{"id":4654,"date":"2026-10-20T17:00:00","date_gmt":"2026-10-20T15:00:00","guid":{"rendered":"https:\/\/digital4productivity.de\/meeting-agent-how-to-turn-your-meetings-into-lasting-knowledge"},"modified":"2026-10-20T17:00:00","modified_gmt":"2026-10-20T15:00:00","slug":"meeting-agent-how-to-turn-your-meetings-into-lasting-knowledge","status":"publish","type":"post","link":"https:\/\/digital4productivity.de\/en\/meeting-agent-how-to-turn-your-meetings-into-lasting-knowledge","title":{"rendered":"Meeting Agent: How to Turn Your Meetings into Lasting Knowledge"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Key Takeaways<\/h2>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>The chaos starts after the meeting:<\/strong> Minutes are missing, tasks get lost, and the knowledge in roughly 9,000 words of raw text per meeting disappears unused.<\/li><li><strong>Transcript in, minutes out:<\/strong> A custom agent in Microsoft Copilot Studio condenses transcripts into structured minutes and, after approval, creates a task in Planner.<\/li><li><strong>Markdown is the knowledge base:<\/strong> Every set of minutes is also saved as a lean Markdown file in SharePoint, because AI reads this format particularly well.<\/li><li><strong>Guardrails are mandatory:<\/strong> A human approves, unclear points are flagged, and instructions inside the transcript are ignored.<\/li><li><strong>Focused knowledge instead of a haystack:<\/strong> A second agent searches only the minutes folder instead of every email and document.<\/li><li><strong>Built with Claude and MCP:<\/strong> The flows were created with Claude via MCP servers, much faster than clicking through the browser.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Introduction<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Does this sound familiar? You attend many meetings and take notes in a notebook or in Teams. Three weeks later you want to know what you agreed with a customer, and you cannot find it. The minutes are missing, the tasks have quietly disappeared, and the knowledge is gone.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">I wanted to solve exactly this problem for myself. So I built a meeting agent: transcript in, structured minutes and tasks out. The building blocks are Microsoft Copilot Studio, Power Automate, SharePoint and Planner. A second agent then turns the archive of minutes into a searchable memory. Behind the scenes, Claude and MCP servers helped me build it, but they do not run in production.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why Knowledge Gets Lost After Meetings<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The transcripts often already exist, because Teams can record and transcribe on request. The problem is that nobody processes them. A single meeting produces around 9,000 words of raw text, and nobody reads that voluntarily afterwards.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Then there are the conversations that never happen in Teams: phone calls, face-to-face talks, or meetings organised by someone else where I am not allowed to record. For those I use a small AI recording device with its own software, which also delivers a transcript. And even when everything sits in Teams, one question remains: where should it all go?<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Transcript In, Minutes and Tasks Out<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The solution is easy to describe. I paste a transcript into the agent, and it creates minutes that land in a fixed folder. When I approve the result, a task is automatically created in my Planner.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The minutes are produced twice: once as a readable document and once as a Markdown file. Markdown is a plain text format that AI can read far better than most other formats. When I later query my archive, the agent first looks only at these files and nothing else.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Every set of minutes follows the same structure: key data, a management summary with the three to five most important statements, discussion points, decisions, to-dos and open questions. A confidentiality level is added, and the complete original transcript stays unchanged in the file.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Two Building Blocks and Clear Guardrails<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Technically there are two main components. The minutes agent is the brain, built in Copilot Studio. Two Power Automate flows support it: one saves the Markdown file in a SharePoint folder, the other creates a task in the Meetings bucket of my Planner, but only if saving the file worked first.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The guardrails matter as much as the technology. The human decides: nothing is saved before I approve it. Uncertain items are reviewed and do not reach Planner unchecked. Only what is actually in the transcript counts, and unclear points are flagged. Most importantly, instructions contained in the transcript are ignored. Anyone building agents has to think about prompt injection from the start.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The result is one lean Markdown file per meeting, without layout or clutter, always built the same way. The AI finds its way around immediately, and people can read the files too.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Focused Knowledge Instead of a Haystack<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">On top of this archive sits a second agent. I can ask it what we agreed with a specific customer, which project tasks are still open, or when we last discussed a certain topic.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Why not simply use the standard Copilot or the Researcher? Because the standard Copilot searches through everything: emails, chats, documents. The signal-to-noise ratio is poor. My agent starts with the condensed minutes instead. If I need more, I can tell it to include other sources in a second step. Limiting AI to relevant information is one of the most effective levers for better answers.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Building with Claude and MCP Servers Instead of Clicking<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In theory, building workflows in Microsoft is simple: you tell Copilot what you want. In practice, that works only moderately well. I also tried browser automation, first with Perplexity's Comet browser and later with the Claude extension in Chrome. It is slow, because it constantly takes screenshots, and it burns a huge number of tokens.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">MCP servers work much better. MCP stands for Model Context Protocol, and it lets Claude access Copilot Studio and Power Automate directly. I describe in plain language what I want, the system builds it and handles error correction, and when questions come up, Claude checks the documentation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Errors Are Part of the Process<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Was the first result perfect? No. Day and month were swapped, so 5 October became 10 May. The agent had also shortened the transcript on its own initiative. We fixed both until everything ran cleanly.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A second pitfall: the new file was visible in the browser but not yet on my computer, because OneDrive had not finished synchronising. The AI itself accesses the files in SharePoint immediately. In general, Copilot automations only become truly productive when files live in SharePoint rather than on network drives.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A Checklist for Your Own Meeting Agent<\/h2>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Transcribe your meetings:<\/strong> Transcription is already included in Teams, even without a paid Copilot licence.<\/li><li><strong>Define a fixed SharePoint folder:<\/strong> All minutes go into one place.<\/li><li><strong>Set up a Planner board:<\/strong> Create a Meetings bucket for the generated tasks.<\/li><li><strong>Build the agent with an approval step:<\/strong> Human in the loop is a good idea.<\/li><li><strong>Add a query agent:<\/strong> Point a Copilot agent at the minutes folder so you can question your archive.<\/li><\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">Mentioned Tools &amp; Resources<\/h2>\n\n\n\n<ul class=\"wp-block-list\"><li><strong>Microsoft Copilot Studio:<\/strong> Toolkit for custom Copilot agents, used here for the minutes agent.<\/li><li><strong>Power Automate:<\/strong> Microsoft's workflow service; two flows save the minutes and create the Planner task.<\/li><li><strong>Microsoft Planner:<\/strong> Task management in Microsoft 365 with a Meetings bucket.<\/li><li><strong>SharePoint:<\/strong> Storage for the minutes archive and the basis for productive Copilot automations.<\/li><li><strong>Claude:<\/strong> AI assistant by Anthropic that helped build the flows via MCP servers.<\/li><li><strong>Model Context Protocol (MCP):<\/strong> Open standard that lets AI assistants access systems directly.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Frequently Asked Questions<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">What exactly does a meeting agent do?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">It turns a meeting transcript into structured minutes with a management summary, decisions, tasks and open questions. After approval it saves them as a Markdown file in SharePoint and creates a task in Planner.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Why are the minutes stored as Markdown?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Markdown is a lean text format that AI systems read very well. With one consistently structured file per meeting, an agent finds its way around immediately, and people can still read the files.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Why is the standard Microsoft Copilot not enough?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">It searches emails, chats and documents at once, so relevant agreements get lost in the noise. A dedicated agent on a focused minutes folder gives more precise answers.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Which guardrails does a meeting agent need?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A human approves before anything is saved, uncertain items are reviewed, unclear passages are flagged, and the agent ignores instructions in the transcript to prevent prompt injection.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Do I need a paid Copilot licence for transcription?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">No. Meeting transcription is already included in Microsoft Teams. For calls or meetings you cannot record, an AI recording device can help.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">What is the fastest way to build such agents and flows?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Describing the solution in plain language and letting an assistant like Claude build it via MCP servers works far better than clicking through interfaces or letting an AI control the browser.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Your meetings are your knowledge. The only question is whether you use it. With a minutes agent, two Power Automate flows, a Markdown archive in SharePoint and a query agent, raw transcripts become a searchable memory with clear tasks in Planner.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Start pragmatically: switch on Teams transcription, create a minutes folder and a Planner board, and set up your first agent with an approval step. Build guardrails in from day one.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Key Takeaways The chaos starts after the meeting: Minutes are missing, tasks get lost, and the knowledge in roughly 9,000 words of raw text per meeting disappears unused. Transcript in, minutes out: A custom agent in Microsoft Copilot Studio condenses transcripts into structured minutes and, after approval, creates a task in Planner. Markdown is the [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":4648,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"wpai_generated_summary":"","footnotes":"","tve_updated_post":"","tve_custom_css":"","tve_user_custom_css":"","tve_globals":{},"tcb2_ready":0,"tcb_editor_enabled":0,"tve_landing_page":"","_tve_header":"","_tve_footer":""},"categories":[47,48,35],"tags":[],"class_list":["post-4654","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-microsoft-365-en","category-tj-technology-tuesday"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Meeting Agent: Turning Meetings into Usable Knowledge<\/title>\n<meta name=\"description\" content=\"Thorsten Jekel shows how a meeting agent built in Copilot Studio turns transcripts into structured 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