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

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

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

Written by: Mirko Peters - Founder of m365.fm m365.show and m365con.net
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Welcome to the M365.FM — your essential podcast for everything Microsoft 365, Azure, and beyond. Join us as we explore the latest developments across Power BI, Power Platform, Microsoft Teams, Viva, Fabric, Purview, Security, and the entire Microsoft ecosystem. Each episode delivers expert insights, real-world use cases, best practices, and interviews with industry leaders to help you stay ahead in the fast-moving world of cloud, collaboration, and data innovation. Whether you're an IT professional, business leader, developer, or data enthusiast, the M365.FM brings the knowledge, trends, and strategies you need to thrive in the modern digital workplace. Tune in, level up, and make the most of everything Microsoft has to offer. M365.FM is part of the M365-Show Network.

Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.Copyright Mirko Peters / m365.fm - Part of the m365.show Network - News, tips, and best practices for Microsoft 365 admins Hourly Politics & Government
Episodes
  • Microsoft Fabric Apps - Simply Explained

    Microsoft Fabric Apps - Simply Explained
    Jul 30 2026
    Microsoft Fabric Apps are a new way to build modern, data-driven web applications directly inside Microsoft Fabric. Rather than managing servers, APIs, databases, authentication, and hosting separately, Fabric provides these services automatically, allowing developers and data professionals to focus on creating business applications instead of infrastructure. A Fabric App can either connect to an existing Power BI semantic model or include its own managed SQL database, making it suitable for everything from interactive dashboards to operational business applications. This significantly lowers the barrier to building enterprise-grade solutions while keeping security, governance, and scalability within the Microsoft ecosystem.

    HOW MICROSOFT FABRIC APPS WORK
    Every Fabric App combines several managed services into a single application platform. When you create a new app, Microsoft Fabric automatically provisions a SQL database, GraphQL API, Microsoft Entra ID authentication, and static web hosting. Developers no longer need to configure backend infrastructure manually. Instead, they can concentrate on designing user experiences, building forms, creating dashboards, and implementing business logic. Fabric handles the underlying platform, making application development significantly faster than traditional full-stack approaches.

    FABRIC APPS VS POWER BI
    One of the biggest misconceptions is that Fabric Apps replace Power BI. They do not. Instead, both products solve different problems while sharing the same governed data foundation. Power BI remains Microsoft's leading business intelligence platform for analytics, reporting, dashboards, drill-through analysis, natural language queries, and executive reporting. Fabric Apps extend these capabilities by enabling custom web applications that can both display and write data. This makes them ideal for operational workflows such as inventory management, approval systems, CRM solutions, and internal business tools where users need to interact with data rather than simply analyze it.

    REAL-WORLD USE CASES FOR FABRIC APPS
    Fabric Apps are designed for business scenarios that require custom user experiences while still leveraging trusted enterprise data. Organizations can build inventory management systems with write-back capabilities, HR onboarding portals, expense approval applications, operational dashboards, customer feedback systems, and rapid business prototypes. Because Fabric Apps can connect directly to Power BI semantic models, organizations reuse existing DAX calculations, relationships, and governance policies without rebuilding business logic. This creates a single source of truth across both analytical reports and operational applications.

    CURRENT LIMITATIONS OF MICROSOFT FABRIC APPS
    Since Fabric Apps are currently in Public Preview, organizations should understand their current limitations before adopting them in production. Authentication currently supports only Microsoft Entra ID users, making the platform suitable for internal applications rather than customer-facing solutions. Applications also consume Microsoft Fabric Capacity Units (CUs), meaning performance and cost planning remain important considerations. In addition, advanced transactional scenarios, stored procedures, and highly complex business workflows may still require traditional development approaches. While AI-assisted development accelerates application creation, developers still benefit from understanding frontend technologies such as JavaScript and TypeScript.

    SHOULD YOU START LEARNING FABRIC APPS?
    If you're already working with Microsoft Fabric or Power BI, Fabric Apps represent one of the most important additions to the Microsoft data platform. They expand what organizations can build without replacing existing reporting investments, allowing the same semantic models and governed datasets to power both analytics and business applications. The best way to get started is by enabling the Fabric Apps preview, experimenting with both the Blank App and Data App templates, and exploring how custom applications can extend your existing Microsoft Fabric environment. Learning the platform today will prepare you for the broader capabilities expected as Fabric Apps move toward general availability.

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    17 mins
  • Beyond the Prompt: Mastering Microsoft Copilot for Real Productivity with Jess Stratton [MVP]

    Beyond the Prompt: Mastering Microsoft Copilot for Real Productivity with Jess Stratton [MVP]
    Jul 30 2026
    Jess Stratton shares her unique career journey from independent Lotus Notes developer to one of the world's most recognized Microsoft 365 educators. After joining LinkedIn Learning, she created training for millions of learners while continuously adapting to Microsoft's rapidly evolving ecosystem. Today, as a Microsoft MVP, TEDx speaker, author, and founder of Nerd Girl Jess LLC, she focuses on helping organizations move beyond simply using Microsoft Copilot toward fundamentally changing the way people work. Her story highlights how continuous learning, curiosity, and community can create extraordinary career opportunities in technology.WHY COPILOT ADOPTION FAILS IN MANY ORGANIZATIONSBuying Microsoft Copilot licenses is only the beginning. Jess explains that many organizations invest heavily in AI but struggle to demonstrate measurable business value because employees are taught where Copilot's buttons are instead of learning how AI actually improves their daily work. Successful adoption requires showing employees practical productivity gains, helping them solve real business problems, and demonstrating why Copilot makes their jobs easier rather than simply introducing another piece of software. Organizations that focus on outcomes instead of features consistently achieve better long-term adoption.HUMAN BEHAVIOR IS THE BIGGEST OBSTACLEWhile many organizations assume governance or technology limits Copilot adoption, Jess believes the real challenge is people. Microsoft already provides strong governance capabilities, security controls, pilot programs, and enterprise protections. The real issue is convincing employees to change established habits and trust AI as part of their daily workflow. Until users understand how Copilot benefits their individual responsibilities, even the best technical deployment will fail to achieve widespread adoption.TRAINING MUST EVOLVE BEYOND FEATURESTraditional software training focuses on explaining menus and features. AI requires a completely different approach. Jess explains that modern Copilot training should answer a different question: How will this improve my work? Instead of showing every feature inside Word, Excel, Teams, or Outlook, trainers should demonstrate concrete productivity improvements, realistic business scenarios, and repeatable workflows that employees can immediately apply. Helping users experience small wins early dramatically increases long-term adoption.THE POWER OF CUSTOM PROMPT GALLERIESOne of Jess's favorite new Microsoft Copilot capabilities is the ability for organizations to build department-specific Prompt Galleries. Rather than forcing employees to invent prompts from scratch, IT teams can provide reusable prompts tailored for HR, Finance, Marketing, Legal, Customer Service, Sales, or Operations. Because every company has unique terminology, business processes, and workflows, these curated prompts significantly reduce the learning curve while helping users experience immediate business value.WHY MOST PEOPLE STILL PROMPT POORLY Many users expect Copilot to generate perfect results after entering a single sentence. Jess explains that this misconception leads to disappointment. The best prompts clearly define four key elements: the goal, the business context, relevant source information, and detailed expectations about the desired output. Instead of simply asking Copilot to "write a report," users should specify the audience, tone, length, formatting, business purpose, and constraints. The more clearly expectations are communicated, the better Copilot performs.CHOOSING THE RIGHT MODEL MATTERSModern Microsoft Copilot offers access to multiple AI models, yet many users leave the default setting unchanged. Jess encourages people to experiment with different models using identical prompts to understand how dramatically responses can differ. Some models prioritize reasoning, others creativity, while some focus on speed or factual consistency. Becoming an effective Copilot user increasingly requires understanding not only prompt engineering but also selecting the most appropriate model for each task.AI SHOULD CHANGE THE WAY YOU WORKOne of the biggest mistakes organizations make is using AI to automate inefficient workflows instead of redesigning work itself. Jess believes Copilot gives businesses a rare opportunity to rethink long-established processes. Rather than recreating old manual habits with AI, organizations should simplify workflows, eliminate unnecessary steps, organize prompts, create reusable agents, and build scalable solutions that remain maintainable for years instead of becoming another layer of technical debt.WHY PERSONALIZATION CHANGES EVERYTHINGPersonalization is one of the most overlooked features inside Microsoft Copilot. Jess explains how users can customize writing styles, preferred formatting, Outlook tone, meeting summaries, PowerPoint branding, Teams meeting templates, and persistent memory to create much more natural ...
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    54 mins
  • The Death of the Chatbot: Why Your Dataverse Strategy Is Broken

    The Death of the Chatbot: Why Your Dataverse Strategy Is Broken
    Jul 29 2026
    Microsoft Copilot has transformed how organizations interact with AI, making conversational experiences more accessible than ever. But while chat-based AI delivers immediate productivity gains, it does not provide the architectural foundation required for enterprise-scale autonomous agents. As organizations deploy more AI solutions across departments, they quickly encounter governance challenges, identity issues, fragmented integrations, and uncontrolled costs. Copilot is an excellent interface—but it is only one layer of a much larger AI ecosystem.

    AGENT IDENTITY, GOVERNANCE, AND SECURITY FOR ENTERPRISE AI
    One of the biggest challenges in enterprise AI is identity. Many organizations still allow AI agents to operate under shared service accounts or even employee credentials, making auditing nearly impossible. Every autonomous agent should have its own dedicated identity, least-privilege permissions, and complete traceability. Combined with centralized governance, organizations gain full visibility into who—or what—accessed sensitive data, ensuring compliance with standards such as GDPR, SOC 2, and industry-specific regulations.

    FROM RAG TO ONTOLOGIES: BUILDING AGENTS THAT UNDERSTAND BUSINESS CONTEXT
    Traditional Retrieval-Augmented Generation (RAG) systems retrieve documents and generate answers based on matching text. While useful, they rarely understand how a business actually operates. Agent Mesh architectures replace document-centric reasoning with ontologies that model customers, products, suppliers, policies, and business relationships. Instead of searching for words, AI agents reason over structured knowledge, dramatically improving accuracy, consistency, and decision-making across the enterprise.

    THE AI LANDING ZONE: CENTRALIZED CONTROL FOR AGENT MESH
    Scaling dozens or even hundreds of AI agents requires more than good prompts. Organizations need a dedicated AI Landing Zone that combines identity management, governance policies, model gateways, observability, cost controls, and centralized approval processes. Every model request flows through a governance layer where security, regional compliance, budget limits, and policy enforcement are applied automatically. This approach transforms isolated AI projects into a standardized enterprise platform capable of supporting large-scale autonomous operations.

    AGENT 365, OBSERVABILITY, AND FINOPS FOR RESPONSIBLE AI
    Managing AI at scale requires complete operational visibility. A centralized control plane such as Agent 365 enables organizations to inventory agents, monitor usage, assign ownership, retire unused "ghost agents," and analyze every model invocation. Combined with comprehensive observability and FinOps practices, businesses can optimize token consumption, enforce budgets, detect abnormal behavior, and maintain continuous compliance while significantly reducing operational costs.

    THE FUTURE OF MICROSOFT AI: FROM COPILOT TO THE AGENT MESH
    The next generation of enterprise AI is no longer about individual chatbots—it is about interconnected, governed, autonomous systems working together. Organizations that invest early in Agent Mesh architectures, centralized governance, ontology-driven reasoning, secure identities, and AI operating platforms will be able to scale hundreds of intelligent agents safely and efficiently. The future belongs to businesses that treat AI not as a feature, but as enterprise infrastructure capable of supporting continuous automation, intelligent decision-making, and long-term digital transformation.

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    1 hr and 42 mins
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