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

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.

  1. قبل ١٣ ساعة

    Microsoft 365 Copilot: What Actually Makes People More Productive with Adrian Espes [MVP]

    Does Microsoft 365 Copilot really make people more productive?In this episode of the M365 FM podcast, Mirko Peters speaks with Microsoft MVP Adrian Espes about what Copilot actually delivers in everyday work—not in a polished demo, but during a normal working day filled with meetings, emails, documents, Teams messages, deadlines, and constant interruptions.Adrian brings a practical perspective shaped by his experience in training, business analytics, modern workplace consulting, and Microsoft 365 adoption. Together, Mirko and Adrian look beyond the marketing and explore where Copilot is genuinely useful, where expectations are still unrealistic, and what organizations need to consider before rolling it out. MICROSOFT 365 COPILOT IN THE REAL WORLD Adrian explains why Microsoft 365 Copilot’s biggest advantage is its position inside the Microsoft ecosystem. Unlike standalone AI tools, Copilot can work directly with the applications people already use every day, including Outlook, Teams, Word, PowerPoint, Excel, and Edge.The conversation explores how Copilot can help users summarize meetings, catch up on conversations, identify follow-up tasks, work with documents, and create useful outputs without constantly moving information between different tools. PROMPTING WITHOUT BECOMING A PROMPT ENGINEER Do employees really need to become prompt engineers?Adrian shares a realistic approach to prompting. Users do not need to learn complicated formulas or memorize a perfect prompt structure. Instead, they should practice explaining their goal clearly, provide relevant context, describe the desired outcome, and refine their requests over time.The discussion also covers why different departments and roles may need different prompting approaches. A financial analyst, a marketing professional, a manager, and a frontline worker will all use Copilot differently because their goals and daily tasks are different. PRODUCTIVITY, EFFICIENCY, AND THE HUMAN FACTOR One of the central themes of this episode is the difference between productivity and efficiency.Adrian explains why the word “productivity” can create anxiety among employees. When companies talk about productivity, many workers may fear that AI is being introduced to measure performance or replace jobs.Instead, Adrian suggests focusing on efficiency, better work quality, reduced friction, and making AI a natural part of everyday work. The real question is not simply whether someone completes more tasks, but whether Copilot helps them work with less effort, better information, and more time for meaningful activities. DATA QUALITY, GOVERNANCE, AND SECURITY Copilot can only be as useful as the information available to it. That makes data quality, permissions, governance, and information architecture essential parts of any Microsoft 365 Copilot project.Mirko and Adrian discuss the importance of reviewing the Microsoft 365 environment before implementation. This includes checking permissions, overshared information, tenant configuration, data protection, sensitivity labels, and the way users store and access content.Adrian also explains the importance of using enterprise accounts and understanding how enterprise data protection works when employees use Microsoft Copilot in a business environment. MICROSOFT 365 COPILOT AND AI MODELS The conversation also looks at the growing number of AI tools and models available today, including Microsoft Copilot, ChatGPT, Claude, Gemini, Perplexity, and different models available through GitHub and Microsoft platforms.Rather than asking which AI tool is universally the best, Adrian recommends choosing the right tool for the task. Some tools may be stronger for coding, reasoning, image creation, or creative work, while Microsoft 365 Copilot’s major strength is its integration with business data and workplace applications. A PRACTICAL COPILOT IMPLEMENTATION ROADMAP Buying Copilot licenses is only the beginning.Adrian outlines the considerations organizations should address when planning a Microsoft 365 Copilot rollout. Before investing in additional licenses, companies should first understand what is already available through their existing Microsoft 365 plans and evaluate whether users genuinely need the full Copilot experience.The implementation process should also include:Reviewing the Microsoft 365 tenant and existing configurationsChecking permissions and data governanceUnderstanding regulatory and regional requirementsEvaluating which users and roles will benefit mostDefining realistic use casesSupporting employees through training and experimentationMeasuring efficiency and adoption instead of relying only on license usage WILL COPILOT ELIMINATE MEETINGS? During the rapid-fire section, Mirko asks Adrian whether Copilot will eliminate most meetings.Adrian’s answer: for now, this is still mostly hype. Copilot can make meetings easier to follow, summarize discussions, and identify actions, but it does not automatically solve the organizational reasons why too many meetings exist.They also discuss whether AI agents will replace traditional business applications. Adrian believes agents will become increasingly important, but they will work alongside business applications rather than replace them entirely. Strong governance, security, visibility, and management will be essential as organizations create more agents. IS COPILOT USEFUL FOR FRONTLINE WORKERS? The value of Copilot for frontline workers depends heavily on their role and daily responsibilities.For employees who regularly work with email, Teams, documents, or operational information, Copilot may provide real benefits. However, not every frontline worker uses Microsoft 365 applications in the same way as an office-based employee.Adrian explains why organizations should avoid assuming that one Copilot strategy will work for every employee group. Adoption needs to be connected to real tasks, real users, and real business needs. KEY QUESTIONS DISCUSSED IN THIS EPISODE Does Microsoft 365 Copilot really improve productivity?What makes Microsoft 365 Copilot different from ChatGPT, Claude, Gemini, and other AI tools?Do employees need to become prompt engineers?How can users improve their prompts?Why do data quality and governance matter so much?How should organizations prepare for a Copilot rollout?What should companies evaluate during the first 30, 60, and 90 days?Can Copilot reduce meetings?Will AI agents replace traditional business applications?Is Copilot useful for frontline workers?How can organizations measure efficiency without creating fear among employees? ABOUT ADRIAN ESPES Adrian Espes is a Microsoft MVP focused on Microsoft 365 and Copilot. He works as a consultant and trainer, helping organizations understand, adopt, and use Microsoft technologies in practical business environments.His background includes sales, training, data analytics, business workflows, and modern workplace consulting. Adrian is passionate about helping people use AI more naturally and effectively in their daily work. FINAL THOUGHTS Microsoft 365 Copilot is not a magic productivity button. Its value depends on the quality of an organization’s data, the clarity of its use cases, the preparation of its environment, and the willingness of employees to experiment and learn.The most successful Copilot implementations will not focus only on buying licenses or showcasing impressive demos. They will focus on helping people work more efficiently, make better decisions, reduce repetitive effort, and use AI as a practical part of the modern workplace.Listen to this episode to discover what Microsoft 365 Copilot can really do beyond the hype. ABOUT THE M365 FM PODCAST The M365 FM podcast explores the people, ideas, and technologies shaping the future of work across Microsoft 365, Copilot, AI, security, governance, Power Platform, and the modern workplace.Hosted by Mirko Peters, every episode features conversations with Microsoft MVPs, product experts, consultants, architects, and practitioners from across the global Microsoft ecosystem.Subscribe to M365 FM for practical conversations about what works, what does not, and what organizations need to know next. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    Microsoft 365 Copilot: What Actually Makes People More Productive with Adrian Espes [MVP]

  2. قبل يوم واحد

    How Microsoft 365 & Copilot Are Redesigning the Way We Work with Tracy van der Schyff [MVP]

    Microsoft 365 has given organizations more tools than ever to communicate, collaborate, automate, and manage information. Now Microsoft 365 Copilot adds an entirely new layer of AI capability. But behind all the discussion about productivity, automation, agents, and AI, there is a much bigger question: are these technologies simply helping us work faster, or are they fundamentally changing the way we think, learn, communicate, collaborate, and work?In this episode of m365.fm, Mirko Peters sits down with Tracy van der Schyff to explore the human side of Microsoft 365 and Copilot. Tracy has spent years working at the intersection of technology, productivity, digital literacy, training, adoption, and organizational change. Her focus is not simply on teaching people which buttons to click. It is about helping people understand technology, use it with purpose, and become more capable because of it.The conversation goes far beyond Copilot features. Mirko and Tracy discuss digital fluency, Microsoft 365 adoption, information management, AI readiness, change management, responsible AI, the broken digital workplace, and a powerful idea that runs throughout the episode: we design technology, but the technology we create and use also shapes us. FROM DIGITAL LITERACY TO DIGITAL FLUENCY For many years, organizations talked about PC literacy and later digital literacy. But Tracy believes those terms no longer fully describe the skills people need in a modern workplace.Knowing how to operate a computer is not enough. Knowing where a button is inside Microsoft Teams or how to upload a document to SharePoint does not necessarily mean somebody understands how to work effectively in a digital environment.Digital fluency goes further. It means understanding the purpose of a technology, knowing when it should be used, understanding how your actions affect other people, and using technology responsibly and intentionally.This becomes even more important as AI enters everyday work. Tracy explains how her original model of eight pillars of digital literacy has evolved into eleven pillars of digital fluency, now incorporating responsible AI use and the additional skills people need when working alongside AI systems.The important distinction is that these are not simply Microsoft 365 skills. They are becoming life skills.AI is also creating unexpected opportunities to develop human skills. Communicating effectively with Copilot requires people to explain what they actually want. Better questions can produce better answers, and those answers can help people formulate better questions the next time. In that sense, working with AI can improve communication, creativity, critical thinking, and the ability to express intent clearly. THE MICROSOFT 365 TOOL OVERLOAD PROBLEM Teams, Outlook, SharePoint, OneDrive, Loop, Planner, Lists, Power Platform, Copilot and countless other applications give employees enormous capabilities. But providing access to tools does not automatically teach people how those tools should fit together.Organizations often deploy technology and expect employees to figure out the rest.That can result in departmental information being shared from personal OneDrive accounts, Teams being created simply for individual meetings, documents being stored in inappropriate locations, and employees constantly switching between tools without understanding where work actually belongs.When that happens, Tracy argues that blaming users is the wrong response.If an employee was never taught the intent behind Teams, SharePoint, OneDrive, Outlook, or another application, they will naturally choose whatever tool helps them complete the immediate task. The underlying problem is often not the employee. It is the absence of a clear digital strategy. ME, WE, US: SIMPLIFYING THE DIGITAL WORKPLACE One framework Tracy uses to make the Microsoft 365 environment easier to understand is ME, WE, US.The ME space represents the individual. These are the tools and information primarily associated with your personal work.The WE space begins when people collaborate around a common goal. Microsoft Teams and collaborative SharePoint environments become particularly relevant here.The US space represents information intended for the broader organization, such as publishing environments and intranets.This sounds simple, and that is precisely the point.Employees should not need to understand every architectural detail behind Microsoft 365 before they can make a sensible decision about where their work belongs. Organizations need to translate complicated technology landscapes into models that ordinary employees can understand and apply. COPILOT DOES NOT FIX A BROKEN DIGITAL WORKPLACE One of the strongest messages from the conversation is that Microsoft 365 Copilot should not be treated as a solution for an already broken digital workplace.Copilot does not magically repair years of poor information architecture, excessive sharing, unmanaged Teams, confusing permissions, duplicated documents, abandoned SharePoint sites, or inconsistent working practices.Instead, Tracy describes AI as an amplifier.If an organization has a healthy digital environment, Copilot can amplify that healthy environment. If the underlying environment is unhealthy, AI can make those existing problems significantly more visible.In that sense, Copilot acts like a huge spotlight.Information that may previously have been difficult to discover can suddenly become much easier to surface. That can make organizations believe Copilot created a problem when, in reality, the underlying permissions, sharing practices, or information-management problems may have existed for years.The AI did not necessarily create the mess. It exposed it. ONTOLOGICAL DESIGN: THE THINGS WE CREATE CHANGE USA fascinating part of the conversation explores ontological design.The concept sounds complicated, but Tracy explains it in a very practical way: we create things, and the things we create eventually change us.That applies to software, applications, intranets, processes, social media, Microsoft Teams, Copilot, and almost every digital environment people interact with.When someone designs an application, they make decisions about how users will interact with it. Those decisions influence the behavior of the people using the application.The same principle applies at a much larger scale to the modern workplace.Employees can spend many hours every day inside Teams, Outlook, SharePoint, OneDrive, Microsoft 365, and increasingly Copilot. Those environments are therefore not neutral. They influence how people communicate, how quickly they expect responses, how they organize information, how they collaborate, and even how they think about work.The intention behind what we design matters because what people consume eventually influences them. WHEN ACTIVITY BECOMES CONFUSED WITH PRODUCTIVITY Microsoft Teams and other collaboration tools have dramatically reduced the friction required to communicate. But reducing friction can also create enormous amounts of noise.Tracy raises an interesting problem: people can begin to use visible activity as proof that they are productive.More messages. More notifications. More updates. More documents. More meetings. More channels.But every communication creates work for somebody else.A message that takes one person a few minutes to write might interrupt dozens or hundreds of other employees. Individually, that interruption may seem insignificant. Across an organization, the cumulative cost can become substantial.The question therefore should not simply be whether Microsoft 365 allows us to communicate faster. Organizations also need to ask whether all of that communication is necessary in the first place. AI CAN BE MORE THAN A PRODUCTIVITY TOOL Many discussions about Copilot focus on straightforward productivity scenarios.Summarize my emails. Summarize this meeting. Create a presentation. Rewrite this document. Analyze this information. Help me find something.Those capabilities are useful, but Tracy argues that AI can become something much more interesting.People can use AI to learn.Someone who struggles with delegation can ask Copilot how to become better at delegating. Someone intimidated by AI can ask AI how to begin learning about AI. Someone concerned about cybersecurity can ask how to protect themselves and their family. Someone who lacks confidence with a technology can use AI as a private environment for experimentation and learning.This moves the conversation from simply asking, “How much time can Copilot save?” toward asking, “How can Copilot increase human capability?”That distinction is important.The most valuable use of AI may not always be automating another task. Sometimes it may be helping someone become better at performing that task themselves. AI DOES NOT REMOVE HUMAN RESPONSIBILITY Copilot might summarize hundreds of emails, but responsibility does not disappear if an important message is missed.AI can generate a document quickly, but somebody still needs to understand why that document exists.AI can retrieve organizational information, but companies still need to understand permissions, ownership, governance, security, and information management.AI can produce an answer, but people still need the judgment required to evaluate that answer.For Tracy, this is another reason digital fluency becomes more important as AI becomes more capable.Organizations should not respond to increasingly powerful technology by investing less in human skills. They should invest more. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    How Microsoft 365 & Copilot Are Redesigning the Way We Work with Tracy van der Schyff [MVP]

  3. قبل يومين

    Stop Reinventing SPFx- Building Better SharePoint Solutions with PnP React Controls with Siddharth Vaghasia [MVP]

    Modern SharePoint development does not mean building every component from scratch. In this episode of the M365 FM Podcast, Mirko Peters talks with Microsoft MVP Siddharth Vaghasia about building production-ready SharePoint Framework (SPFx) solutions by combining the right Microsoft 365 technologies with reusable community components.Siddharth brings nearly 18 years of experience across the Microsoft technology stack, from .NET and the early days of SharePoint Server to SharePoint Online, Microsoft 365, Power Platform, Azure, and modern SPFx development. WHEN SHOULD YOU ACTUALLY USE SPFx? Not every SharePoint requirement needs custom development. Siddharth explains a simple principle: first determine whether Microsoft already provides the functionality. If the requirement can reasonably be solved with standard SharePoint capabilities, avoid unnecessary customization.SPFx becomes valuable when organizations need experiences, integrations, or interfaces that cannot be delivered effectively with out-of-the-box functionality. SPFx VS POWER PLATFORM Should you build the solution with SPFx or Power Apps?The discussion explores where each approach fits. Power Apps can be effective for relatively straightforward forms, conditional fields, business rules, and scenarios where citizen development and low-code maintainability matter.SPFx becomes particularly powerful when developers need greater control over the user interface, complex data handling, reusable components, APIs, or sophisticated application experiences directly inside SharePoint. Siddharth also argues that generative AI coding tools are changing the traditional assumption that pro-code development necessarily takes longer than low-code development. THE MODERN SPFx TECHNOLOGY STACK A modern SPFx project brings together several technologies rather than relying on one framework.Siddharth breaks down the roles of TypeScript, React, Fluent UI, PnPjs, and PnP React Controls. TypeScript provides stronger typing and compile-time checks, while Fluent UI helps custom solutions retain the familiar Microsoft user experience.PnPjs simplifies interaction with SharePoint, Microsoft Graph, and other Microsoft 365 services by replacing repetitive REST request code with reusable abstractions. STOP REBUILDING CONTROLS THAT ALREADY EXIST One of the central lessons of the episode is simple: professional development does not mean writing everything yourself.PnP React Controls provide SharePoint-aware and Microsoft 365-aware components for common development requirements. Instead of repeatedly creating the UI, API calls, data binding, and associated logic for components such as file pickers, developers can use established community controls.Siddharth's preferred approach is to check existing capabilities first: use Microsoft functionality when available, then Fluent UI or PnP React Controls where they satisfy the requirement, and create a custom component only when the required functionality does not already exist. THE FIVE PnP REACT CONTROLS DEVELOPERS SHOULD KNOW If Siddharth had to choose only five controls, his selection would be People Picker, Taxonomy Picker, List View, File Picker, and Live Persona.These components cover several recurring requirements in enterprise SharePoint applications, including selecting users, working with managed metadata, presenting SharePoint data, selecting or uploading files, and displaying Microsoft 365 user information. BUILDING REAL APPLICATIONS INSIDE SHAREPOINT The conversation moves from individual controls to application architecture with the example of a sophisticated project management solution.SharePoint lists can provide the underlying data layer for projects, customers, resources, and tasks, while SPFx can deliver a unified application experience containing dashboards, project views, charts, CRUD operations, role-specific interfaces, task management, and navigation.The result can feel much more like a dedicated business application while remaining embedded inside the SharePoint environment users already know. SHAREPOINT DOESN'T HAVE TO BE YOUR DATABASE SPFx applications are not restricted to SharePoint data.Siddharth discusses retrieving information from Dataverse and integrating external systems. When data resides in systems such as Azure SQL, a backend API can provide the secure middle layer between the client-side SPFx application and the database.He also describes a real example where an SPFx web part surfaces Power Automate approvals directly inside SharePoint and allows users to approve or reject requests without moving to another application. MICROSOFT GRAPH AND SPFx Microsoft Graph expands SPFx far beyond SharePoint itself.Applications can interact with Microsoft 365 services including OneDrive, Planner, Outlook, meetings, and other resources exposed through Graph. Siddharth explains when SharePoint REST APIs remain appropriate and when Graph becomes the better or necessary option. SECURITY, PERMISSIONS AND LEAST PRIVILEGE Security is a major part of professional SPFx development.SPFx solutions calling Microsoft Graph typically operate using delegated permissions and therefore respect the identity and access rights of the currently signed-in user. Requested API permissions also require administrative approval.One of the most common mistakes Siddharth sees is requesting more permissions than the application actually requires. His recommendation is to start with the minimum permissions necessary rather than granting broad access by default.Developers also need to test solutions from the perspective of real users instead of assuming that permissions available during development will also exist in production. NEVER PUT SECRETS IN CLIENT-SIDE SPFx CODE Because SPFx executes client-side, sensitive secrets should never be embedded directly into the application code.For scenarios requiring secrets or credentials, Siddharth recommends introducing a backend API that can securely access services such as Azure Key Vault while the SPFx frontend communicates only with that API. SECURITY REVIEW DOESN'T END WITH YOUR OWN CODE SPFx relies heavily on the modern JavaScript and npm ecosystem. Organizations therefore need to consider the security and maintenance status of third-party packages as well as their own application logic.Siddharth recommends reviewing dependencies, paying attention to package warnings and vulnerabilities, and including security assessment as part of the deployment process rather than assuming every dependency is safe simply because it is available through npm. WHY IS YOUR SPFx SOLUTION SO SLOW? When an SPFx application performs badly, Siddharth starts with the browser's network tools.Developers should examine how many API calls occur during page load, identify unnecessary requests, look for API calls accidentally executed inside loops, and inspect React components for excessive rendering or state changes.A seemingly simple application can generate dozens of requests when data retrieval is implemented inefficiently. BATCH YOUR REQUESTS Once unnecessary API traffic has been identified, batching can significantly improve how requests are handled.Instead of sending multiple individual operations from the client, developers can combine appropriate SharePoint operations into batch requests and reduce client-side request overhead. FROM DEVELOPMENT TO THE SHAREPOINT APP CATALOG Siddharth also walks through the SPFx deployment process, from packaging the solution into an .sppkg package to deploying it through the SharePoint App Catalog and approving required API permissions.Importantly, deploying a package does not automatically mean installing it everywhere. Organizations can control which SharePoint sites receive the application, and site collection App Catalogs can provide an even narrower deployment scope. SPFx MEETS COPILOT AND AI AGENTS SPFx is also moving into the agent era.Siddharth discusses SharePoint Copilot apps and how SPFx can provide interactive user-interface components inside Microsoft 365 Copilot experiences. Instead of returning only text or Markdown, an agent can potentially surface richer interfaces that users can interact with directly.He describes the concept as similar to taking the idea behind Adaptive Cards much further by enabling richer, more customizable application experiences. THE BIG TAKEAWAY The strongest SharePoint developers are not necessarily the developers who write the most code.They know when to use SharePoint out of the box, when Power Platform is sufficient, when SPFx provides the necessary flexibility, when Microsoft Graph is required, and when existing Fluent UI and PnP components can eliminate unnecessary development.The goal is not to reinvent another component. It is to combine the Microsoft 365 ecosystem into solutions that are secure, maintainable, performant, accessible, and capable of solving an actual business problem. ABOUT SIDDHARTH VAGHASIA Siddharth Vaghasia is a Microsoft MVP, consultant, founder, speaker, blogger, and community contributor specializing in Microsoft 365, SharePoint, Power Platform, Azure, and related technologies. He also discusses his company Binary Roots and its work with customers across multiple international markets. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    Stop Reinventing SPFx- Building Better SharePoint Solutions with PnP React Controls with Siddharth Vaghasia [MVP]

  4. قبل ٣ أيام

    SharePoint Isn't Boring Anymore: How Copilot Is Reinventing the Modern Workplace with Marcin Siewnicki [MVP]

    For years, SharePoint has carried a reputation for complicated document libraries, outdated intranets, confusing navigation, too many sites, and information that employees simply cannot find. But Microsoft 365 is changing, and Copilot is making SharePoint more important than it has been in a long time.In this episode of the M365 FM Podcast, Mirko Peters talks with Microsoft MVP Marcin Siewnicki about how SharePoint is evolving from a traditional document and intranet platform into a central information and knowledge layer for the modern workplace. Marcin has worked with SharePoint since the SharePoint 2003 era, giving him more than two decades of perspective on how the platform has changed. WHY SHAREPOINT GOT A BAD REPUTATION Much of SharePoint’s reputation was created by the way organizations implemented it. Intranets were often designed by IT, heavily customized, difficult to use, and disconnected from what employees actually needed.Instead of continuously gathering feedback and improving the experience, many companies delivered an intranet and expected employees to adapt to it. The result was complex navigation, outdated content, overloaded pages, and systems people avoided whenever possible. INFORMATION ARCHITECTURE BEFORE TECHNOLOGY One of the biggest problems is not SharePoint itself but how information is organized inside it. Without a clear information architecture, SharePoint can quickly become a huge shared folder filled with duplicated files, outdated information, unclear ownership, and multiple versions of the same document.Marcin explains why organizations should start with a simple structure, understand their data, remove unnecessary content, and introduce basic metadata. Information architecture does not have to be complicated to make SharePoint significantly easier to use. BUILDING A MODERN SHAREPOINT WORKPLACE A modern SharePoint homepage should not become an endless collection of web parts, corporate announcements, applications, and links. It should be simple, personalized, visually clear, and focused on what employees actually need.Communication sites can provide departments and organizations with modern, mobile-friendly publishing experiences without requiring the enormous custom intranet projects that were common in the past. The focus should be on useful information, important applications, relevant documents, straightforward navigation, and strong search capabilities. SOLVING THE SHAREPOINT NAVIGATION PROBLEM Navigation remains one of SharePoint’s biggest challenges. Organizations frequently attempt to expose every department, application, resource, and internal page through a single navigation structure.Marcin explains why simpler navigation usually works better. Global navigation should focus on the most important destinations, while detailed navigation can be provided closer to individual departments, sites, and business areas. Otherwise, navigation itself becomes another information problem. SHAREPOINT AND TEAMS SPRAWL Microsoft Teams and SharePoint are deeply connected. Every new Team and many Teams channels can introduce additional SharePoint resources, which means uncontrolled Teams creation can quickly become uncontrolled SharePoint growth.Organizations therefore need simple creation processes, templates, basic metadata, lifecycle management, and user education. Employees should understand when they need a Team, when a SharePoint site is sufficient, and what happens behind the scenes when these collaboration environments are created.One useful way of looking at the relationship is to think of Microsoft Teams as the collaboration interface while SharePoint provides much of the document and information layer underneath it. GOVERNANCE WITHOUT KILLING INNOVATION Governance does not need to mean preventing employees from using new technology. The goal is to provide enough freedom for people to work effectively while maintaining control over information, permissions, external sharing, security, and lifecycle management.Marcin discusses periodically reviewing inactive SharePoint sites and Teams, identifying environments that are no longer needed, checking ownership, reviewing permissions, and archiving or removing obsolete workspaces.Governance also cannot remain exclusively an IT exercise. Business stakeholders and users need to be involved because overly complicated policies often lead employees to find their own workarounds. PERMISSIONS, SHARING AND SECURITY Permissions become increasingly difficult to understand as SharePoint environments grow. Users add colleagues, external partners, vendors, and sharing links over time, but access is rarely reviewed with the same frequency.Regular permission reviews should therefore become part of the governance model. Site and Team owners need responsibility for checking who still requires access and whether external sharing remains necessary.Microsoft Purview sensitivity labels can add another security layer by helping organizations classify and protect information based on its sensitivity. AUTOMATING SHAREPOINT GOVERNANCE Governance does not have to be completely manual. PowerShell, Microsoft Graph, Power Automate, Azure Logic Apps, and specialized third-party platforms can automate many administrative and governance processes.Marcin sees PowerShell and Microsoft Graph as fundamental tools for administrators, while Power Automate can provide practical automation for provisioning, approvals, notifications, lifecycle processes, and many other SharePoint scenarios. MODERN DOCUMENT MANAGEMENT SharePoint is still heavily associated with documents, and documents remain an important part of the platform. The challenge is managing them properly.Metadata, naming conventions, permissions, versioning, storage management, and sensitivity labels all contribute to a healthier information environment. Versioning deserves particular attention because large documents with many retained versions can consume significant amounts of SharePoint storage. METADATA VS. FOLDERS The old SharePoint debate between folders and metadata has not completely disappeared. Marcin argues that metadata remains extremely valuable, but organizations need to keep their metadata models simple.If users need to spend too much time deciding how to classify every document, adoption will suffer. Metadata should support the way employees work rather than creating another administrative task. COPILOT CAN AUTOMATE METADATA Copilot changes this equation because AI can reduce the manual work associated with metadata. SharePoint can analyze documents, extract relevant information, and populate columns based on the content.Organizations still need to decide which metadata is useful, but employees no longer necessarily have to enter everything manually. This can make structured information much more practical at scale. COPILOT CHANGES SHAREPOINT Copilot significantly lowers the amount of SharePoint knowledge employees need before they can start accomplishing useful work.Users can increasingly create content, work with documents, extract information, generate pages, and interact with organizational knowledge using natural language instead of understanding every technical SharePoint concept.Many of the repetitive tasks traditionally associated with maintaining SharePoint environments can therefore become easier. FROM FINDING DOCUMENTS TO GETTING ANSWERS This may be the biggest change of all.Traditional SharePoint experiences required employees to find the right site, navigate to the right library, locate the correct document, open it, and search for the information they needed.Copilot changes that interaction. Instead of only finding documents, employees can increasingly ask questions and receive answers based on information stored across their Microsoft 365 environment.SharePoint therefore starts moving from document storage toward becoming an enterprise knowledge layer. COPILOT CAN UNDERSTAND MORE THAN OFFICE DOCUMENTS Organizational knowledge is not limited to Word documents, Excel files, and PowerPoint presentations.Copilot can work with different types of information, including text, HTML, Markdown, SharePoint lists, and content extracted from video transcripts.That means training videos, recorded meetings, presentations, and other media stored within the Microsoft 365 environment can become part of the knowledge available through AI. WHAT HAPPENED TO SHAREPOINT AGENTS? SharePoint Agents provide dedicated AI experiences grounded in selected SharePoint sites, document libraries, or information sources.Marcin discusses where these agents fit into the current Copilot landscape and why the concept has become less prominent as Copilot itself gains broader capabilities for interacting directly with SharePoint information. IS SHAREPOINT REALLY COPILOT’S KNOWLEDGE LAYER? There is certainly marketing around the idea, but there is also a strong technical reality behind it.Organizations already store enormous amounts of business information in SharePoint and Microsoft Teams. Copilot can use this information, which means the quality of the underlying environment directly affects the quality of the AI experience.Poor permissions, outdated documents, duplicated information, weak metadata, and uncontrolled SharePoint sprawl do not disappear because Copilot has been introduced. They potentially become even more important Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    SharePoint Isn't Boring Anymore: How Copilot Is Reinventing the Modern Workplace with Marcin Siewnicki [MVP]

  5. قبل ٥ أيام

    Microsoft Fabric End-to-End: From Raw Data to Business Decisions with Amit Chandak [MVP]

    Microsoft Fabric brings data engineering, analytics, business intelligence, governance and increasingly AI together in one platform. But what does an end-to-end Fabric architecture actually look like when you move beyond individual features and start connecting everything?In this episode of the M365 FM Podcast, Mirko Peters is joined by Amit Chandak [Microsoft Data Platform MVP] for a practical journey through Microsoft Fabric — starting with raw organizational data and ending with trusted information that business users can use to make decisions. WHY MICROSOFT FABRIC? Before Fabric, organizations could already build sophisticated analytics architectures using Azure, Power BI and other platforms. The problem wasn't a lack of technology. In many cases, it was the opposite: organizations had too many choices, separate storage technologies, different compute models and multiple copies of essentially the same data.Amit explains how Microsoft Fabric attempts to simplify this architecture by bringing workloads together around shared foundations such as OneLake, common Fabric capacity and the Delta format. Lakehouses, warehouses, Power BI and other Fabric experiences can therefore operate as parts of a broader platform instead of completely isolated services. ONELAKE AS THE FOUNDATION OneLake is one of the central concepts behind Fabric. Amit compares it conceptually to OneDrive: instead of every analytics workload creating completely independent storage environments, OneLake provides a virtualized storage foundation across the Fabric tenant.Organizations can still separate data through workspaces, Lakehouses, Warehouses and domains, but those resources exist within a common Fabric storage architecture. This becomes particularly important when organizations want to reduce unnecessary duplication while maintaining security and organizational boundaries. CENTRALIZED DATA OR DATA MESH? Fabric doesn't automatically mean putting everything into one giant centralized analytics environment.For smaller organizations, a centralized architecture may still work well. As organizations become larger, Amit sees increasing value in domain-oriented architectures where areas such as sales, finance and purchasing can have their own workspaces and responsibilities.IT can remain responsible for availability, governance and the technical foundation while business domains increasingly take ownership of how their data is analyzed and consumed. SHORTCUTS INSTEAD OF COPYING DATA One of the recurring themes throughout the conversation is avoiding unnecessary copies of data.Fabric Shortcuts allow teams to reference data stored elsewhere rather than physically copying it into every environment that needs it. That can apply both inside Fabric and to supported external storage.Amit also explains an interesting architectural benefit of shortcuts: they can help separate workloads across capacities. This can become important when organizations want Power BI consumption workloads isolated from intensive data engineering workloads while still working with the same underlying information. LAKEHOUSE VS. WAREHOUSE One of the biggest Fabric architecture questions remains: Should you use a Lakehouse or a Warehouse?A Lakehouse can work with structured and unstructured data and is naturally aligned with Spark. A Fabric Warehouse focuses on structured data and provides the familiar T-SQL experience.Both ultimately use Delta for structured data inside Fabric, which means the decision increasingly comes down to the type of data, preferred technologies and workloads.Organizations with strong SQL teams don't necessarily need to abandon their existing skills. Teams working with very large datasets, advanced engineering scenarios, unstructured information or extensive data science workloads may find the Lakehouse and Spark approach more attractive. GETTING DATA INTO FABRIC Once the architecture is defined, organizations still need to bring data into Fabric.Amit walks through several approaches, including Shortcuts, Mirroring, Pipelines, Copy Activity, Copy Jobs, Dataflow Gen2 and notebooks.The right option depends heavily on the source and use case. Dataflow Gen2 remains particularly useful because of its broad connector support and familiar Power Query experience. For Power BI professionals entering Fabric, this can provide a natural starting point before moving toward more engineering-oriented approaches. WHEN PYSPARK BECOMES IMPORTANT Power Query and Dataflow Gen2 can work very well for small and medium-sized workloads, but scale changes the equation.For larger transformation workloads, Amit sees significant advantages in Spark-based processing. PySpark and Spark notebooks provide greater flexibility and are designed for distributed processing at scale.SQL and Power BI professionals don't necessarily have to make that transition immediately. Spark SQL can provide a familiar entry point for SQL developers, while many PySpark operations have conceptual similarities to transformations Power Query users already understand. DO YOU REALLY NEED BRONZE, SILVER AND GOLD? The Medallion Architecture has become almost synonymous with modern data engineering: Bronze for raw data, Silver for cleaned and transformed data, and Gold for business-ready information.But Amit argues that organizations shouldn't create layers simply because an architecture diagram says they should.If an organization already has excellent master data management and high-quality source data, every intermediate layer may not provide enough value to justify another copy and another transformation step. Where source data quality is inconsistent, however, the traditional Bronze-Silver-Gold structure remains highly valuable. WHERE SHOULD BUSINESS LOGIC LIVE? Another important architecture decision is determining where calculations and business rules belong.Amit prefers keeping measures and KPIs in the semantic model where possible because they remain dynamic and easier to change. Heavy row-level calculations across millions of records, however, are generally better handled earlier in the Gold layer.The result is not an either-or decision. A mature Fabric architecture distributes business logic deliberately between the transformation layer and semantic model depending on the type and cost of the calculation. SEMANTIC MODELS ARE BECOMING MORE IMPORTANT The semantic model was traditionally viewed primarily as the foundation for Power BI reports. AI is changing that role.Relationships, measures, KPIs and business definitions encoded within a semantic model represent organizational knowledge. That knowledge can increasingly be consumed by experiences beyond traditional dashboards.Amit discusses how Data Agents, ontology-driven solutions and Fabric Apps can build on semantic models. Instead of being merely a Power BI component, the semantic model can become a reusable business layer between organizational data and multiple human or AI-driven experiences. DOES DAX STILL MATTER IN THE AI ERA? AI can already generate DAX, SQL, PySpark and other code remarkably quickly. Does that mean professionals no longer need to learn these languages?Amit argues that expertise still matters, particularly when generated solutions don't work correctly or need optimization. AI can dramatically reduce the amount of syntax professionals need to write manually, but understanding the underlying logic remains valuable for debugging and improving what AI creates.Over time, the skill may shift from remembering syntax toward understanding architecture, algorithms, business logic and how to describe requirements precisely. SECURITY FROM WORKSPACE TO DATA Putting more organizational data into a unified platform makes security increasingly important.The discussion covers security across multiple layers, beginning with Fabric workspace roles and continuing through item-level access, OneLake security and semantic-model security.For larger organizations, Amit recommends using security groups rather than managing individual users wherever possible. Microsoft Entra provides the identity and group foundation, while Fabric applies those identities and groups to workspaces, items and data access. FROM DATA ENGINEERING TO BUSINESS DECISIONS Ultimately, most business users don't care whether their information came through PySpark, a Lakehouse, Delta tables or Dataflow Gen2. They care about getting reliable answers.This is where Amit sees Data Agents, ontology and AI-driven analytics becoming increasingly important.Instead of every user receiving the same predefined dashboard, future analytics experiences could become far more dynamic. Users may interact conversationally with organizational data and eventually have personalized reports or applications generated around their specific questions and responsibilities. RAPID FIRE The episode closes with a rapid-fire round.SQL or PySpark? PySpark.Dataflow Gen2 or Notebook? Notebook.DAX or SQL? DAX.Most underrated Fabric feature? Fabric Apps.Biggest Power BI modeling mistake? Many-to-many relationships.And perhaps the most provocative answer of the episode:Are Fabric Apps the new Power BI?Amit's answer: Yes. THE BIG PICTURE Microsoft Fabric isn't simply another analytics product to add to the Microsoft stack.Its larger opportunity is connecting ingestion, engineering, storage, Lakehouse and Warehouse architectures, semantic models, security, Power BI and emerging AI experiences into one coherent analytics platform.The technical architecture matters, but the endpoint isn't OneLake, PySpark or even Power BI.The endpoint is trusted information that people — and increasingly AI agents — can turn into better business decisions. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    Microsoft Fabric End-to-End: From Raw Data to Business Decisions with Amit Chandak [MVP]

  6. قبل ٦ أيام

    Beyond Copilot: Building Enterprise AI Agents That Actually Work with Copilot Studio with Manpreet Singh [MVP-MCT]

    Enterprise AI is moving beyond chatbots that simply answer questions. The next generation of AI agents can understand business context, connect to enterprise systems, orchestrate workflows, and take action on behalf of users.But building an impressive AI agent demo is easy. Building an agent that works reliably across a global enterprise—with sensitive data, complex business processes, governance requirements, thousands of users, and measurable outcomes—is a very different challenge.In this episode of the M365 FM Podcast, Mirko Peters talks with Manpreet Singh [MVP/MCT] about what it actually takes to build production-ready enterprise AI agents with Microsoft Copilot Studio and the wider Microsoft AI ecosystem.Manpreet explains how organizations are evolving from individual departmental agents toward multi-agent architectures where specialized agents collaborate behind a single interface. The discussion explores when to use Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry—and how these technologies can work together rather than becoming isolated AI platforms. FROM ANSWERS TO ACTIONS The real transformation begins when an AI agent can do more than retrieve information.Using practical examples, Manpreet explains how agents can connect with systems such as Workday, Salesforce, SAP, ServiceNow, Jira, Confluence, and PeopleSoft. Instead of navigating several applications manually, employees can interact with an agent through Microsoft Teams or another conversational interface.An employee requesting leave, for example, could have an agent check available leave, consult HR policies, initiate the request in the underlying HR system, ask the manager for approval, and return the final result—all without the employee opening the individual applications. KNOWLEDGE, TOOLS AND TRIGGERS A useful enterprise agent requires more than a good prompt.Manpreet breaks the architecture down into essential elements: knowledge sources that provide organizational context, tools and connectors that allow the agent to interact with enterprise systems, and triggers that determine when processes should begin.SharePoint can become an important knowledge layer, while Power Platform connectors and APIs enable agents to perform actions across business applications. WHY DATA QUALITY MATTERS Connecting an agent to twenty years of SharePoint content is not necessarily a good strategy.Manpreet strongly recommends cleaning and curating organizational knowledge before exposing it to AI. Thousands of outdated PDFs, duplicate documents, missing metadata, and obsolete policies can undermine the quality of agent responses.A smaller, carefully maintained knowledge base with current documents, useful metadata, tags, descriptions, and version management can produce significantly better results than simply indexing everything an organization owns. HUMAN-IN-THE-LOOP AI Autonomous does not have to mean uncontrolled.For low-risk transactions, organizations may allow an agent to complete an action automatically. Higher-value or sensitive decisions can introduce human approval.Manpreet discusses examples including financial claims, invoice processing, access requests, and infrastructure changes where humans remain part of the decision-making process while AI handles much of the repetitive work surrounding the decision. GOVERNANCE BEFORE SCALE As agents gain access to multiple enterprise applications, governance becomes critical.The conversation explores Microsoft Purview, Data Loss Prevention policies, security controls, sensitivity labels, Microsoft Defender, identity, environment strategies, and the importance of establishing an AI Center of Excellence before allowing agent development to expand throughout an organization.Governance should protect enterprise information without creating policies so restrictive that agent performance and usability suffer. CONTROLLING AGENT SPRAWL Organizations can quickly move from a handful of experimental agents to hundreds or thousands.Manpreet discusses agent lifecycle management, parent-child agent relationships, centralized inventories, ownership, connected data sources, permissions, consumption, and emerging management capabilities around Agent 365.The goal is to give administrators visibility into which agents exist, who owns them, what they can access, and how they are being used. THE AI COMMAND CENTER One of the most interesting concepts discussed in the episode is a unified AI Command Center.Instead of agent creation happening without oversight, organizations can establish a central process for requesting agents, connectors, APIs, MCP integrations, environments, and permissions.The command center can combine approval workflows, auditing, monitoring, governance, usage information, and cost controls—creating a central operational layer for enterprise AI. OBSERVABILITY AND TROUBLESHOOTING Traditional applications have logs. Enterprise AI needs observability.When an employee reports that an agent produced an unexpected result, administrators need to understand which knowledge sources were accessed, which tools were called, what actions occurred, and where the process failed.Copilot Studio's tracing and evaluation capabilities can help teams investigate these execution paths and understand how an agent arrived at an outcome. TESTING NON-DETERMINISTIC AI Testing AI agents requires a different mindset from testing traditional applications.Manpreet discusses evaluation features, generated test cases, structured datasets, indexing, user feedback, and repeated validation. Organizations should continuously test their agents against realistic questions and expected outcomes rather than deploying an agent once and assuming it will behave correctly forever. MULTI-AGENT ARCHITECTURES Instead of forcing employees to find the correct agent for every task, organizations can create an orchestration layer.A primary agent can understand the user's intent and delegate work to specialized agents for HR, travel, marketing, sales, IT, or other functions.The user interacts with one interface while multiple specialized agents operate behind it. ADOPTION IS WHERE AI ROI HAPPENS The final challenge is not technical.Organizations can build thousands of sophisticated agents and still fail to generate meaningful business value if employees do not understand when, why, and how to use them.Manpreet argues that adoption, persona-based training, practical use cases, and helping employees integrate agents into their daily work are essential to realizing ROI from Microsoft 365 Copilot and enterprise AI investments. IN THIS EPISODE Microsoft Copilot Studio and enterprise AI agentsMicrosoft 365 Copilot vs. Copilot Studio vs. Azure AI FoundryAutonomous agents and action-oriented AIEnterprise knowledge groundingSharePoint as an AI knowledge sourceData quality, metadata, and indexingPower Platform connectors and enterprise integrationsHuman-in-the-loop architecturesMulti-agent systems and orchestrationMicrosoft Purview and DLPAI security and governanceAgent lifecycle managementAgent inventories and Agent 365AI Centers of ExcellenceUnified AI Command CentersAI observability and tracingAgent testing and evaluationHallucination reductionAI consumption and cost managementEnterprise AI adoption and ROIKEY TAKEAWAY The next phase of enterprise AI is not simply about adding better chatbots. It is about moving from answers to outcomes.AI agents can connect organizational knowledge, applications, workflows, and business processes—but the fundamentals of enterprise technology remain essential: identity, security, governance, data quality, architecture, testing, observability, cost control, and adoption.And ultimately, the technology only creates value when people actually use it. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    Beyond Copilot: Building Enterprise AI Agents That Actually Work with Copilot Studio with Manpreet Singh [MVP-MCT]

  7. ٢٣ أغسطس

    From Copilot Rollout to AI Workplace: Adoption, Agents & Real Business Value with Christoffer Besler Hansen [MVP]

    Microsoft 365 Copilot has moved beyond the question of “What can generative AI do?” The harder challenge is now turning AI into something thousands of employees actually use, trust, and derive measurable business value from. In this episode of M365 FM, Mirko Peters talks with Microsoft MVP Christoffer Besler Hansen, Head of AI Workplace at Atea Group, about what it takes to move from a Copilot rollout to a genuine AI-powered workplace. Drawing on experience supporting AI adoption across more than 8,000 employees, Christoffer shares lessons on Microsoft 365 Copilot adoption, training, agents, Copilot Studio, Microsoft Foundry, governance, security, extensibility, FinOps, and measuring business value. WHAT IS AN AI WORKPLACE? An AI workplace is much broader than simply giving employees Microsoft 365 Copilot licenses. At Atea, the AI Workplace team is responsible for how more than 8,000 users incorporate AI into their daily work. Microsoft Copilot is a major component, but the strategy also includes Copilot Studio, agentic AI, Foundry, experimentation with other technologies, and—critically—continuous user adoption. The objective is not to deploy one AI product. It is to change how people work with information, applications, and business processes. TECHNOLOGY MOVES FAST. PEOPLE NEED TIME. New AI models and capabilities can appear every week. Human working habits don't change at the same speed. Christoffer explains why organizations need to spend substantial effort helping employees feel comfortable changing established workflows. At Atea, this includes training throughout the year, sometimes every other week, with sessions designed for different audiences such as managers, consultants, salespeople, beginners, and advanced users. AI adoption therefore isn't a launch event. It is an ongoing organizational capability. BUYING 5,000 COPILOT LICENSES ISN'T A STRATEGY What should happen after an organization purchases thousands of Microsoft 365 Copilot licenses? According to Christoffer, the organization first needs to determine why it purchased them. What is the objective? What should employees accomplish differently? How will the organization support adoption? How will success be measured? Simply assigning licenses and expecting employees to teach themselves isn't enough. Employees already have jobs to perform and cannot realistically follow every weekly change across rapidly evolving AI products. WHY EARLY COPILOT ADOPTION OFTEN DROPS AI naturally generates curiosity. When users initially received Copilot without structured adoption support, Christoffer observed strong engagement for approximately the first four weeks. Employees experimented with the technology. But when they struggled to turn those experiments into new working habits, usage declined. After structured training was introduced, users were more likely to continue using Copilot over time—and began asking for additional training as the products evolved. Initial excitement gets people through the door. Continuous education helps keep them there. HOW DO YOU MEASURE COPILOT ROI? One of the hardest enterprise AI questions is determining whether Copilot is actually creating value. Usage alone isn't enough. An employee opening Copilot 50 times doesn't necessarily mean the organization has become more productive. Christoffer argues that organizations need to identify what matters to their particular business and then measure whether AI improves those outcomes. That could include completing work faster, handling more customer cases, improving quality, or increasing business capacity. MEASURE OUTPUT, NOT JUST AI USAGE One example discussed in the episode involves an employee who previously handled two cases simultaneously but could use AI to work across six while still receiving better customer feedback. That represents something more meaningful than a Copilot usage statistic. The employee is producing more output while maintaining or improving quality. The right KPI therefore depends on what the organization actually produces. AI metrics should ultimately connect with business metrics. COPILOT AS A THINKING PARTNER Meetings were one of the earliest areas where Microsoft 365 Copilot delivered obvious value. Transcription, summaries, and meeting intelligence can reduce administrative effort. But Christoffer highlights another important pattern: using AI as a thinking partner. Instead of asking AI to do all the thinking, start with your own ideas. Speak or dictate those thoughts. Let Copilot structure them. Review the result. Give feedback. Iterate until you have something useful. This approach can save time while simultaneously improving the quality of emails, presentations, documents, and other knowledge work. RESEARCH AGENT CHANGES KNOWLEDGE WORK Christoffer highlights Microsoft's Research Agent as one of the particularly valuable additions to Copilot. For large projects involving significant amounts of information, an agent capable of working through numerous sources can dramatically reduce research effort. It can also help users find information they may previously have struggled to discover manually. Importantly, users can review the underlying sources and verify whether the resulting information is correct. YOUR AI IS ONLY AS GOOD AS YOUR INFORMATION Enterprise AI quickly exposes existing information-management problems. Organizations need to think about how information is structured across SharePoint, OneDrive, CRM systems, and other repositories. Microsoft Purview can play an important role in identifying and protecting confidential information. Retention policies also matter because outdated documents can lead AI toward outdated answers. Simply giving an agent access to more information doesn't automatically make it better. Sometimes the correct approach is to clean the data before connecting the agent. WHEN SHOULD YOU BUILD AN AGENT? ㅤ Christoffer recommends encouraging employees to start thinking about potential agent use cases early. Initially, organizations may create many simple agents that primarily retrieve information. Some will provide little long-term value. But experimentation changes how employees think about automation. The next maturity step is building agents that don't merely answer questions but perform actions—sending messages, updating CRM systems, triggering processes, or interacting with other applications. Eventually, organizations can move toward more autonomous agents working alongside employees. AGENT BUILDER VS COPILOT STUDIO Not every employee needs to begin with Copilot Studio. Christoffer sees many non-technical employees using Agent Builder directly inside Copilot to create simpler agents. More technical users move toward Copilot Studio when they require additional capabilities. This can create a useful progression: Idea → Simple Agent → Validation → Copilot Studio → Advanced Enterprise Agent An employee can prove the concept without becoming a professional developer, then involve technical specialists when the solution needs to become more sophisticated. FROM ANSWERS TO ACTIONS An HR agent answering “How many vacation days do I have?” is useful. An agent that can actually book next Friday as vacation represents a fundamentally different capability. This transition from information retrieval toward actions changes the architecture and security requirements surrounding AI. Christoffer expects users to interact less directly with traditional application interfaces as agents increasingly perform tasks on their behalf. Instead of navigating several administrative screens, users may simply describe the desired outcome to an agent. AGENT SECURITY BECOMES CRITICAL Once agents can take actions, organizations need strong guardrails. What can the agent do automatically? What requires explicit approval? What can it delete? Which systems can it access? What permissions does it receive? Christoffer emphasizes least privilege and approval controls, particularly when agents interact with administrative environments. Giving an autonomous agent Global Administrator privileges and allowing it to operate without restrictions would create obvious risks. The more capable agents become, the more important their permission architecture becomes. ENTERPRISE AGENTS NEED AN INTAKE PROCESS A personal agent used by one employee is different from an agent deployed to thousands of users. Enterprise-wide agents need quality control. Organizations should review instructions, permissions, connectors, integrations, and data access before allowing large numbers of employees to use them. Christoffer suggests establishing an intake process where employee ideas can be evaluated. Some agents may be returned to their creators for improvement. Strategically important ideas can instead be developed by a dedicated internal agent team. COPILOT EXTENSIBILITY AND AGENT 365 The conversation also explores Copilot extensibility and the Agent 365 SDK. Christoffer describes experimenting with personal agents that have their own identities in Microsoft Entra. Such an agent could appear within an organizational structure, have its own email and Teams presence, and receive carefully controlled permissions. His example involves building an agent that can act as a personal assistant and potentially answer appropriate questions when he is away from work. The important architectural shift is that the agent begins looking less like a chatbot and more like another identity participating in the organization. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    From Copilot Rollout to AI Workplace: Adoption, Agents & Real Business Value with Christoffer Besler Hansen [MVP]

  8. ٢٢ أغسطس

    Azure Local and Landing Zones: How to Build Hybrid Cloud the Right Way with Christoffer Klarskov Jakobsen [MVP]

    What happens when your cloud strategy cannot live entirely in the public cloud? Organizations are modernizing infrastructure with Azure, platform services, Infrastructure as Code, automated deployment pipelines, and Azure Landing Zones. At the same time, some workloads still need to remain close to factories, offices, regulated environments, existing infrastructure, or latency-sensitive systems. In this episode of M365 FM, Mirko Peters talks with Microsoft MVP Christoffer Klarskov Jakobsen about how Azure Local can become part of a broader Azure architecture rather than another isolated on-premises platform. They explore Azure Local, Azure Landing Zones, Azure Arc, governance, Infrastructure as Code, Bicep, Azure DevOps, modernization, and the realities of building hybrid cloud environments. WHAT IS AZURE LOCAL? Azure Local combines familiar infrastructure technologies with Azure-based management, governance, and security capabilities. At its core, organizations can run workloads such as virtual machines locally while connecting the environment back to Azure. Christoffer explains that the major difference compared with a traditional Windows Server environment is the Azure experience surrounding the infrastructure. Organizations can keep workloads and data locally while using Azure capabilities to manage and govern the environment. IS AZURE LOCAL JUST AZURE IN YOUR DATA CENTER? Not exactly. Azure provides a significantly larger catalog of cloud services, but Azure Local can bring selected Azure experiences closer to local infrastructure. Christoffer discusses running virtual machines and Kubernetes on Azure Local as well as scenarios involving SQL Managed Instance and Azure Virtual Desktop. The result isn't a complete copy of Azure running inside your building. It's a hybrid platform combining local compute requirements with selected Azure services and management capabilities. WHEN DOES AZURE LOCAL MAKE SENSE? Several scenarios stand out. Organizations may have regulatory requirements requiring data to remain locally. Others need extremely low latency between applications, machines, factories, or other infrastructure. Some organizations simply have workloads that cannot yet move completely into the public cloud. Christoffer also sees increasing potential around local AI workloads, including scenarios where organizations need AI capabilities while maintaining local control over their data. AZURE LOCAL IS A LOCAL CLOUD One of the important architectural lessons from the conversation is that Azure Local shouldn't be treated as simply another pair of servers. The environment includes multiple infrastructure and Azure-connected layers. Organizations therefore need people who understand the underlying hardware and operating technologies as well as Azure management. Christoffer describes Azure Local as effectively operating a local cloud rather than simply installing another traditional virtualization cluster. WHY AZURE LANDING ZONES MATTER Moving workloads into Azure doesn't automatically create a well-designed cloud environment. Organizations need structure, security boundaries, governance, permissions, networking, logging, and clear separation between workloads. Azure Landing Zones provide an architectural approach for establishing those foundations. Instead of placing unrelated applications, development environments, production systems, networking components, and shared services inside the same subscription, organizations establish clearer boundaries around workloads and responsibilities. THINK DIFFERENTLY ABOUT AZURE SUBSCRIPTIONS A subscription shouldn't simply become a container for everything an organization deploys. Christoffer recommends thinking about subscriptions as boundaries for specific environments and workloads. A development environment can have its own subscription. Testing can have another. Production can have another. Shared connectivity, logging, identity, and other platform services can be separated appropriately. This makes environments easier to secure, govern, understand, and eventually decommission. MANAGEMENT GROUPS CREATE STRUCTURE Management groups provide another layer for organizing Azure environments. They allow organizations to establish a hierarchy above subscriptions and apply governance at broader scopes. Policies and permissions can then be assigned at the management-group level rather than repeatedly configuring every individual subscription. Christoffer also discusses the local management group, which makes Azure Local increasingly relevant within the same Landing Zone architecture. AZURE POLICY AS THE GUARDRAIL Azure Policy plays a major role in this architecture. Policies can audit environments against organizational or regulatory requirements. They can identify non-compliant resources. They can deploy required configuration when something doesn't already exist. They can also deny configurations that organizations don't want users to create. Examples discussed include controlling Azure regions and preventing insecure storage configurations. Instead of relying entirely on documentation telling employees what they should do, organizations can encode many requirements directly into the platform. DENTITY, RBAC AND ZERO TRUST Landing Zones also provide a foundation for stronger access control. Christoffer emphasizes the principle of least privilege. Users and automated deployment identities should receive only the permissions required to perform their responsibilities. Application owners shouldn't automatically have access to connectivity infrastructure. Support personnel shouldn't automatically be able to modify logging systems. The objective is to establish clear security boundaries instead of making everybody an owner simply because that configuration is easier. AZURE LOCAL MEETS AZURE LANDING ZONES This is where the hybrid architecture becomes particularly interesting. Azure Local previously had limitations around how organizations could structure subscriptions and resources. Christoffer explains that newer capabilities make it possible to use multiple subscriptions and resource groups, enabling Azure Local to align much more closely with Landing Zone design principles. The Azure Local cluster itself can live within one subscription while different workloads use additional subscriptions. That enables organizations to apply clearer boundaries between the control plane and workloads. TIER 0, TIER 1 AND TIER 2 The conversation goes deeper into separating workloads according to security requirements. For example, domain controllers can be treated as Tier 0 resources and placed into a dedicated subscription with particularly strict access controls. Member servers can occupy another tier. End-user workloads such as Azure Virtual Desktop can be separated again. This creates an architecture where local workloads don't simply exist inside one giant infrastructure bucket—they participate in a structured Azure governance model. AZURE ARC CONNECTS THE TWO WORLDS Azure Arc is one of the technologies making the traditional boundary between cloud and on-premises infrastructure increasingly less important. Arc can connect servers running outside Azure with Azure management capabilities. That can include Windows and supported Linux systems running locally, on virtualization platforms, or even with other infrastructure providers. Once connected, organizations can use Azure capabilities including Microsoft Defender for Cloud, Azure Policy, and Azure Update Manager across infrastructure that isn't physically running inside an Azure datacenter. ONE MANAGEMENT PLANE FOR HYBRID INFRASTRUCTURE Traditionally, organizations often accumulated separate products for monitoring, patching, security, configuration, and infrastructure management. Azure Arc changes that model. Instead of treating every location as an entirely separate environment, administrators can increasingly manage distributed infrastructure through Azure. The physical location of the workload still matters for latency, compliance, hardware, and availability—but it doesn't necessarily require an entirely separate management model. INFRASTRUCTURE AS CODE FOR AZURE LOCAL Infrastructure as Code isn't limited to Azure public cloud resources. Christoffer explains that Azure Local infrastructure and workloads can also be deployed using Infrastructure as Code. His principle is straightforward: If you're going to do something more than once, automate it. The initial investment may take additional time, but repeatable deployment becomes particularly valuable for environments requiring ongoing maintenance and consistent configuration. WHY BICEP? Christoffer primarily uses Bicep for Infrastructure as Code. Coming from a PowerShell background, he found the transition into Bicep relatively natural. Visual Studio Code and its supporting extensions also make the development experience easier by identifying syntax issues and helping developers understand available configuration. He doesn't argue that Bicep is universally better than Terraform—rather, Bicep fits naturally into the Microsoft-focused environments and workflows he works with. Become a supporter of this podcast: https://www.spreaker.com/podcast/m365-fm-modern-work-security-and-productivity-with-microsoft-365--6704921/support.

    Azure Local and Landing Zones: How to Build Hybrid Cloud the Right Way with Christoffer Klarskov Jakobsen [MVP]
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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.

المعلومات

  • صناع العمل
    Mirko Peters - Founder of m365.fm, m365.show and m365con.net
  • سنوات النشاط
    ٢٠٢٥ - ٢٠٢٦
  • الحلقات
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  • التقييم
    ملائم
  • حقوق النشر
    © Copyright Mirko Peters / m365.fm - Part of the m365.show Network - News, tips, and best practices for Microsoft 365 admins
  • موقع البرنامج على الويب
    M365.FM - Modern work, security, and productivity with Microsoft 365

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