Microsoft published Dataverse Is Your Agent Data Platform: Here’s What’s New on May 5. I already wrote about the positioning shift, but the dataverse agent data platform new features in this post are the part I actually want to wire up this week. Knowledge sources you can attach to an agent. Agent feedback captured and stored back in Dataverse. Tighter coupling between business skills and the data model. That last bit is the one that changes my build order.
What it actually does
Three things stand out from the post.
First, knowledge sources on Dataverse. You can now attach SharePoint sites, websites, files, and Dataverse tables as knowledge an agent can reason over, governed at the Dataverse level rather than configured per agent. The point is that knowledge becomes a managed artifact in the data platform, not a per-agent setting buried in Copilot Studio.
Second, agent feedback stored in Dataverse. Thumbs up, thumbs down, and the conversation context land as rows you can query. That means feedback is not trapped in a separate analytics surface. You can write a flow on it. You can build a Power BI report on it. You can route a thumbs-down with a specific topic tag to the skill owner.
Third, business skills tied to the data model. The business skills I wrote about when they shipped now sit closer to the tables they operate on. Skill ownership, policy versioning, and the data the skill reads from are governed in one place.
For the official surface area, the Microsoft Learn docs are the right starting point once you have read the announcement.
Why it matters
I have built enough Copilot Studio agents to know where the pain actually sits, and it is never the model. It is the loop between what the agent does, what users think of what the agent did, and the policy owner who has to fix the thing that went wrong. That loop has been broken on Power Platform for a year.
Feedback used to live in conversation transcripts you had to export. Knowledge used to be attached per agent, which meant the same SharePoint site got wired up four different ways by four different makers. Business logic lived in a 4000-token system prompt or a hardcoded Power Automate flow nobody could find six months later.
Putting all three in Dataverse closes the loop. Feedback is a table. Knowledge is a managed artifact. Skills are versioned records with owners. You can finally write the query that says “show me every thumbs-down on the leave policy topic in the last 30 days, grouped by the skill that was invoked.” That query was not possible before. Now it is a view.
The thing I am cautious about is the same thing I flagged with business skills. Sprawl. If five teams attach overlapping knowledge sources to overlapping skills with no naming convention, the agent will misroute silently and the feedback table will just tell you users are unhappy without telling you why. Governance has to come before deployment, not as a month-six cleanup. The multi-agent orchestration patterns that are now GA in Copilot Studio make this even more important to get right before you scale.
What I would do with it this week
I have a small internal agent that answers process questions. The plan for the next few evenings looks like this.
Move knowledge out of the agent and into Dataverse. Right now the agent has three SharePoint sources wired up directly. I want one knowledge source registered in Dataverse, owned by the process owner, that any future agent on the same domain can reuse. That is the silo fix.
Turn on feedback capture and build the report. Thumbs-down without a report is just noise. I want a Power BI page that shows feedback rate per topic, with a drill-through to the conversation. If I cannot see which skill was invoked when the user said no, I cannot improve anything.
Pick one skill and version it properly. I am going to take the leave policy skill, rewrite it as a Dataverse business skill with an owner who is not me, and document the handoff. If the policy changes, the policy owner edits the skill. I do not get a ticket. That is the architectural shift I keep talking about, and it only works if I actually do it on something real. The error handling patterns that hold up in production become especially relevant once feedback loops are writing rows back into Dataverse and triggering flows downstream.
None of this needs a new model. It needs the data platform to do its job, and it finally can.
The interesting question now is what the second wave of agents looks like once knowledge and feedback stop being per-agent problems.
This post was inspired by Dataverse Is Your Agent Data Platform: Here’s What’s New via Microsoft Power Platform Blog.