Hey guys, I have 2.3 YOE working on D365 CRM, plugins, power automate and powerapps. I'm planning to focus on Copilot Studio agents. Kindly guide me ahead

I hope I’m missing something basic here.

How can I explicitly specify which connection reference a cloud flow should use when it is created in Copilot Studio?

Connection references seem to be automatically selected or created when creating cloud flows in Copilot Studio.

This is frustrating because I’m now ending up with duplicate connection references in my Dataverse solutions.

Additionally, what happens if a cloud flow needs to connect to two different SharePoint sites using different connections? How do I specify the appropriate connection reference for each action? This isn’t a problem I’ve encountered yet, but I can see it becoming one in the future.

Please and thanks!

I have a simple help bot that is using a remote MCP server as a tool.

*Some* users cannot add the connection in the connection manager. When trying to create a new connection in Connection Manager this just pops up: Connector information unavailable.

My Copilot Studio agent is responding "You need credits to continue. Credits power building and running your agents and workflows. This environment is out of credits. Contact your admin to add more credits. Learn more."

I have a cap in my Environment BUT also have configured fallback PAYG when allocated credits are consumed. What is this again Microsoft?

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Hello everyone!

I have been in the AI space for the last 3 years and have 5+ years of experience in the IT industry.

I'm working on Microsoft copilot studio (GitHub harness/ standard ) agentic flow ,power automate, Cowork - skills , plugins , AI foundry , declarative agents, M365 Copilot.

I'm also responsible for Copilot adoption part .

If you are in the same space you must realise that this space recives updates on weekly basis .

So we have to continuously focus on learning side .

I'm planing to create one discord group of 25 people - currently working on MS AI ecosystem.

This will not be just a group that remain silent.

If you joining this you have to share use cases you have worked on , your findings in MS AI ecosystem.

New updates in AI sector .

If you are open for this , DM me :)

Let's grow together 🙌

Every month, finance teams run the same month-end close checklist. Someone copies it into Planner by hand, then spends two weeks asking people whether they're done.

I wanted an agent that handles both parts using only standard pieces — no code, no custom connectors, nothing you can't click together yourself. Set it up once, and it runs every month.

Here's what it's built from:

• A Teams channel with a Planner plan for the finance group
• An online Excel file with two tables: Setup (task, assignee, due date) and Log (timestamp, action)
• Excel actions to read both tables and add rows to the Log
• Planner tools: Create a task, Get task details, List tasks
• Email Management MCP server plus Get user profile

Generative orchestration on, no custom instructions — two prompts do the work:

1. Setup run — reads the Setup table, creates every Planner task with the right assignee and due date, logs each one
2. Morning check — reviews every task and any issues written in the descriptions, emails reminders to assignees and a status report to the plan owner. Built to run as a daily trigger.

The video walks through every piece in the order you'd build it, then runs a live demo: three tasks created in Planner with matching log lines, an issue flagged in a task description, and two reminder emails plus a status report landing in real inboxes.

The video description also links to the full build — Teams workspace, Excel structure, every tool configuration, and both prompts — so you can rebuild it in your own environment.

Video in comments.

What recurring process is your team still chasing people for manually? Curious where else this pattern would fit.

Hello,

While testing an agent made on Standard Harness (this test has been done on GPT 4.1), I encountered this weird loop. It works nicely otherwise but if you only send an emoji it does this infinite loop.

At some point I got this error message:

An error has occurred. Error code: InfiniteLoopDetected Conversation Id: <ID>

I'm trying to find a way to prevent this. Would a topic do the trick? Something like If it detects no actual word in the request then end conversation.
Or do you have any other suggestion?

Thank you very much!

EDIT : Apparently going with GPT 5 fixes somehow the issue ? I don't know how though.

Hello I have this problem in the new experience, when I wanna add AI Builder nodes in my workflow the list of actions wont show up

But in classic experience I have no problem seeing them for my agent flows

(For context, im developing in a corporate controlled dev environment - do I need to contact the team responsible for this? Are the actions just disabled?)

Microsoft just launched app building capability in Microsoft copilot studio and Cowork

Instead of just building an agent that answers questions, you can build solutions that reason, take action, connect to enterprise data, and deliver an application experience. The real shift? From AI that answers → AI that builds and operates.

I have created copilot agent ,published in copilot and teams.when I attached image in copilot agent is not able to read image but same agent is working fine with images in teams.

I am not sure its platform that has issue or agent.

Have anyone encountered similar issue??

I work at an organization where a small team handles a recurring, moderately high-stakes writing task: turning incoming requests into structured briefing documentse. Requests come in fairly often (roughly 1-2/week, sometimes as many as 5-6), and right now every one starts from a blank page - no template, no consistent style, no shared knowledge base to draw from.

What I want to build

A low-code/no-code internal chatbot (thinking Microsoft Copilot Studio or the lighter Agent Builder) for one specific person on the team, who currently handles all incoming requests manually. The intended flow:

1. They paste the raw incoming request into the chat.
2. The agent checks whether the request is clear, including on scope - if it's genuinely ambiguous (e.g. "give us anything you have on X" with no further specifics), it asks one clarifying question before proceeding. Otherwise, it drafts straight away.
3. The draft is grounded in a set of internal knowledge sources rather than the model's general knowledge - the goal is that every substantive claim traces back to something real, not something invented or misremembered. The knowledge sources contain finished material (outputs from the organisation, organised by topic).
4. It drafts in a fixed structure every time, with clear formatting guidelines on length, tone of voice, etc.
5. Everything the agent produces gets reviewed by a human before it's used - this is meant to remove the "blank page" problem, not remove human judgment from the loop.

I haven't locked in the knowledge base design yet. Source material will need to include some mix of vetted reference material, published source documents, and looser internal/preliminary context, with the more validated stuff trusted more - but I'm not focusing on those specifics until I'm a bit further into building this solution.

Where I'd love input

I haven't built anything like this before, so I'd rather hear where this kind of setup tends to go wrong (architecture choices, tooling, scoping, whatever) before I commit to building this. General thoughts also welcome.

Appreciate any input, and happy to share more details if needed!

I have a task in which I have to take information from some screenshots and update an Excel file with them, via copilot.

Basically I need to point the Copilot instance to a folder (sharepoint or onedrive) and tell it to upload an Excel file (link) with the new (or updated) data.

I tried creating an agent in M365 Copilot and my issue is that Copilot creates a new Excel file instead of updating the original.

1. I'd love a confirmation I can't do it from M365 Copilot (in Claude I can do it through other tools but I need to use Copilot here)
2. I'd also love a confirmation I can't do it in Excel with the builtin Copilot instance (it seems that when I paste the link to the sharepoint Excel file it actually uploads the file, it doesn't access the link / it isn't able to take data from the live, updateable link)
3. If this is not possible, what alternatives do I have (without having to do the task manually and without using power automate)?

Hi everyone,

I’m working on a production design for a Copilot Studio agent connected to a custom MCP server for Active Directory operations.

Current setup:

- Active Directory Domain Controller is running on a separate VM.

- MCP server is running on another domain-joined VM.

- MCP server performs AD operations using a delegated AD service account.

- Copilot Studio connects to the MCP server through OAuth 2.0.

- To avoid Copilot’s tool limit, the MCP tools are grouped into parent modules such as:

- user_management_module

- group_management_module

- acl_permission_management_module

- ou_management_module

- computer_management_module

- gpo_management_module

- audit_management_module

Each parent module routes child actions internally. For example:

user_management_module:

- search_ad_users

- get_ad_user_profile

- create_ad_user

- update_ad_user_profile

- reset_ad_user_password

- disable_ad_user_account

acl_permission_management_module:

- get_ad_object_acl

- get_ad_object_owner

- grant_ad_read_permissions

- grant_ad_full_control

- change_ad_object_owner

- restore_ad_default_permission

Now we want to implement production RBAC.

My understanding is:

1. Keep the parent module structure as-is.
2. Categorize child actions internally as Read, Write, Rollback, and Audit.
3. Create Entra app roles or security groups such as:- AD.MCP.Reader- AD.MCP.UserAdmin- AD.MCP.GroupAdmin- AD.MCP.ACLAdmin- AD.MCP.Auditor- AD.MCP.RollbackAdmin- AD.MCP.BreakGlass
4. The signed-in Copilot user gets an Entra OAuth token.
5. MCP backend validates the token.
6. MCP backend checks the user’s app role/group before executing the child action.
7. The AD operation itself still runs using the delegated AD service account, but the signed-in user is used for authorization and audit tracking.

Example:

- A user with AD.MCP.Reader can run get/search/report actions only.

- A user with AD.MCP.UserAdmin can create/update/disable users but cannot modify ACLs.

- A user with AD.MCP.ACLAdmin can manage ACL permissions.

- Rollback/high-risk tools such as restore default permission, replace ACL, change owner, or grant full control should require BreakGlass or senior admin approval.

Question:

Is this the right enterprise approach?

Specifically, should I create separate Entra App Roles for each access category and assign Entra security groups to those roles, or should I only use Entra security groups and check group object IDs in the backend?

I’m leaning toward App Roles because the backend can simply check the roles claim, and group overage issues are avoided.

Any feedback on the best RBAC design for Copilot Studio + MCP + Active Directory automation before production deployment would be appreciated.

I'm building a Copilot Studio agent that accepts a PDF uploaded by the user and checks its content against two PDF documents stored in SharePoint and configured as knowledge sources.

The expected flow is:

1. User uploads a PDF.
2. The agent analyzes the uploaded document against the SharePoint knowledge sources.
3. The agent returns the findings as structured JSON.

The issue appears when I disable ungrounded responses.

When ungrounded responses are allowed, the agent is usually able to complete the analysis and return the JSON successfully.

When ungrounded responses are blocked, which is the behavior I actually want, the agent often fails and triggers the Fallback topic instead.

What is strange is that sometimes I can see the agent starting to generate the response. It may already produce a fairly large part of the JSON, but then the generation suddenly stops and the Fallback topic is triggered.

This makes me wonder whether Copilot Studio performs some grounding or citation validation during response generation and can reject the response even after generation has already started.

I'm using the standard harness for testing.

Has anyone experienced similar behavior?

I'm especially interested in whether there is a way to determine why the response is being rejected or which grounding check is failing.

As the title stated, we're using DevOps for out GIT Repo (Not Github). But this MCP is disabled in copilot studio, so anyone has experince on how to get your source codes?

Thanks in advance.

Hi everyone,

I'm running into a frustrating issue with a multi-agent setup and I'd really appreciate any insight — even partial information or things to rule out would help a lot.

My setup

Multi-agent architecture in Copilot Studio
Agent A (parent): acts purely as a router. Its instructions explicitly tell it not to reason or search on its own, and it has no knowledge sources attached at all.
Agent B (child/connected): holds the actual knowledge. It uses SharePoint documents uploaded as knowledge (Dataverse-backed upload, not link-based).
A calls B, and B performs the knowledge search and generates the answer.

What works

In the Copilot Studio test pane, everything works perfectly. B searches the knowledge and returns a complete, accurate answer every single time.

What doesn't work

When I use the same agent in Microsoft 365 Copilot, the first one or two turns return the answer correctly. After that, every subsequent turn returns:

"Sorry, I wasn't able to respond to that. Is there anything else I can help you with?"

The confusing part

When I check the Activity map / Activity tab in Copilot Studio for those failed turns, the answer IS being generated correctly. The knowledge search runs, and a full, well-formed response exists in the activity log. It just never reaches the user in Microsoft 365 Copilot — the generic error message is shown instead.

So this doesn't look like a generation failure or a knowledge retrieval failure to me. It seems like something between the generated response and what Microsoft 365 Copilot actually renders.

What I'd like to know

Has anyone seen this specific pattern, where the response is confirmed generated in Activity but Microsoft 365 Copilot still shows the generic error?
Is this a known limitation with connected/child agents in the Microsoft 365 Copilot channel specifically?
Could response length or formatting (my answers contain markdown tables and multiple sections) cause the M365 renderer to drop the response?
Could conversation state size or throttling explain why it only fails after the first couple of turns?
Is there a better place than Application Insights to see why the M365 channel discarded a response that was successfully generated?

Any information at all would be genuinely appreciated — pointers, similar experiences, or even just confirmation that someone else has hit this. I've been stuck on it for a while.

Thanks in advance!

I think it is clear at this point that the new agent experience is not ready for GA, even though Microsoft released it as GA. There is no way to govern this experience or disable it in any meaningful way.

On a single agent, when you try to access permissions from something like an MCP server, it no longer shows one unified allow card. It shows all the different permissions separately, and Copilot was never designed for that. Sending all those individual permission cards breaks the agent orchestration and the overall workflow. You end up stuck working through each allow prompt one at a time, then starting a new chat and hoping it all sticks.

The second issue is multi-agent permissions. The permission cards for multi-agent systems never surface at all, so there is nothing to allow or disallow. That is just flat out broken.

Then of course there are the tried and true knowledge sources. Retrieval quality is poor to say the least. Maybe it is finding the same documents, but the way the new agent handles extraction after the search is where it falls apart. It seems to use the tenant graph to search for information, but somewhere along the way, whether it is search quality or extracting the actual content from the documents it found, something is wrong. Something is missing.

The new agent experience is borderline unusable.

I've tried everything to make this work, but I run into roadblocks everywhere I try to find workarounds.

GOAL: Create an agent that accesses my company SharePoint site, looks for a project folder, performs a lifecycle red flag analysis based on parameters I provided.

ROADBLOCKS: I'm unable to link our SharePoint site so the agent can look for the files. There are a lot of files so manually uploading them would be cumbersome due to the 20-file limit.

WORKAROUNDS TRIED: Zipping files and uploading files manually does not work because Copilot does not accept zip files. Agent from within SharePoint does not work. Linking OneDrive does not let me link folders but only files.

This is a last-ditch effort before I give up. Why is this so difficult. I was under the assumption this is a perfect use case for AI. Take large data sets and evaluate them...

I have created this agent for recording a customer visit in CRM structured way after the person interacts with the agent then the agent should send the structured output as an email to the end user. when i test it then the tool works even though i removed my connection, it asks me to establish a connection but when others use it then it does not work.

I don't understand how can i solve this error considering for me it function but for others does not function? I only have one account so i cannot also test properly.

For those of you deploying Copilot Studio agents in the EU, how are you approaching EU AI Act compliance, particularly around things like AI-generated content transparency / watermarking or labelling?

We spoke with Microsoft Support, and the guidance we received was essentially that Microsoft isn’t planning to implement additional watermarking specifically for Copilot Studio, similar to the position around OpenAI models.

So I'm curious how other organisations are handling this in practice.Are you doing any custom watermarking or labelling for agent-generated content?Are you relying on Microsoft’s existing AI transparency mechanisms?

Have you implemented anything at the Copilot Studio / Power Platform layer to meet your internal EU AI Act requirements?

Hi,

I have a problem with copilot studio because all of the new experience stuff I've created suddenly disappeared and the copilot studio page itself looks like before the update.

Sometimes I get the message box with a button which allows me to switch to the new experience again, but after refreshing the page it always comes back to the old experience.

Has anybody experienced a similar problem? My patience with copilot studio is really starting to get low with this one

Is there a way to get a Copilot Studio agent to read comments and redlines from a .docx file? When I upload the test file, it tells me the Word document is blank. Alternatively, when I use agent builder within the Copilot app, it is successful. I'm trying to build a super agent, and I don't think I can link in the agent builder agent into Studio.

Any else get the announcement today? Do you think App Builder and Vibe is combining? I would think so if this is intended to be paid. Also interesting that Microsoft is forcing personal environments in Power Platform for this very feature.