Copilot, Microsoft 365 & Power Platform Community call
💡 Copilot, Microsoft 365 & Power Platform weekly community call focuses on different use cases and features within the Copilot, Microsoft 365 and Power Platform - across Microsoft 365 Copilot, Copilot Studio, SharePoint, Power Apps and more. 👏 Looking to catch up on the latest news and updates, including cool community demos, this call is for you! 📅 On 18th of June we'll have following agenda: Copilot prompt of the week CommunityDays.org update Microsoft 365 Maturity model Latest on PnP Framework and Core SDK extension Latest on PnP PowerShell Latest on script samples Latest Copilot pro dev samples Latest on Power Platform samples Picture time with the Together Mode! Reshmee Auckloo (Avanade) – Insurance Claims Assist using AI in SharePoint with Copilot Studio Garry Trinder (Microsoft) – No API, No Problem: Building Declarative Agents with Dev Proxy David Warner (Quisitive) – Powerful Animations - VS Code Extension Updates for M365 and Power Apps 📅 Download recurrent invite from https://aka.ms/community/m365-powerplat-dev-call-invite 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/m365-powerplat-dev-call-join 👋 See you in the call! 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!Microsoft Power Platform community call - June 2026
💡 Power Platform monthly community call focuses on different extensibility options for builders, makers and developers within the Power Platform. Typically demos are from our awesome community members who showcase the art of possible within the Power Platform capabilities. 👏 Looking to catch up on the latest news and updates, including cool community demos, this call is for you! 📅 On 17th of June we'll have following agenda: Power Platform Updates & Events Latest on Power Platform samples Elliot Margot (Witivio) - Process Mining + Copilot Studio: Stop Reading Dashboards, Start Asking Questions Sailaja Mantripragada (Low Code Power) - From Prompt to a Filled-In Word Template: Automating Deep Customer Research with Copilot Studio and Agent Flows John Liu (Rapid Circle) - Using Copilot Cowork with MCP to build Power Automate flows 📅 Download recurrent invite from https://aka.ms/powerplatformcommunitycall 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/PowerPlatformMonthlyCall 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 👋 See you in the call! 📖 Resources: Previous community call recordings and demos from the Microsoft 365 & Power Platform community YouTube channel at https://aka.ms/community/videos Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/homeCopilot, Microsoft 365 & Power Platform product updates call
💡Copilot, Microsoft 365 & Power Platform product updates call concentrates on the different use cases and features within the Microsoft 365 and in Power Platform. Call includes topics like Microsoft 365 Copilot, Copilot Studio, Microsoft Teams, Power Platform, Microsoft Graph, Microsoft Viva, Microsoft Search, Microsoft Lists, SharePoint, Power Automate, Power Apps and more. 👏 Weekly Tuesday call is for all community members to see Microsoft PMs, engineering and Cloud Advocates showcasing the art of possible with Microsoft 365 and Power Platform. 📅 On the 16th of June we'll have following agenda: News and updates from Microsoft Together mode group photo Vesa Juvonen – How to share and reuse SharePoint Skills - Introducing open-source SharePoint Skills Sahil Baid – Introduction to List Agent in Microsoft 365 Copilot Vesa Juvonen & Bert Jansen – Introduction to SPFx Copilot Apps 📞 & 📺 Join the Microsoft Teams meeting live at https://aka.ms/community/ms-speakers-call-join 🗓️ Download recurrent invite for this weekly call from https://aka.ms/community/ms-speakers-call-invite 👋 See you in the call! 💡 Building something cool for Microsoft 365 or Power Platform (Copilot, SharePoint, Power Apps, etc)? We are always looking for presenters - Volunteer for a community call demo at https://aka.ms/community/request/demo 📖 Resources: Previous community call recordings and demos from the Microsoft Community Learning YouTube channel at https://aka.ms/community/youtube Microsoft 365 & Power Platform samples from Microsoft and community - https://aka.ms/community/samples Microsoft 365 & Power Platform community details - https://aka.ms/community/home 🧡 Sharing is caring!Partner Blog | Copilot monetization for SMBs: Convert renewal momentum into wins
Partners serving small and medium-sized businesses (SMBs) continue to tell us that customers are excited about AI, but they want clear guidance on what to buy, how to buy it, and how to justify the investment. For partners, this creates a critical opportunity to simplify the path to decision and translate that momentum into measurable wins. This is the third installment in our Copilot series focused on SMB monetization. Earlier posts covered how Microsoft 365 Copilot Chat introduces AI in an approachable way and how Microsoft 365 Copilot Business embeds AI into everyday work, and how agents extend AI into core processes. This month, we are focusing on the moment that matters most: converting interest into action. Stage 3: Empower & Achieve is the inflection point Stage 3 of the Microsoft Customer Engagement Methodology (MCEM), Empower & Achieve, is built for customers approaching a decision point. This is where partners can accelerate deals and create a more predictable path to conversion. As customers evaluate their options, partners can help move them forward by: Bundling Microsoft 365 Copilot Business with Microsoft 365 at renewal or upgrade moments Reducing friction with promotion kits, in-market offers, and CSP incentives Reinforcing value with ROI tools, business case builders, and customer success stories These actions help simplify decision-making while addressing the two things SMB buyers care most about: clarity and confidence. This is also where Customer Zero partners stand out. By sharing first-hand experience with Copilot, partners can bring practical insights into conversations and build the trust customers need to move forward. With the recent announcements on transitioning Microsoft 365 Business with Copilot promotion bundles into two durable SKUs, partners are well positioned to help organizations scale from intent to action, while giving organizations the controls to scale AI responsibly. Stage 3 is also where you can align go-to-market efforts to a repeatable framework. When you consistently apply the Empower & Achieve motion, you can improve conversion at renewal and upgrade moments, strengthen your value story, and create a clear on ramp to ongoing adoption and expansion. Continue reading blog here
News to Know – Volume 3, Edition 6, June 2026
This month’s newsletter brings together the latest updates, insights, and best practices to help you use Viva Glint & Pulse as part of your broader AI transformation strategy. As Copilot adoption grows, employee listening can help organizations better understand employee experiences, identify opportunities for support, and turn feedback into action that drives meaningful business impact. *Side note: Have you configured your Viva Glint blog notifications to send you an email when a new newsletter or blog is posted but you haven’t been receiving them? You may need to add notifications@communityhub.microsoft.com to your approved email sender domain list to ensure that you get the email notifications. We’ve also added this information here. New on your Viva Glint platform This section highlights new capabilities and updates now available to help you strengthen security, reporting, and administrative control in Viva Glint. Benchmark Refresh: Industry benchmark suites. This month, the industry benchmarks have been updated in alignment with the annual refresh cycle. As part of this update: Coverage has been refined, with Media added and Retail – Wholesale Distribution removed due to insufficient data. The one-year data collection suites are labeled “Industry 2025 (Calendar Year)” and include data collected from January 1 to December 31, 2025. To broaden benchmark coverage, a two-year data collection period (i.e., January 2024 - December 2025) was used to introduce Automotive and Nonprofit and to refresh Pharmaceuticals benchmarks. These benchmarks are labeled "Industry 2024 - 2025" on Viva Glint. To access external benchmark comparisons in reporting, customers must opt in to benchmarking. Opting in increases the overall benchmark data pool, improves data coverage, and supports a broader set of benchmark suites. Customers who have not opted in won’t be able to view or include external benchmarks in their reports. Survey Configuration: Custom confidentiality statements. Viva Glint admins now have the option to use Viva Glint’s default confidentiality statement in their survey programs, or they can opt to turn off the default Viva Glint confidentiality statement and define their own organization‑specific confidentiality messaging. This enables clearer, context-appropriate communication to survey participants while maintaining Viva Glint’s core confidentiality protections and trust standards. The update helps organizations meet legal, compliance, and cultural requirements without compromising employee trust. Learn more here and here. Reporting: Topic Assignments Included in Comment Report Export. When exporting comments from the Comments report to a spreadsheet, Viva Glint now includes the topic(s) assigned to each comment. This enhancement allows analysts to seamlessly extend their analysis into external tools with Viva Glint’s topics already applied. Coming soon to Viva Glint The following section offers an early look at capabilities coming to Viva Glint shaping the future of continuous listening, analytics, and AI‑powered insight. Please note that public documentation (e.g., MS Learn articles) is not typically published until a feature is generally available. Seamless Entra authentication for MTO organizations | Generally available starting mid June. Seamless Domain Discovery (SDD) will simplify the sign-in experience for multitenant organizations and support users by introducing automatic tenant discovery. This new Entra‑based experience reduces reliance on MTO policies, lowers admin overhead, and aligns Viva Glint access with standard Microsoft 365 sign‑in—delivering a more scalable and seamless authentication experience. For scenarios where users need to explicitly access a different tenant (for example, guest or support access) or they have access to more than a one Viva Glint instance with their credentials, domain selection remains available to ensure flexibility and control. This feature will start rolling out to MTO customers in mid June with the rollout expected to be complete by the end of June. Custom data retention policy | Generally available starting late June. Viva Glint admins will be able to set how long survey data is retained before deletion to help meet organizational and compliance needs. This policy will apply across Viva Glint survey data, including engagement, ad hoc, recurring, always-on, and 360 surveys, as well as focus areas and goals. Customers with an existing retention policy will see their current settings carried over automatically. Improved audit activity logs for user data import | Generally available starting late June. Viva Glint audit activity logs will soon provide enhanced visibility into successful data imports with a downloadable processed file details report. With this feature, admins can quickly review processed, updated, or partially ingested records for SFTP and MODIS user data imports. “Select All” toggle for report filters | General availability coming soon. A new “Select All” option in the reporting filter panel will let users select or clear every attribute value in one click. This removes the pain of managing filters with long value lists, speeding up analysis and reducing manual effort. We aim to make this feature generally available in the next couple of months. Copilot Reporting: Dynamic Topics with Copilot | General availability coming soon. By leveraging Copilot, this functionality is designed to enhance the relevance and context of comment themes by extending beyond the current static set of topics and identifying customer-specific topics that can be tracked over time. These custom topics will remain confined to your platform and will not be accessible to Microsoft or other customers. This feature will also improve the accuracy of assignment to topics for both standard and dynamic categorization. We aim to make this feature generally available in the next couple of months. Copilot-supported commenting for Viva Glint survey takers | Private preview ongoing. Soon, Viva Glint survey participants will be able to use an in-survey Copilot experience to polish their written feedback (please note: this capability is not available for respondents accessing surveys via attribute-based login or personalized links). Copilot can rephrase comments so employees can communicate more clearly and with greater confidence. By helping reduce distinctive writing patterns and making it easier to provide thoughtful input, the feature can increase comfort and perceived privacy—driving higher participation, richer responses, and more candid insights that organizations can act on. Continuous Employee Engagement with Workplace Metrics | Private preview ongoing. Improve actionability for Work-Life Balance and Collaboration focus areas by integrating Viva Insights workplace metrics into Viva Glint reporting. This feature will help Senior Leaders in your organization access supplementary data points, in conjunction with survey responses, to better understand their team's experience and conduct more data-driven discussions on what can be improved in these areas. Between survey cycles, leaders can also enable notifications to keep track of changes in their team's workplace patterns, allowing them to keep a better pulse on behavior change commitments. Private Preview is targeted in May 2026. Future capabilities will include the ability to map Viva Insights and Copilot metrics to survey items and bring in additional data sources from M365, such as meeting metadata and content. To express your interest, please complete the following: Private Preview: Continuous Employee Engagement with Workplace Metrics. If you are already part of the Employee Experience Customer Connection (EECC) program, request to join our Workplace Patterns & Continuous Listening EECC Teams subchannel through the main Viva Glint EECC Teams channel so you can iterate on the future of continuous engagement with the product team in monthly calls. If you aren’t already part of the EECC, see the Connect with us section in this newsletter for more detail on how to join. Employee Feedback Agent | Private preview ongoing. Enhance your Employee Listen program with The Employee Feedback Agent a dynamic, AI-powered conversation, where employees can share what matters most through natural, chat-like interactions, whether prompted or always-on, enabling real-time feedback and deeper insights into the drivers behind their experiences. By combining Copilot intelligence and People Science principles, the agent streamlines feedback collection and reduces administrative overhead for HR and leaders. Unlike traditional Copilot tools that simply summarize information, the Employee Feedback Agent collects experiential data through probing questions and back and forth dialogue with employees. Future capabilities will expand impact with an actionable insights reporting experience, accelerating the “feedback-to-action” cycle. Raw Data Export API Egress | Private preview ongoing. Unlock seamless, automated access to raw survey data—no more manual downloads. Built on Microsoft Graph, these APIs make integrations easier and help admins move faster with greater efficiency. Express your interest here. See our public roadmap for more feature updates. Events and learning opportunities Stay up to date with upcoming events, recent documentation updates, and highlights from EECC customer sessions—designed to help you learn, connect, and get more value from Viva Glint & Pulse. Recent documentation enhancements: Have technical questions about Viva Glint? Microsoft Learn is your best source for clear, current guidance. We’ve expanded and refined our documentation to add detail on new capabilities, address frequent questions, and strengthen the topics customers rely on most. These updates improve clarity and consistency, making it easier to use Viva Glint with confidence. Below are a few of the most impactful recent updates now live on Microsoft Learn: Additional notes added to live survey updates Update to allowed email sender domain list to ensure receipt of blog notifications Focus area cascading guidance clarification 360 configuration guidance updates here and here Important note added around adding survey reminders EECC Customer Engagement Sessions: Previous sessions: May 28th – Help Shape What’s Next for Viva Glint 360 Assessments Target Audience: Viva Glint 360 Admins We invited Viva Glint 360 admins to join an interactive listening session focused on the real-world experience of running 360 assessments in Viva Glint. The session created a space for admins to share candid feedback and directly influence the future direction of Viva Glint 360s, which have seen limited evolution to date. The discussion centered on where the 360 process creates friction for admins, managers, and participants; moments where workflows slow down, break, or require manual workarounds; and small, high-impact improvements that could meaningfully enhance the overall experience. It was a candid, discussion-driven session with the Viva Glint Product team and customer peers sharing what’s working well and where challenges remain. Key takeaways: Aggregate reporting emerged as one of the top customer requests, with many customers emphasizing the need for easier ways to consolidate and analyze 360 feedback data. Customers also exchanged creative workarounds and best practices during the session, showcasing strong peer collaboration within the community. Poll results helped validate the highest-priority enhancement areas, which will help inform future Viva Glint 360 investment planning. If you are not yet a member of the Employee Experience Customer Connection (EECC) but would like to participate in upcoming sessions, as well as gain access to numerous other engaging and valuable Viva Glint and Pulse customer activities, please see the sign-up information below. Customer Success Stories See how organizations are using Viva Glint, Pulse, and Copilot to turn employee insight into measurable impact. Energy Company Advances from Copilot Adoption to Measured, HR‑Led AI Transformation with Microsoft EVE After scaling Microsoft 365 Copilot across 20,000 employees, Energy company partnered with Microsoft’s Viva Glint team to introduce AI transformation measurement—aligning HR and IT around shared readiness, governance, and priorities for scalable agentic automation. Situation The customer scaled Microsoft 365 Copilot across 20,000 employees, but maturity varied across business units. As the organization shifts toward agentic automation, leaders need consistent, data‑driven measurement of readiness, impact, and transformation maturity to guide aligned enterprise investment. Solution At this critical inflection point, Microsoft's Viva Glint team engaged alongside the Microsoft FastTrack and broader account teams, introducing the Frontier Firm AI Transformation Measurement framework, enabling the customer to establish a common language for AI maturity and shift from qualitative discussions to data‑driven insight. Working closely with Group HR, Employee Experience (EEX), and IT, they leveraged Viva Glint to establish an enterprise‑wide measurement baseline—positioning HR as a strategic co‑driver of AI transformation alongside IT governance. Cross‑Functional Collaboration: HR and IT in Action Two priority areas emerged through joint HR–IT alignment: AI Transformation Measurement HR and IT partnered to create shared visibility into workforce readiness, adoption quality, and transformation maturity across the enterprise Viva Glint enabled scalable, repeatable measurement tied to business and technology priorities HR‑Led Agentic Experimentation HR partnered with IT governance to align agentic automation experiments to workforce readiness Ensured automation scaled responsibly, with employee experience, engagement, and change readiness embedded from the start Impact This customer is positioned to shift from AI experimentation to measured, governed, and scalable agentic transformation. Expected improvements in coming months include increases in Copilot MAU, higher usage frequency visible in dashboards, and strengthened employee engagement scores reflecting greater clarity and readiness for AI‑enabled work. Connect with us Stay engaged with the Viva Glint & Pulse community through the Employee Experience Customer Connection (EECC) program. The Employee Experience Customer Connection (EECC) program offers our customers an opportunity to be part of a feedback community as employee experiences continue to evolve with Viva and Microsoft 365 Copilot. What the program provides: Product team engagement for Employee Experiences powered by Viva and M365 Copilot Forums for you to influence product direction & unlock value for your organization Early insight into product roadmap Private preview engagement opportunities Connection with other enterprise customers If you’re interested in joining, please fill out this form so we can guide you through the enrollment process and help you get started. We look forward to partnering with you to build better products—together.Restricting Access is The Most Important Step in a Microsoft 365 Copilot Deployment
I was asked what the most important step is in the deployment of Microsoft 365 Copilot. It’s a good question. Put simply, restricted access is the answer. That is, restricting Copilot access to information stored in Microsoft 365 locations until your tenant is ready for unrestricted Copilot search and retrieval. The fortunate thing is that tools exist today to make it relatively easy to establish guardrails for Copilot, which is exactly what you need to do. https://office365itpros.com/2026/06/10/microsoft-365-copilot-prep/
From AI Suggestions to Autonomous CRM Actions in Dynamics 365
Modern CRM AI solutions often stop at case summarization—but real transformation requires more. This blog introduces a CRM Copilot Agent Accelerator built on Microsoft Power Platform, designed to evolve AI from simple insights to predictive intelligence and ultimately to autonomous actions. By combining Dynamics 365, Dataverse, Power Automate, and AI Builder, and extending capabilities through modular add-on packs, this approach enables organizations to reduce manual effort, improve decision-making, and scale service operations efficiently—without additional Copilot licensing.Make Your Copilot Credits Count: A Student's Guide to Smarter AI Usage
If you're a student enrolled in GitHub Education, you already have something most developers pay for: free access to GitHub Copilot and its premium features. That's incredible. But here's the thing, free access doesn't mean unlimited usage, and not all AI interactions cost the same. Every chat message, every agent task, every model call consumes something called AI Credits, and knowing how they work will help you use Copilot smarter, produce better code, and build the kind of disciplined AI habits that professional developers are only just starting to learn. This post is inspired by a fantastic deep-dive from my collegaue developer advocate Bruno: "GitHub Copilot and Tokens: How to Keep Using AI Without Burning Your Budget" . We've taken those professional lessons and tailored them specifically for students because your learning environment, your assignments, and your goals are different from a seasoned engineer at a tech company. TL;DR: Use autocomplete before chat. Choose the right model. Keep context small. Start fresh chats often. Plan before you build. These habits will make you a better developer and stretch your credits further. What Are AI Credits and Why Do They Matter? When you interact with GitHub Copilot through chat, agent mode, or inline edits the model processes tokens. Tokens are small chunks of text (roughly 3–4 characters each). Every interaction consumes: Input tokens — everything sent to the model (your message, attached files, chat history, instructions) Output tokens — everything the model generates back to you Cached tokens — context the model reuses from previous turns (cheaper) These tokens are converted to AI Credits, where 1 AI Credit = $0.01 USD. Different models have very different token costs a lightweight model like GPT-5 mini charges $0.25 per million input tokens, while a powerful model like GPT-5.5 charges $5.00 per million input tokens (20x more expensive). Using the wrong model for a simple task is like taking a taxi to a destination that's a 5-minute walk. See the official pricing table: GitHub Copilot Models and Pricing . Figure 1: The four cost tiers of Copilot interactions. Autocomplete and Next Edit Suggestions are free — they do not consume AI Credits on paid plans Strategy 1: Tab Before Chat The Free Tier is Powerful Here is the single most impactful habit you can build: always try autocomplete before opening chat. According to GitHub's official billing documentation, code completions and Next Edit Suggestions are not billed as AI Credits on paid plans. That means every time you press Tab to accept an inline suggestion, you are getting AI assistance for free. Use autocomplete (Tab) for: Completing a line or a simple function Generating repetitive boilerplate (constructors, properties, getters/setters) Completing a repeated pattern you've started Writing obvious next lines like console.log , imports, or variable declarations Adjusting variable names inline Only move to Inline Edit (Ctrl+I / Cmd+I) when autocomplete isn't enough for a local change. Only open a Chat window when you need genuine reasoning an explanation, a plan, or a multi-step solution. As Bruno puts it: "The most expensive model in the world should not be helping you write public string Name { get; set; } . That's what Tab is for. And coffee." Strategy 2: Choose the Right Model for the Job GitHub Copilot gives you access to models from OpenAI, Anthropic, and Google each at different price points and capability levels. The key insight from VS Code's official Copilot usage guide is: reserve powerful reasoning models for tasks that genuinely need them. Your Task Recommended Model Tier Example Models Simple question or boilerplate Lightweight GPT-5 mini, Gemini 3 Flash Code explanation or basic docs Lightweight GPT-5 mini, GPT-5.4 nano Writing tests or debugging a single function Medium / Versatile Claude Haiku 4.5, GPT-5.4 Multi-file refactor or code review Medium / Versatile Claude Sonnet 4.6, GPT-5.4 Complex system design or architecture Powerful Claude Opus 4.7, GPT-5.5 Long agentic workflows Powerful (scoped!) Claude Opus 4.8, GPT-5.5 Not sure what you need Auto (recommended default) Copilot selects for you GitHub Copilot's Auto Model Selection feature automatically chooses a model based on task complexity, availability, and policies. For most students, Auto should be your default only switch manually when you have a specific reason. And when the complex task is done, switch back to Auto or a lighter model. Strategy 3: Context is Currency Smaller is Smarter Here's the counterintuitive truth that surprises most developers: the expensive part of a prompt is usually not the question you type it's everything surrounding it. Every token consumed by Copilot includes: All your previous chat messages in the session Every file you have open or attached Workspace search results Copilot pulled in Build output, terminal logs, or diff content Responses from any MCP (Model Context Protocol) servers you have enabled Your custom instructions file ( .github/copilot-instructions.md ) A single question inside a conversation with 80 messages, 12 open files, and 3 tool call results can cost significantly more than the same question asked fresh in a new chat with one relevant file attached. Figure 2: The same task asked two ways. Scope your prompts to save credits and often get better answers. Practical rules for context management: Attach only 2–3 relevant files — not your entire project Don't ask Copilot to analyse the whole repo when you only need changes in one module Paste only the first relevant error from a log, not 2,000 lines of output Remove timestamps and duplicate stack traces from pasted logs State the expected output format explicitly so the model stops early Use /compact in VS Code Chat to summarise a long conversation without losing key context Use /fork to explore an alternative direction without polluting the main conversation Strategy 4: Start Fresh Chats When You Change Tasks This is one of the simplest optimisations and one of the most ignored. The VS Code Copilot usage guide is explicit about it: when a conversation grows, it carries context from all previous messages. If you switch to an unrelated task in the same session, the model still processes that irrelevant history and you pay for it in credits. Bad pattern: Chat session: - "Help me fix the JWT bug in auth.ts" [10 messages] - "Now write unit tests for my sorting algorithm" [still in same chat!] - "Can you generate the README for my project?" [still in same chat!] - "Now debug this CSS layout issue..." [still in same chat!] Smart pattern: Chat 1: "Fix JWT bug in auth.ts" - DONE, close chat. Chat 2: "Write unit tests for sorting algorithm" - DONE, close chat. Chat 3: "Generate README for project" - fresh context, fresh cost. New task = new chat. Your human brain benefits too — focused sessions produce better outcomes than sprawling multi-topic conversations. Strategy 5: Plan Before You Build Use Agent Mode Wisely Agent mode is one of the most powerful Copilot features for students working on larger assignments — it can create files, run terminal commands, edit across multiple files, and execute tests. But agent mode also carries the highest token cost, because it loops: it plans, acts, observes tool output, then plans again. The VS Code documentation recommends separating planning from implementation to reduce rework and back-and-forth. Here's a phased approach that saves credits and produces better results: Figure 3: The credit-smart workflow. Always try the cheaper option first, escalate only when needed. Phase 1: Plan (lightweight model, low cost) I need to add user authentication to my Express app. Before writing any code, give me a step-by-step plan covering which files to create, which packages to install, and what tests to write. Do not write code yet. Phase 2: Scoped Implementation (one feature at a time) Using the plan we agreed, implement only Step 1: create src/middleware/auth.ts with JWT validation. Do not modify any other files yet. Phase 3: Validate Run the existing tests in tests/auth.test.ts and report the results. Fix only test failures related to the new auth middleware. Phase 4: Cleanup The implementation is complete. Update README.md with setup instructions for the auth module. Keep it under 200 words. Each phase is small, scoped, and verifiable. You can stop at any phase, check the result, and only continue when you're satisfied. This dramatically reduces expensive re-runs where the agent reverses its own changes. Strategy 6: Review Your MCP Servers and Custom Instructions MCP Servers MCP (Model Context Protocol) servers let Copilot connect to external tools databases, GitHub issues, Jira, Slack, browser automation, and more. Each enabled server expands what the agent can do, but also adds to the context the model must consider, which increases token usage. For students, a practical rule: only enable MCP servers relevant to your current project. If you're working on a simple Python web app, you probably don't need browser automation, a Kubernetes connector, and a Slack integration all active at the same time. See the VS Code MCP servers documentation for how to enable, disable, and configure them. Custom Instructions A .github/copilot-instructions.md file in your repository lets you give Copilot standing instructions — coding standards, testing commands, architecture conventions. This is a fantastic feature. But that file is included in every prompt's context, so a bloated instructions file costs credits on every single interaction. A good custom instructions file is: Short — under 200 words for a student project Specific to this repository's real conventions Clear about test commands (e.g., npm test , pytest ) Free of generic advice that applies to every codebase on earth Example of a good student instructions file: # Copilot Instructions for MyWebApp Language: TypeScript (strict mode) Framework: Express.js with Prisma ORM Tests: Run with `npm test` (Jest) Lint: Run with `npm run lint` (ESLint + Prettier) Conventions: - Use async/await, not callbacks - Validate all request inputs with Zod - Keep controllers thin; put logic in service files - Write a test for every new public function That's it. Short, actionable, and genuinely useful — not a 500-line manifesto. Strategy 7: Use Traditional Tools First AI is excellent for reasoning, explaining, planning, and connecting ideas. It is not the right tool for every job. Before reaching for Copilot chat, ask yourself whether a traditional tool can answer your question faster, cheaper, and more reliably: Compiler / type-checker — to find type errors (TypeScript, mypy) Linter — to find style and logic issues (ESLint, Pylint, Checkstyle) Formatter — to fix formatting (Prettier, Black, gofmt) Test runner — to confirm whether your code works (Jest, pytest, JUnit) Debugger — to step through execution and inspect state Docs / Stack Overflow — for well-documented APIs and common patterns If your linter tells you there's a missing import, fix it directly — don't ask Copilot to analyse your code to find it. Let deterministic tools do deterministic work, and let AI do the reasoning where it genuinely adds value. Your GitHub Education Benefits: What You Get If you haven't already, apply for GitHub Education with your school email address. Once verified, you receive: Free GitHub Copilot including premium features — see how to enable Copilot as a student Free GitHub Codespaces — 180 core hours per month, equivalent to GitHub Pro (great for browser-based coding with Copilot built in) GitHub Student Developer Pack — free access to dozens of professional tools from GitHub's partners, including cloud credits, domains, and IDEs GitHub Classroom — your instructors can manage assignments and provide feedback GitHub Community Exchange — discover and contribute to student-built projects Campus Experts program — become a student leader in your tech community These benefits are designed to give you real-world tools in an educational setting. Copilot is the standout feature — it's the same tool professional developers use every day. Using it wisely during your studies means you'll arrive in the workforce already ahead of the curve. Pre-Prompt Checklist for Students Before you fire off your next Copilot prompt, run through this checklist. It takes 10 seconds and can save significant credits — and more importantly, it builds the mental habits of a professional AI user. Figure 4: Two-column checklist covering what to check before opening chat and when writing your prompt. Before you open chat: ☐ Can Tab / autocomplete solve this? ☐ Is inline edit (Ctrl+I) enough for this local change? ☐ Can a linter, compiler, or test runner answer this? ☐ Is this a different task from my last message? If so, start a new chat. ☐ Am I on Auto model selection (or the right tier for this task)? ☐ Should I ask for a plan before asking for code? ☐ Do I have MCP servers enabled that I don't need right now? ☐ Is my copilot-instructions.md file concise and current? When writing your prompt: ☐ Attach only 2–3 relevant files, not the whole project ☐ Paste only the first relevant error from any logs ☐ Define the files to change, the goal, and any files not to touch ☐ Ask for a plan before implementation on complex tasks ☐ Remove timestamps and duplicate stack traces from pasted logs ☐ State the expected output format and length ☐ Use /compact if the session is getting long ☐ Use /fork to explore alternatives without polluting the main thread A Note on Responsible AI Use in Education Using Copilot smartly is not just about saving credits it's about developing genuine skills. When you ask Copilot to write all your code without understanding it, you lose the learning opportunity the assignment was designed to create. When you review and understand every suggestion Copilot makes, you learn faster, build better instincts, and can confidently explain your own work. Best practices for academic integrity with AI tools: Understand before you accept — never paste code you can't explain Use Copilot to learn, not to skip learning — ask it to explain the code it generates Follow your institution's AI policy — many universities have specific guidance on AI use in assessments Treat Copilot as a senior pair-programmer, not an answer machine — question its suggestions, push back, iterate Verify facts and documentation links — AI can hallucinate; always check official sources GitHub Education exists to give you real professional tools while you learn. The goal is for you to graduate with genuine skills, a real portfolio, and the confidence that comes from building things yourself — with AI as your collaborator, not your ghostwriter. Key Takeaways Tab first — autocomplete and Next Edit Suggestions are free; use them for everything small Auto model by default — only switch to a powerful model when you have a clear reason Context is cost — fewer files, fewer messages, fewer tools = fewer tokens New task = new chat — don't carry stale context into unrelated work Plan before you build — a 10-message plan session is cheaper than 50 messages of rework Keep instructions short — your copilot-instructions.md runs on every prompt Use traditional tools first — linters and compilers are free, fast, and deterministic Understand your code — Copilot is a collaborator, not a replacement for learning Resources and Next Steps GitHub Education — apply for your free student benefits GitHub Student Developer Pack — explore free tools for students Enable GitHub Copilot as a student GitHub Copilot: Models and Pricing — understand exactly what each model costs Auto Model Selection in GitHub Copilot VS Code: Optimising GitHub Copilot Usage — the official guide that inspired many of these tips Managing MCP Servers in VS Code El Bruno: GitHub Copilot and Tokens (the original professional perspective) GitHub Education Community Discussions — connect with students and educators worldwide This post draws on insights from El Bruno's developer blog and best practices from GitHub Education. All pricing figures are sourced from the official GitHub Copilot billing documentation and are correct as of June 2026.From insight to action: how Adobe and Microsoft are helping marketers move faster with AI
Today’s marketing leaders are under pressure to do more than ever—deliver meaningful personalization, accelerate execution, and prove measurable business impact. At the same time, teams are navigating increasing complexity: fragmented data, disconnected tools, and insights that arrive too late to act on. AI can change this—but only when it’s embedded directly into how people already work. That’s why Microsoft and Adobe are deepening our partnership: bringing customer experience intelligence, AI-powered workflows, and enterprise-grade AI directly into Microsoft 365 Copilot—so teams can move from insight to alignment to execution in one continuous workflow. The result is faster decisions, more coordinated execution, and clearer business outcomes—without breaking flow or context. Bringing customer experience intelligence into the flow of work Marketing teams don’t struggle because they lack data. They struggle because insights live in one place, collaboration in another, and execution somewhere else entirely. That disconnect slows teams down and creates unnecessary friction between analysis and action. Together, Adobe and Microsoft are changing that dynamic by connecting Adobe’s customer experience capabilities with Microsoft 365 Copilot and Copilot Cowork—so insight, collaboration, and next-best action can happen where work already happens: in Copilot Chat and in everyday apps like Teams, Word, and PowerPoint. Marketers can ask questions, explore insights, align with teammates, and take action without jumping between tools—turning intelligence into impact at the moment it matters. Adobe Marketing Agent for Microsoft 365 Copilot: now generally available A major milestone in this journey is the general availability of the Adobe Marketing Agent for Microsoft 365 Copilot, now available via Microsoft Commercial Marketplace. The Adobe Marketing Agent brings Adobe customer experience intelligence directly into Copilot, enabling marketing teams to: Accelerate time from insight to decision Move seamlessly from analysis to execution Keep humans firmly in control, with AI supporting—not replacing—decision‑making Importantly, the agent is enterprise-ready by design. IT administrators can deploy and manage the experience through the Microsoft 365 admin center, ensuring security, governance, and compliance at scale. Expanding executive experiences with Copilot Cowork Looking ahead, Adobe skills designed for customer experience orchestration will be accessible in Copilot Cowork—in a future release. This upcoming experience will enable customer experience leaders to engage with customer experience insights in a more direct, conversational way, bringing strategic visibility into the same Copilot environments where decisions are made and actions are coordinated. Built on Azure to scale securely and responsibly The technology foundation of this innovation is Azure. Adobe Experience Platform, Adobe Experience Platform Agent Orchestrator, and Adobe AI Agents are built on Azure and leverage Azure AI models, providing the scalability, security, and reliability enterprises require. By running on Azure, these agentic experiences benefit from Microsoft’s global infrastructure, enterprise‑grade security, and responsible AI commitments—supporting customer trust as organizations scale AI across their business. Designed for interoperability across agent ecosystems Modern enterprises don’t operate in a single ecosystem—and their agents shouldn’t either. Adobe agents are built to interoperate with agents created using Microsoft Azure AI Foundry or Copilot Studio, enabling customers to orchestrate richer, cross‑functional workflows across marketing, sales, service, and operations. This architecture is designed to enable organizations to compose agentic solutions that reflect how work actually happens—across systems, teams, and business processes. Moving from experimentation to execution This partnership reflects a broader shift in how organizations adopt AI—moving from experimentation to embedded, enterprise‑ready execution. By bringing the full power of Adobe Experience Platform together with Microsoft’s AI platform, cloud infrastructure, and Copilot experiences, we’re helping teams move faster with clarity, confidence, and control. This is how AI becomes not just powerful—but practical. Learn more Adobe + Microsoft partnership page Adobe Marketing Agent for Microsoft Copilot pagePitch Maker Agent: Turn Copilot Chat Signals into Microsoft 365 Copilot Deals
Executive Summary Customers are already using free Copilot Chat at scale, but adoption is often ungoverned and disconnected from the Microsoft 365 workloads where measurable productivity and risk controls live. The Pitch Maker Agent (BETA) helps partners convert Partner Center Copilot growth opportunity signals into customer-ready narratives—reducing pitch preparation from days to minutes and improving consistency across stakeholders (replace with your measured baseline). What it enables (partner outcomes) Turn raw usage signals into an executive business case with clear opportunity, risk, and next steps. Standardize value conversations across IT and business buyers while keeping customer context specific. Accelerate conversion from exploration to governed deployment by anchoring on Microsoft 365 workloads. Why it’s different Evidence-led: uses Partner Center Copilot growth opportunities (ASPX) signals rather than generic prompts. Buyer-ready: outputs a structured narrative (not a feature list) designed for executive alignment and action. Inputs required Partner Center Copilot growth opportunities export (all columns) for the target customer. The Opportunity: From AI Exploration to Enterprise Direction The move from free Copilot Chat to Microsoft 365 Copilot is a timing advantage: customers have intent and familiarity, but need a governed path that ties AI to real work in Teams, Outlook, Excel, and beyond. Advisory gap: translate usage metrics into business insight executives can fund. Governance gap: balance opportunity with security, compliance, and lifecycle controls. Workflow gap: connect AI usage to measurable outcomes inside Microsoft 365 workloads. How the Agent Works (BETA) The Agent follows a simple, repeatable flow to generate an executive-ready pitch narrative from Partner Center Copilot growth opportunity signals. See the agent in action below. In three steps Upload the Partner Center Copilot growth opportunities export (all columns). Run the Agent to translate usage signals into a customer-specific executive narrative. Use the generated business case, recommendations, and next steps in the customer conversation. What the Output Enables Translate Partner Center signals into a fundable business case, faster. Improve executive alignment by presenting opportunity, risk, and plan in one narrative. Increase repeatability across accounts with a consistent structure and messaging. The figure below illustrates how the Agent turns usage signals into a concise, executive-ready pitch narrative and action plan. Figure 1. From Copilot Chat signals to an executive pitch narrative and next-step plan. For customers, the conversation shifts from features to outcomes—clear productivity impact, role-based change, and risk-aware governance. Deployment and Execution The Agent is delivered as a solution package and deployed through Copilot Studio with a straightforward publish-and-run flow. Prepare Partner Center ASPX export (all columns) and validate sensitivity labels. Import the solution package into Copilot Studio. Verify dependencies, publish the Agent, and enable access in Microsoft 365 Copilot and Teams. Run the guided pitch flow by uploading customer data and capturing the narrative output. The run guide provides step-by-step visuals for data preparation, import, publication, and how to use the output in customer conversations. Why This Matters for Partner Practices The Pitch Maker Agent (BETA) supports a repeatable value motion: identify opportunity, align stakeholders, and move customers from experimentation to governed Microsoft 365 Copilot adoption. Higher conversion: clearer executive rationale anchored in evidence and outcomes. Lower effort: less time drafting, more time on discovery and delivery. Better governance: built-in prompts to address risk, readiness, and controls early. Call to Action This week: 15-minute start Locate the solution package and run guide in the Agent folder. Deploy the Agent in Copilot Studio and publish to Microsoft 365 Copilot/Teams. Export Partner Center Copilot growth opportunities data and validate sensitivity labels. Upload the dataset and generate a customer-specific executive pitch narrative. Resources Helpful links to learn more and access supporting materials: Partner Center Copilot growth opportunities data GitHub repository Overview: Run guide
