Framework to build scalable AI solutions.David shares his journey from web development and .NET programming to becoming a leading voice in AI-driven automation. He explains how the arrival of GPT models transformed the technology landscape and why the real challenge today is no longer generating impressive demos but creating measurable business outcomes with AI. WHAT ARE MULTI-AGENT AI SYSTEMS? One of the core topics of this conversation is the concept of multi-agent systems. David compares modern AI architectures to the evolution from monolithic applications to microservices. Instead of building one giant AI agent responsible for everything, organizations can create specialized agents focused on individual tasks and orchestrate them through a central coordinator.Key benefits include: * Improved scalability and maintainability * Better task specialization and accuracy * Easier testing and optimization * Reusable AI components across multiple business scenarios * Greater control over automation workflows COPILOT STUDIO VS AZURE AI FOUNDRY Microsoft now offers multiple ways to build AI-powered solutions, and David explains when to choose each platform.The discussion covers how Copilot Studio enables rapid low-code development using Power Platform integrations, while Azure AI Foundry provides greater flexibility, customization, and scalability for advanced AI implementations. As Microsoft continues to integrate these platforms, organizations have more options than ever to match their technical and business requirements.Topics covered include: * Copilot Studio connected agents * Azure AI Foundry orchestration * MCP connectors * Knowledge integration * Low-code versus pro-code development * AI workflow design patterns HUMAN-IN-THE-LOOP AND RESPONSIBLE AI While autonomous AI systems are becoming more capable, David strongly advocates for maintaining human oversight in critical business processes. He explains why AI should support decision-making rather than completely replace it, especially when financial, legal, or operational risks are involved.The conversation explores: * Approval workflows * Human validation processes * Governance strategies * Compliance considerations * Risk mitigation for AI automation MICROSOFT AGENT FRAMEWORK AND THE FUTURE OF AI DEVELOPMENT A major highlight of the episode is Microsoft's new Agent Framework. David explains how the framework combines capabilities from Semantic Kernel and other Microsoft AI initiatives to create a powerful platform for building enterprise-grade agents.Listeners will learn how developers can: * Create custom AI agents * Build complex orchestration workflows * Deploy scalable AI solutions * Integrate with Azure services * Develop reusable intelligent systems GOVERNANCE, SECURITY, AND THE EU AI ACT As AI adoption accelerates across Europe, governance and compliance have become essential topics. David discusses how Microsoft addresses security, data residency, privacy, and regulatory requirements through Azure AI services and emerging governance tools such as Agent 365 Control Plane.The discussion also covers: * Data protection requirements * European AI regulations * Azure OpenAI compliance * Model selection strategies * AI governance best practices CONTROLLING AI COSTS AND FINOPS One of the biggest challenges organizations face is understanding and controlling AI costs. David explains why estimating AI consumption is difficult and how businesses can establish practical monitoring and optimization strategies. Learn about: * Token consumption * Copilot Studio credits * Pay-as-you-go models * Cost optimization techniques * AI FinOps best practices KEY TAKEAWAYS This episode delivers practical insights for architects, developers, IT leaders, and business decision-makers looking to move beyond AI hype and create sustainable business value through intelligent automation.David's final message is simple yet powerful: AI is a wave that is transforming every industry. Organizations and individuals can either let it pass over them or learn how to ride it. Those who embrace AI responsibly, strategically, and thoughtfully will be best positioned for the future.CONNECT WITH M365 FMIf you enjoyed this episode, subscribe to M365 FM on Apple Podcasts, Spotify, YouTube, and your favorite podcast platform. Don't forget to leave a review and share the episode with colleagues interested in Microsoft Copilot, AI Agents, Azure AI Foundry, and the future of intelligent automation. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support [https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support?utm_source=rss&utm_medium=rss&utm_campaign=rss].

15. Juni 202654 min