Windows 11 lock screen bug
We are having an issue where some users cannot log back into windows 11 after going to a lock screen. Windows will tell you the password or username is incorrect even though the credentials are defiantly correct. The only solution I've found so far is to reboot the machine. What could be causing this? Our users are loosing unsaved work from having to reboot through out the day.Beyond Tokens: Rethinking AI Economics with Microsoft Foundry
Beyond Tokens: Rethinking AI Economics with Microsoft Foundry From the cost of intelligence to the value of outcomes Enterprise AI has an accounting problem. Executives expect agentic AI to return roughly 171% on investment, according to one widely cited survey. Yet McKinsey finds only about 39% of organizations can attribute any earnings impact to AI at all. Both numbers can be true at once — because the gap between them is not a technology gap. It is a measurement gap. For the first few years of generative AI, one number dominated the economics conversation: tokens. How many tokens did a model consume? What was the cost per million tokens? Could a smaller model perform the same task? Those questions mattered when enterprises were experimenting with AI. They are no longer enough as AI moves into production. An enterprise agent doesn't simply consume tokens. It reasons, retrieves context, invokes tools, calls APIs, verifies its work, retries unsuccessful actions and sometimes escalates exceptions to humans. The model call might cost pennies. The business outcome could cost considerably more. Which leads to an increasingly important question: What is the right economic unit for intelligence? From AI experimentation to economic accountability The first wave of enterprise AI was about possibility: Can AI do this? The next wave is about production, as AI becomes embedded in software engineering, customer service, finance, healthcare and supply chains. And production changes the question: Should AI do this and at what cost? Microsoft has moved decisively onto this ground. In August 2026, the Microsoft Foundry team launched its Economics of Agent Optimization series, arguing that "tokens have become the new unit of technology spend" and that AI should be run as a managed investment system. On the latest earnings call, Satya Nadella described Microsoft's objective as "advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results." The discipline is going mainstream too: 98% of FinOps teams now manage AI spend, up from 31% two years ago. Microsoft's series is largely about the numerator of that curve - making every request, agent and dollar more efficient. This article is about the denominator: what an outcome is, what it truly costs, and what it is worth. The evolution of Microsoft Foundry reflects the same shift. At Build 2026, Microsoft expanded the conversation beyond building agents toward tracing behavior, evaluating quality, monitoring production performance, optimizing agents and connecting their operation to ROI. Think of the progression as: Trace → Evaluate → Monitor → Optimize → ROI This is more than a technology roadmap. It represents a shift from observing AI as technology to managing AI as an economic asset. Tokens became the unit of spend. They were never the unit of value. Consider two AI agents handling the same customer-service workflow. Agent A costs $0.08 per interaction. Agent B costs $0.20. Agent A appears cheaper. But suppose Agent A successfully resolves only 55% of cases, while Agent B resolves 90%. The remainder require retries, additional reasoning or human intervention. Which agent is actually cheaper? The inexpensive interaction may produce the expensive resolution. This illustrates a fundamental problem: We often measure AI where it is consumed rather than where value is created. Tokens are a unit of consumption. Businesses operate in outcomes. A customer-service leader cares about issues resolved. An engineering leader cares about high-quality software reaching production. A finance leader cares about reconciliations completed accurately. The economic denominator needs to move closer to the business. The AI Economic Ladder I think of this evolution as an AI Economic Ladder: Tokens → Interactions → Tasks → Outcomes → Value Each step moves measurement closer to what the enterprise actually cares about. At the token level: What intelligence did we consume? At the interaction level: What did each AI run cost? At the task level: What did it cost to complete the work? At the outcome level: What did a successful result cost? At the value level: Was the outcome worth creating? An AI system can become more efficient at every technical metric while creating little economic value. Conversely, an expensive AI workflow could be extraordinarily valuable if it prevents revenue leakage, reduces operational risk or accelerates a critical business process. The objective isn't cheaper AI. It is better economics. Not every completed task is a successful outcome There is another complication. If an agent completes a workflow, should we count it as a successful outcome? Not necessarily. A meaningful outcome needs three characteristics: Completed. Quality-gated. Attributable. It must reach its intended end state, meet an explicit standard for quality, accuracy, safety or business acceptability, and be attributable to the agent or workflow that produced it. That gives us a more meaningful measure: Cost per Successful Outcome = Fully Loaded AI Workflow Cost / Completed, Quality-Gated, Attributable Outcomes The denominator becomes real only when named in business language: cost per prior authorization resolved in healthcare, per pull request triaged and tested in engineering, per disputed invoice reconciled in finance operations. If you cannot name the outcome in a sentence the process owner recognizes, you are not ready to measure it. The quality gate matters. With AI, "the system ran successfully" and "the system produced a good outcome" are not the same thing. Microsoft Foundry's tracing and evaluation capabilities become economically important for precisely this reason. Evaluation isn't merely quality control. It helps determine what gets counted as value. What does an AI outcome really cost? The true economic footprint goes far beyond inference: Model + Reasoning + Grounding + Tools + Orchestration + Infrastructure + Retries + Evaluation + Governance + Human Intervention Human intervention is particularly easy to overlook. Every time someone must review, correct, approve or recover an AI-generated outcome, the economics change. The same applies to verification. An agent reaching an acceptable result in three steps has different economics from one requiring fifteen steps and multiple retries. And verification is not a rounding error — it is the bulk of the bill. McKinsey's 2026 analysis of production agentic workflows found roughly 60% of an agentic task's cost is tied to refining answers — checking, repairing, re-verifying — not generating the initial response. Most of what you pay for is not intelligence. It is assurance. This means quality and economics are connected. The quality bar you set influences the cost you pay. The challenge isn't simply minimizing consumption. It is finding the right balance between quality, cost, speed and risk. Cost per outcome is only half the equation Now imagine two agents. Both cost $5 per successful outcome. One saves an employee ten minutes of administrative work. The other prevents $500 in revenue leakage. Their cost efficiency is identical. Their economics clearly aren't. So we need to move another step up the ladder: from Cost per Outcome to Value per Outcome. The question isn't only how cheaply AI can complete the work. It is: How much economic value does this outcome create relative to the intelligence required to produce it? Now the CIO, CFO, CAIO and business leader have a common conversation. Give every outcome an Intelligence Budget Not every problem deserves the smartest model available. Classifying an email may require relatively little intelligence. Resolving a complicated customer complaint may justify more context and reasoning. Assessing the risks in a multimillion-dollar contract may justify sophisticated reasoning, multiple validations and human review. Every business outcome therefore has an economically rational amount of intelligence worth spending on it. Call it an Intelligence Budget. This changes the architecture question from which model should we standardize on, to: What combination of model, reasoning, context, tools and human judgment does this outcome deserve? This is where Microsoft Foundry's model router becomes interesting. Individual requests can be dynamically routed so simpler work doesn't consume the same model resources as complex reasoning. If the Intelligence Budget is the economic principle, intelligent routing is one way of operationalizing it. The future enterprise AI architecture won't be about one model doing everything. It will route intelligence according to the economics, quality and risk of the outcome. Making AI economics observable None of this works without visibility. An AI system can be technically healthy and economically unhealthy — responsive and error-free while repeatedly choosing inefficient reasoning paths, invoking unnecessary tools or producing outputs requiring expensive human correction. AI economics and AI observability are becoming inseparable. Microsoft Foundry increasingly connects these disciplines. Tracing shows what an agent did. Evaluation determines whether it met required criteria. Observability helps monitor production behavior. Agent optimizer can test improvements across prompts, skills and models. Microsoft's emerging ROI capabilities take the next step by connecting operating costs with measures such as task completion, time saved and cost efficiency. Attribution is the bridge to the finance conversation. Teams place Azure API Management in front of Foundry endpoints as an AI Gateway, stream token telemetry into Application Insights, and use Entra Agent ID to give every agent run a discrete identity that maps cost to its cost center. Microsoft Agent 365 extends the discipline tenant-wide — spending policies, budget caps and departmental chargeback across Microsoft and third-party agents. Together, they create something enterprises have historically lacked: A feedback loop between how intelligence is consumed and what that intelligence accomplishes. The paradox of cheaper intelligence There is another reason AI economics will become more important as models get cheaper. The Jevons paradox suggests that when technology makes a resource cheaper and more efficient, total consumption can actually increase. AI may experience the same effect. Cheaper intelligence enables more agents, more reasoning and more workflows that were previously uneconomic. So we could see cost per unit of intelligence fall while total intelligence consumed rises. Cheaper AI may therefore produce larger AI bills. That isn't necessarily bad — provided value grows faster than consumption. The objective isn't minimum AI consumption. It is maximum economic value from AI consumption. From workload economics to portfolio economics As AI scales, economics becomes a capital-allocation question. I see three levels. Workload Economics: Is this AI system running efficiently? Outcome Economics: Is it producing quality outcomes economically? Portfolio Economics: Where should we put our next AI dollar? That final question will become increasingly important. An enterprise with hundreds of AI initiatives shouldn't assume every one deserves continued investment. Some should scale. Some need optimization. Some should be redesigned or consolidated. And some should be stopped. The ability to experiment cheaply created the first explosion of enterprise AI. The discipline to allocate capital intelligently will determine what scales. Who owns AI economics? Once an agent becomes part of how work gets done, its economics cannot remain purely an IT metric. The business understands the value of the outcome. Technology understands the architecture and optimization levers. Finance brings economic discipline and comparability. That suggests a shared model: Business owns the outcome. Technology owns the optimization levers. Finance owns the economic discipline. AI economics ultimately isn't just a technology-cost conversation. It is a business-performance and capital-allocation conversation. From abundant intelligence to intelligent economics We are entering an era where intelligence is becoming an increasingly abundant, programmable and variable-cost resource. Microsoft Foundry and the broader Microsoft AI stack are making it easier to build, evaluate, observe, optimize and govern that intelligence. But abundant intelligence does not guarantee abundant value. Enterprises still need to decide where AI belongs, how much intelligence each problem deserves, what defines a successful outcome, when humans should remain involved and which AI investments deserve more capital. The winners won't necessarily use the cheapest models. They won't consume the fewest tokens. And they won't be the organizations that build the most agents. They will become exceptionally good at moving up the AI Economic Ladder: from consumption, to outcomes, to value. Because the next era of AI won't be won by organizations that buy intelligence most cheaply. It will be won by those that convert intelligence into value most efficiently. Where to start: the first 90 days Define the denominator for your top three agents — what counts as done, what quality gate applies, who signs off. Instrument attribution — Azure API Management as an AI Gateway, token telemetry to Application Insights, Entra Agent ID on every run. Wire evaluations into the cost pipeline so only quality-gated outcomes count. Set Intelligence Budgets — model router per request, agent optimizer against your evaluators, Agent 365 policies as circuit breakers. Stand up a joint monthly review — business, technology and finance on one dashboard: outcomes delivered, cost per outcome, value per outcome. Frequently asked questions What is Cost per Successful Outcome in enterprise AI? The fully loaded cost of an AI workload divided by outputs that were completed, quality-gated and attributable - for example, cost per prior authorization resolved or per pull request triaged. It turns token metrics into the unit economics of AI-performed work. What is an Intelligence Budget? The economically rational amount of intelligence - model capability, reasoning, context, tools and human review — worth spending on a given outcome, based on its value and risk. Model router in Microsoft Foundry is one way to operationalize it. Why do AI agents cost more than single model calls? One agent task can involve planning, tool calls, retries and verification - many model calls with compounding context. Research on production agentic workflows attributes roughly 60% of task cost to refining and verifying answers, not generating the first response. Will falling model prices make AI cost management unnecessary? No. By the Jevons paradox, cheaper intelligence expands consumption, so total AI spend typically rises as unit prices fall. The discipline that matters is maximizing value per unit of intelligence. Who should own AI economics? A shared model: the business owns the outcome and its value, technology owns the optimization levers, and finance owns the economic discipline and review cadence. #MicrosoftFoundry #Agent365 #AzureAI #FinOps #AgenticAI #AIAgents #Azure #MicrosoftCostManagement #AIEconomics #Tokens References Microsoft Azure Blog: "The Economics of Agent Optimization: From pilots to measurable returns" (August 12, 2026) Microsoft FY26 Q4 earnings call (Satya Nadella, July 2026) McKinsey — "Cost versus value: managing agentic AI system performance" (July 2026) FinOps Foundation — State of FinOps 2026; Microsoft Learn — Model router for Microsoft Foundry; Agent optimizer; Foundry Control Plane cost optimization
What is the Microsoft Graph API replacement for deprecated Recent, SharedWithMe, and Insights APIs?
Hi Microsoft Graph community, I'm currently working on a Microsoft Graph integration that needs to retrieve: Files recently accessed/used by the current user Files shared with the current user Files from OneDrive and SharePoint I'm currently using the following APIs: GET /me/drive/recent GET /me/drive/sharedWithMe GET /me/insights/used However, these APIs are deprecated, and some of them will stop returning data after November 2026. (https://learn.microsoft.com/en-us/graph/api/drive-sharedwithme?view=graph-rest-1.0&utm_source=chatgpt.com) I'm stuck in development because I haven't been able to identify a Microsoft-supported replacement that provides the same functionality. Could someone please clarify: What is the official replacement for /me/drive/recent? What is the official replacement for /me/drive/sharedWithMe? What is the official replacement for /me/insights/used? Is there a single recommended Microsoft Graph API that can provide recently used and shared files across both OneDrive and SharePoint? I'm specifically looking for the officially supported API/recommended approach, rather than a workaround that may also become deprecated. Any guidance from Microsoft Graph experts or Microsoft employees would be greatly appreciated. Thanks!Prepare for the launch of growth margins with API readiness resources
Starting October 1, 2026, growth margins will provide eligible partners with incremental margin on qualifying Microsoft 365 growth opportunities. Built on partner feedback, growth margins give you more flexibility to structure deals, compete for new business, reward reseller performance, and reinvest in capabilities that support long-term growth. Review the available readiness resources now so you can maximize growth opportunities, maintain business continuity, and prepare for upcoming technical changes. Technical guidance is available to help you navigate API changes and implement best practices for data export and billing automation. Review the partner resource collection. Evaluate opportunities to incorporate growth margins into your Microsoft 365 sales and growth strategies. Eligible partners may open an advisory case with Microsoft Partner Technical Consulting for API transition guidance.Transitioning from Microsoft 365 Business Premium to Business Basic: What Nonprofits Need to Know
As Microsoft begins transitioning out the Business Premium grant for nonprofits, many organizations are reassessing their licensing needs therefore this is an opportunity to streamline operations and continue leveraging powerful tools with Microsoft 365 Business Basic. _____________________________________________________________________________________________________ What Is Microsoft 365 Business Basic? Microsoft 365 Business Basic is a cloud-first productivity suite designed for organizations that don’t need desktop Office apps but still want access to essential collaboration and communication tools. It includes: ✅Web and mobile versions of Word, Excel, PowerPoint, and Outlook ✅Microsoft Teams for meetings, chat, and collaboration ✅Exchange Online with a 50 GB mailbox per user ✅OneDrive for Business with 1 TB of cloud storage ✅SharePoint Online for document management and team sites It’s a cost-effective solution for nonprofits looking to maintain productivity while reducing licensing expenses. __________________________________________________________________________________________________ The Change Microsoft has announced the retirement of the Business Premium grant, which previously provided eligible nonprofits with free access to premium features like desktop Office apps, Intune, and advanced security tools. As a result, many organizations are now exploring Business Basic as a cost-effective alternative. Note: If your organization decides to continue using Microsoft 365 Business Premium, you may be eligible for a discount of up to 75% through Microsoft’s nonprofit pricing. This can be a great option if you still need access to advanced features. ______________________________________________________________________________________________________ How to Transition from Business Premium to Business Basic Here’s a step-by-step guide to help you make the switch smoothly: Step 1: Evaluate Your Current Usage Identify users who don’t need desktop apps or advanced security features. Use the Microsoft 365 admin center to review license assignments and usage patterns. Step 2: Purchase Business Basic Licenses Go to Microsoft 365 admin center > Billing > Purchase services. Select “Details” next to Microsoft 365 Business Basic and buy the number of licenses you need. Important: Although the process says “purchase,” eligible nonprofits receive the first 300 Business Basic licenses for free. You will not be charged for these licenses, even though they are added through the purchase flow. Step 3: Reassign Licenses Navigate to Users > Active users. For each user, go to Licenses and Apps, uncheck Business Premium, and check Business Basic. Save your changes. Step 4: Remove Unused Premium Licenses Once all users are reassigned, reduce or cancel your Business Premium licenses to avoid unnecessary charges. Go to Billing > Your Products Click on Microsoft 365 Business Premium, then click remove licenses Ensure that users have been unassigned licenses or that may cause an error Step 5: Communicate the Transition Let your team know what’s changing and what tools they’ll still have access to. Offer training or resources to help them adapt to web-based tools. ______________________________________________________________________________________________________ Business Premium vs Business Basic Comparison Feature Business Premium Business Basic Desktop versions of Office apps (Word, Excel, PowerPoint, Outlook, etc.) ✅ ❌ Advanced security features (Microsoft Defender for Business, Microsoft Purview) ✅ ❌ Device management (via Microsoft Intune) ✅ ❌ Access and Publisher (PC only) ✅ ❌ Webinar hosting and attendee tools in Teams ✅ ❌ ______________________________________________________________________________________________________ What You’ll Still Have with Business Basic Despite the changes, you’ll retain access to essential tools that support collaboration and productivity: Web and mobile versions of Office apps Microsoft Teams (chat, call, meet with up to 300 attendees) Business-class email with Exchange 1 TB of OneDrive cloud storage SharePoint Standard security and support ______________________________________________________________________________________________________ Making the Most of Microsoft 365 Business Basic Even without desktop apps, Business Basic offers a robust suite of tools to keep your team connected and productive: ✅ Web-Based Office Apps Use Word, Excel, PowerPoint, and Outlook directly in your browser. Collaborate in real-time with colleagues on shared documents. ✅ Microsoft Teams Host virtual meetings, chat, and collaborate on files. Create channels for departments or projects to streamline communication. ✅ OneDrive and SharePoint Store and share files securely in the cloud. Use version history and co-authoring to improve productivity. ✅ Email and Calendar Access professional email with a 50 GB mailbox via Outlook on the web. Manage calendars and schedule meetings with ease. ___________________________________________________________________________________________________ Final Thoughts While the retirement of the Business Premium grant may require some adjustments, Microsoft 365 Business Basic still provides essential tools to help your nonprofit thrive. With thoughtful planning and a focus on cloud-based collaboration, you can continue to operate efficiently and make a meaningful impact—without breaking your budget.Microsoft Teams Meeting Controls: July 2026 M365 Champions Community call
Hello Champions! Here’s a recap and top Q+A from our July M365 Champions monthly call of 2026. We kicked off the call annoucing a new Champion Stories program to showcase real-world Microsoft 365 Copilot adoption success stories from the Champions community. Organizations that have successfully introduced or scaled Copilot are invited to share their journey, lessons learned, and best practices. Selected stories will be professionally filmed and published to help other Champions learn from peer experiences. Submit your story at aka.ms/ChampionStory. This month's main topic featured the redesigned Microsoft Teams meeting controls with Michelle Maislen, Principal Product Manager and Ryan Miller, UX Researcher from the Microsoft Teams product group. She explained that the redesign was driven by customer feedback around cluttered meeting controls, accidental clicks, and difficulty finding key features. The new experience introduces a cleaner, more organized toolbar with mic, camera, and share controls prioritized, separates the Share and Leave buttons to prevent accidental exits, moves advanced features into a structured “More” menu, and allows users to customize their meeting controls through drag-and-drop pinning. She acknowledged that changes such as moving Raise Hand under Reactions may be polarizing, but emphasized that users can personalize the toolbar to fit their workflow. Michelle also detailed the phased rollout plan, with users receiving opportunities to opt in before automatic migration, and shared that the redesign will extend across meetings, webinars, and town halls. Throughout the discussion and Q&A, she reinforced that the goal is to create a simpler, more intuitive, and highly customizable Teams meeting experience while preserving access to all existing meeting functionality. Click here to learn more about the Teams Meeting Controls redesign. Q+A from this month's session: 1. When will the new Teams Meeting Controls reach General Availability (GA)? Answer: Microsoft expects the redesigned meeting controls to roll out worldwide in September 2026, following preview validation and user feedback. 2. How does the 20-day rollout experience work? Answer: Users will receive several opportunities to opt in to the new experience. After approximately 20 days, they will be automatically migrated. 3. Can users switch back to the old meeting controls? Answer: Yes. A temporary toggle allows users to switch back to the old experience, although Microsoft plans to remove this option in the future. 4. Why was Raise Hand moved under Reactions? Answer: Research showed users frequently clicked the wrong button when Raise Hand and Reactions were adjacent. Moving Raise Hand under Reactions reduces accidental clicks. 5. Can users move Raise Hand back to the main toolbar? Answer: Yes. Users can drag and pin Raise Hand to the main toolbar if they prefer it there. 6. Can users customize the meeting toolbar? Answer: Yes. Most controls can be pinned, unpinned, and rearranged using drag-and-drop customization. 7. Which controls cannot be moved? Answer: Microphone, Camera, Share, and Leave remain fixed to ensure a consistent core meeting experience. 8. Will toolbar customizations persist between meetings? Answer: Yes. Customizations persist across meetings on the same device. 9. Will toolbar settings sync across multiple devices? Answer: Not initially. Microsoft indicated multi-device synchronization is planned for a future update. 10. Can users pin specific reactions (such as Thumbs Up) to the toolbar? Answer: Not in the initial release. The team acknowledged the request and is considering expanded reaction customization. 11. Will Microsoft add more meeting reactions? Answer: Yes. The Teams team confirmed they're exploring expanded reaction sets and potentially custom organizational reactions. 12. Does the redesign apply to Webinars and Town Halls? Answer: Yes. The redesigned controls will be available across Teams meetings, webinars, and town halls. 13. Is the redesign available in both Teams Desktop and Teams Web? Answer: Yes. The redesigned controls are supported in the Desktop and Web clients. 14. Will Virtual Desktop Infrastructure (VDI) environments be supported? Answer: Yes. Microsoft confirmed support for VDI deployments. 15. Why redesign the meeting controls at all? Answer: The redesign addresses common pain points including: Toolbar clutter Difficulty locating controls Accidental clicks Confusion between Reactions and Raise Hand Accidentally clicking Leave instead of Share 16. Where did features like Notes, Rooms, Apps, Facilitator, and Captions go? Answer: These capabilities were not removed. They have been reorganized under the new More menu to create a cleaner primary toolbar. 17. What adoption and readiness resources are available? Answer: Microsoft published: An IT Pro Change Management Guide An End User Visual Guide Adoption content on adoption.microsoft.com These resources are designed to help organizations prepare users for the transition. 18. Is Microsoft addressing AI-related meeting security concerns? Answer: Yes. The Teams team is actively working on better visibility and notifications for: AI note-taking bots External recording tools Third-party meeting assistants 19. Can meeting actions and decisions automatically flow into other Agents or workflows? Answer: The question was raised by attendees, and Microsoft acknowledged the scenario as valuable feedback. No roadmap or confirmed functionality was announced. 20. Will Education (EDU), GCC, and other government environments receive the redesign? Answer: GCC is expected to receive the update roughly in line with worldwide rollout. GCCH and DoD environments are expected to follow later. EDU deployment details were still being validated during the session. Join us on September 22nd for our next community call. Haven't joined the program yet? It's free! Join here: https://aka.ms/M365Champion. Bring your questions to our discussion forum: https://aka.ms/DriveAdoption.
Bridging the Skills Gap: Empowering Non-Coders to Automate Workflows in M365
Namstey Folks 🙏, As we look at digital transformation, one of the biggest bottlenecks is the skills gap in handling complex operational workflows. With the rise of modern M365 extensions and Power Platform capabilities, the barrier to entry is shifting. We can now build robust solutions directly inside SharePoint without needing heavy custom code. From what I’ve seen, the benefits of going the low-code/no-code route within the M365 ecosystem are clear: - Faster Deployment: Building internal workflows directly where teams already work cuts out weeks of standard dev cycles. - Empowered Teams: Operations teams can patch their own inefficiencies without waiting in a long IT queue. However, it also opens up real strategic questions around data governance, compliance, and keeping these citizen-developed solutions maintainable over time. How is your organization approaching upskilling for this? Are you training existing operational teams to build their own tools within the Microsoft ecosystem, or is IT still handling everything from the top down? Let's build robust solutions
How to Get Swags From Microsoft
Hi Team, Greetings of the Day, I'm completed the some Microsoft Azure Certifications. But , I'm not apply for the Gifts like T-Shirts..etc from Microsoft. Could anyone please help me in this.. How to apply and get those... please reply me... Warm Regards, Vanamali. vanamalimatha How to Applu
