Primary Proposal: Copilot as an AI Gateway
Problem Statement Advanced users increasingly encounter limitations in Copilot’s ability to: generate or modify complex VBA safely maintain architectural integrity in multi‑module systems perform multi‑step workflows inside Office apps handle file generation or structured content creation operate without overly restrictive guardrails provide specialized domain expertise (e.g., coding, data science, creative tasks) Competitors — even free tiers — often outperform Copilot in these specialized tasks, despite lacking Microsoft’s integration advantages. This creates a mismatch between user expectations and Copilot’s current capabilities. Opportunity Microsoft does not need to build every specialized AI capability internally. Instead, Copilot can become the trusted orchestrator that: Authenticates the user Understands the task Selects the best AI engine for the job Executes the task securely Delivers the result inside Microsoft applications This approach: reduces Microsoft’s infrastructure burden increases Copilot’s capability ceiling preserves enterprise security and compliance provides users with best‑in‑class results positions Copilot as the central nervous system of the Microsoft ecosystem Proposed Architecture: Copilot as an AI Gateway Identity & Security Layer (Microsoft) Copilot remains the authentication and authorization layer, ensuring: user identity data boundaries compliance logging enterprise governance Task Classification Layer (Copilot) Copilot determines: the user’s intent the domain (VBA, Excel, OneDrive, coding, creative, etc.) the required capability level the risk profile AI Routing Layer (Copilot) Copilot selects the appropriate engine: Microsoft models for general tasks Specialized third‑party models for advanced tasks Local models for privacy‑sensitive operations Domain‑specific engines (e.g., coding assistants, creative generators) Integration Layer (Microsoft Apps) Results are delivered directly into: Excel Word PowerPoint OneDrive Windows Teams Outlook This is where Copilot’s integration advantage becomes unbeatable. Benefits to Microsoft Reduced infrastructure burden Increased user satisfaction Competitive differentiation Enterprise trust Developer ecosystem growth Secondary Proposal: OneDrive User‑Choice Restoration Overview OneDrive’s increasing emphasis on automatic cloud storage, forced sync behaviors, and reduced local‑storage autonomy has created friction for advanced users and power workflows. While these defaults benefit casual users, they can unintentionally disrupt professional, technical, and offline‑critical workflows. Restoring user choice — even through advanced or hidden settings — would allow OneDrive to serve both mainstream and power users without compromising Microsoft’s cloud‑first strategy. Issues Addressed Forced Cloud Migration Can Break Application Dependencies Automatic OneDrive migration can cause: broken links missing references VBA failures sync conflicts unexpected file locks Especially in Excel/VBA environments and engineering workflows. Sync Conflicts Create Data Integrity Risks Automatic sync can introduce: partial uploads version conflicts corrupted files duplicate “ghost” versions These issues disproportionately affect advanced users. Offline‑Critical Workflows Are Undermined Forced cloud storage can result in: files unavailable offline delayed syncs “file not found” errors This disrupts field work, travel, and low‑connectivity environments. User Intent Is Overridden Automatic folder redirection and forced sync violate a core professional principle: Users should control where their files live. Enterprise and Power Users Need Granular Control Organizations and advanced users often need: selective sync local‑only folders per‑directory rules opt‑out flags Providing these options would dramatically reduce friction. Proposed Solution Introduce a User Choice & Advanced Control Panel for OneDrive, allowing: per‑folder sync control local‑only folder designation optional migration prompts clear visibility into file location enterprise policy overrides Outcome This complements the Copilot gateway proposal by ensuring the underlying file system behaves predictably — a prerequisite for reliable AI‑assisted workflows.
Can Copilot help create development plan suggestions after a review?
After performance reviews, we want managers to turn feedback into practical development plans, but the quality is inconsistent. Some managers write clear next steps, others keep it very generic. Has anyone used Copilot or another AI workflow to suggest development actions based on review feedback, goals, or competencies? Could I build an agent specific to this? Could I create a subskill that standardizes this? Should I go for something third party?
Confusion between Gemini and Copilot
Microsoft Copilot and Google Gemini are sending me mixed signals on whether MAI’s Phi (Microsoft’s on-device small language models) models support LoRA adapters or any sort of community fine tuning. Copilot is saying no, and Gemini is saying yes. I need to talk with real Microsoft engineers to confirm with Microsoft if their Phi models support LoRA adapters or not.Copilot Feedback - Power User Experience Improvements
As a frequent Copilot user for technical discussions, architecture, governance, Microsoft 365, Power Platform, and problem-solving activities, I would like more control over the user experience. Copilot has become a daily productivity tool, but several UI and usability improvements would significantly benefit advanced users. 1. Allow Disabling Suggested Follow-Up Prompts The suggested replies shown below every response may be useful for new users, but for experienced users they often add little value and consume screen space. Please provide an option to: Disable suggested prompts entirely Adjust their frequency or aggressiveness Enable them only for new conversations or learning scenarios 2. Make '/' and '@' Shortcuts Configurable The automatic triggering of slash commands and @ mentions while typing can be disruptive and may interrupt or replace text unexpectedly. Please allow users to: Disable these shortcuts Configure alternative trigger characters Require a keyboard shortcut before activating them 3. Add a Power User Mode Consider introducing a dedicated Power User Mode featuring: No suggested prompts Reduced UI clutter Compact layouts Fewer interruptions while typing Advanced customization options A productivity-focused experience 4. Compact Conversation View Long technical conversations can become difficult to navigate due to excessive spacing and scrolling. Please provide: A compact view option Reduced vertical whitespace More conversation content visible on screen 5. Conversation Search Many conversations contain valuable information that users want to revisit later. Please add the ability to: Search within a conversation Search code snippets and formulas Search by date or topic Quickly jump to matching results 6. Pin Important Messages Allow users to pin key answers, code snippets, formulas, decisions, or reference messages within a conversation so they can be easily found later. 7. Enhanced Copy Experience For technical users working with Power Apps, Power Automate, SQL, PowerShell, and other technologies: One-click copy for all code and formulas Preserve formatting during copy operations Support copying multiple related blocks together 8. User-Defined Response Profiles Allow users to create and switch between response styles such as: Technical Troubleshooting Power User Learning Mode Executive Summary Architecture Review This would reduce the need to repeatedly explain personal preferences. 9. Memory Transparency and Management Allow users to: View all stored memories and preferences Edit or delete individual memory items Temporarily disable specific memories Understand which memories are influencing responses This would improve transparency and trust. Summary Copilot is evolving from a simple chat tool into a professional productivity platform. Providing greater control over the interface, shortcuts, suggestions, memory, and conversation management would allow experienced users to tailor the experience to their workflow while preserving the current experience for those who prefer more guidance. Thank you for considering these improvements.Can I set up an automated employee recognition system with copilot?
My manager asked me to look into whether Copilot can help us build some kind of employee recognition program inside Teams. It could include anniversary and birthday recognitions, or even recognitions sent based on achievements and milestones? Can I connect it with Praise? Or set up automations with power automate? Am I overengineering something I can pawn of to something third party?
Can Copilot generate meaningful insights from 1:1 meeting history?
Someone on our leadership team wants to know if Copilot can analyze patterns across a manager's 1:1 meetings. Like, if an employee has been bringing up workload concerns for 3 months straight, can Copilot flag that? Right now all our 1:1 notes are spread across different Loop pages and OneNote sections. Even if we consolidated them, im not sure Copilot can do trend analysis on that kind of unstructured data. Anyone tried this?
Can Copilot help summarize employee feedback and review data?
My boss asked me to look into whether Copilot can help managers prep for performance reviews. Like, instead of reading through months of feedback and notes manually, could Copilot pull together a summary of key themes from peer feedback, goal progress, and past 1:1 notes? If we keep all of these on Sharepoint, can we prompt Copilot to automatically access and summarize them? Do we need to build something custom for this or are there apps in the M365 ecosystem that already have AI built in for this kind of thing?Can Microsoft Frontier Program Copilot Cowork Agent Delegate Tasks to Other Copilot Agents?
Hi everyone, I'm currently exploring the capabilities of Copilot Cowork that is available through the Microsoft Frontier Program, and I'm trying to understand whether a multi-agent orchestration pattern is officially supported. My Use Case I want users to interact with only a single, central Copilot Cowork agent. For example: User asks the Cowork agent to create or update a Jira ticket. Instead of Cowork handling the Jira operation directly, it delegates or hands off the task to a dedicated Jira Copilot Agent. The Jira agent performs the required actions and returns the result. The Cowork agent then presents the final response back to the user. Similarly, I would like to have specialized agents for: Jira ServiceNow Knowledge Management HR Operations Internal IT Support Other business systems The goal is to have Cowork act as an intelligent orchestrator/router while specialized agents handle domain-specific operations. Questions Is agent-to-agent delegation or handoff officially supported in Copilot Cowork (Frontier Program)? Can Cowork directly invoke another Copilot Studio agent? Is there any built-in multi-agent orchestration framework available today? If this is supported, what is the recommended architecture and implementation process? If it is not currently supported, what workarounds are people using? Power Automate? Agent as a tool/action? Custom APIs? Azure AI Foundry / Azure AI Agent Service? Other approaches? I'm specifically looking for guidance from anyone who has worked with Copilot Cowork in the Frontier Program, since the documentation and public examples seem to focus mostly on standalone agents. Any insights, architecture diagrams, documentation links, or real-world experiences would be greatly appreciated. Thanks!
Succession Planning in Microsoft 365?
Hi everyone. I'm looking to implement some of our core HR practices like performance management, talent reviews, natively inside our Microsoft 365. The one that challenges me the most currently is succession planning. Do you think I can set something up where managers can evaluate succession candidates through Copilot, build succession plans on SharePoint, etc? Does anyone have any experience with this? I am also open to suggestions for any succession planning apps or software if doing it manually could be too complicated. However in that case, it would have to be a pretty native integration.Architectural: Copilot should detect missing source data, avoid inference, and surface uncertainty.
Users expect the AI to detect when it lacks source data, avoid inference, surface uncertainty, and adapt to environmental constraints like character normalisation. These behaviours materially improve trust and usability. I’ve been working with Copilot on structured data extraction from a PDF and noticed a behaviour that seems like an architectural gap rather than a simple bug. Copilot attempted to infer table structure from a template when it did not have access to the actual source data. It produced confident but incorrect output instead of signalling that the source was unavailable. Additionally, Copilot attempted to output TAB‑delimited data, but the MS365 environment silently normalised TABs to spaces, and Copilot did not detect or adapt to this constraint. Recommendation: Copilot should proactively: detect when it lacks source data avoid inference when accuracy is expected surface uncertainty explicitly detect environment‑specific formatting limitations (e.g., TAB stripping) adapt output formats automatically These behaviours would materially improve trust, reliability, and user experience.
