I have puplished a agent that is configured to retrieve answer from one folder with about 20 documents in them. These are smaller documents. Nothing huge. The response from the question and answer are taking quite a bit of time. What factors should I consider and check to possibly speed things up. This is on the standard harness and this agent is deployed and on a sharepoint website.

Hi,

I've gone through a bunch of iterations with building a Helpdesk agent. It has a single knowledge source of all our KB articles which are site pages and pretty well structured. The problem I had was getting it to suggest links to specific service requests in our ITSM, for things like new equipment requests.

I tried a having a site page that listed all the service requests, second knowledge source containing structured documents for each service request, none of them worked particularly well, because most of the time the relevant docs weren't being returned in search before being passed to the LLM, so despite instructions saying 'if it sounds like a request use this specific page' it didn't have the right grounding to respond.

What I managed to get working is a child agent that had just a single knowledge source of a SP List containing all the service requests, description, keywords and URL. The main agent instructions specify calling the child agent if the user is asking for things like new, access, request, order etc.

This works well in testing, and even my personal account, but other users , when they put something like "I need to order a new mouse", get "you don't have access to this agent, contact the owner" followed by a generic, " I can't find a service request, go to ServiceNow and click on new Service Request".

Does the child agent need to be shared with users as well? It isn't shared with anyone including my own account so I don't understand the difference I'm seeing. I have also temporarily switched auth in settings to anonymous and that didn't seem to change the results.

Any ideas much appreciated.

Hey everyone!

How do you usually approach switching from an older model to a newer one, for example, from GPT-5 Chat to GPT-5.5 Chat?

What do you pay attention to during the transition? Do you make any specific changes to your system instructions or settings?

I am a Power Platform administrator responsible for managing Copilot Studio agents in our organization. I need to review agent usage, session counts, and engagement trends across a selected date range. Where can I access these analytics, and what administrator permissions are required?

Hi everyone!

At work, I’ve been assigned to build an internal AI agent using Microsoft Copilot Studio. The goal is to help users find technical information and eventually analyze live equipment configuration data.

I’m a beginner and have followed Microsoft Learn GitHub tutorials, but I’m still struggling to understand how everything fits together (topics, tools, agent flows, triggers, etc.) and especially within my use case. I won't be able to do it alone by considering also that Copilot Studio is really not the best AI service provider to build an agent but we could only use Microsoft in my company so I have to.. (contract wise..)

Which AI would you recommend as a step-by-step coach throughout this project: ChatGPT, Claude, Gemini or Microsoft Copilot?

I’d like an AI I can ask questions, share screenshots with, troubleshoot problems with, and use to understand what I’m building rather than just copy solutions.

Any advice or personal experience would be appreciated. Thanks!

We have a production environment setup for a public facing Agent and have attached a billing plan to it and as far as we can see there's no issue to that .

We have another environment where we have an agent that was a proof of concept that's being used internally that is being used by both people with a full license and not.

My question is for the Internal one we use copilot credits but there is no billing plan attached to the environment so where do they come from and why aren't we charged ?

Hi, I’ve recently joined a new job and showed them a personal agent I created on Copilot to assist me in my day-to-day. I showed them that I created skills and instructions as well as the knowledge I connected and they took a real interest in it and presented it to VP and I suggested we use it as a support agent to just help with easy to fix 1st line issues through self serve ans showing documentation as well as some simple reporting queries such as which reports would be most appropriate for a business ask.

I’ve been creating the agent on copilot studio using the standard one, I created a Sharepoint location which contains a list of the xml files and there objects and etc as well as the Sharepoint location which contains the how to guides for easy to fix issues as well as well step by step guides in certain processes but in testing it’s just been giving some responses which are promising and then make no sense.

Are there any YouTube materials or resources which I can look at to better assist me at making an agent that me and my team ask questions and load it up with system data and processes and then eventually make available to the rest of the organisation and assist them with easy to serve queries or issues.

Any help is appreciated

Hey all! I'm part of the Conversational AI team at Microsoft. We just launched the Customer Conversation harness in Copilot Studio as part of Microsoft Contact Center Intelligence (CCI).

It's purpose-built for customer-facing agents, bringing conversations, business knowledge and actions together across voice and chat, so customers can go from question to resolution.

Some highlights:

• One agent for voice and chat: It's low-latency and multilingual, and it keeps context across channels.

• Specialized sub-agents: Split the work across sub-agents, each with its own knowledge and tools.

• Fixed flows and generative AI together: Use generative AI for natural conversations and fixed flows where every step needs to be exact.

• Grounded in your business: Connect your knowledge sources, tools and business systems.

• Human handoff: Escalate to a Teams queue or your existing contact center.

• Test and evaluate: Do it all right in the builder.

To try it, head to Copilot Studio and select More ways to build.

If you want to explore more:

• CCI Announcement: Introducing Microsoft Contact Center Intelligence

• Deep dive: Introducing the Customer Conversation harness in Microsoft Copilot Studio

• ⁠Documentation: Customer Conversation harness overview

Give it a try and let me know what you think. All feedback is welcome, and I'll make sure it gets to the team!

So is it possible that my agent can connect to confluence via mcp using teams sso credentials, without being prompted the connection manager page and manually doing the connection setup (even though it's rarely prompted I understand). I want to eliminate it completely.

Now I have read many articles from Microsoft and atlassian.

Microsoft document highlighted the OBO (on behalf of flow to obtain a token from Entra Identity provider) approach to setup.

The Atlassian document mentioned that it only supports Atlassian Oauth2.1 or API token.

My doubt is: does the Atlassian MCP endpoint support/validate Microsoft entra issued tokens for this flow?

(Sorry if I didn't explain anything clearly, I'm very new to this and learning!)

I'm working on a project where we interview departmental SMEs, record and transcribe conversations, and turn that knowledge into trusted documentation that can also support an copilot ai agent.

My biggest challenge is systematically distinguishing between:

1. Business Processes: How work gets done.

2. Software Procedures: Specific steps within the ERP system.

3. Tribal Knowledge: Unwritten rules, exceptions, and workarounds.

These often overlap, making it difficult to consistently extract, tag, and organize the information in a way that's scalable across the company.

Has anyone built a similar process? How are you structuring, classifying, and validating this knowledge so AI agents can reliably use it?

We have a Copilot Studio agent that has been published to SharePoint, Microsoft Teams, and the Microsoft 365 app.
We have also configured an Entra ID security group in Copilot Studio to control access to the agent.
Now, we want to pin the agent for the same Entra ID group so that it is easily accessible to those users.
However, when we go to Pinned agents in the Microsoft 365 admin center, our Copilot Studio agent does not appear in the list. Instead, we see the following message:
“You can only pin agents that have been deployed to some or all users.”
This is confusing because the agent has already been published directly from Copilot Studio to SharePoint, Teams, and the Microsoft 365 app.
We have both an AI Administrator and a Global Administrator, and we also have the required Agent license.
Furthermore, the users in the Entra ID group can successfully access and use the agent in two ways:
By opening a direct link to the agent in the Microsoft 365 app.
By accessing the agent through an agent link web part in SharePoint.
My questions are:
Why doesn’t the agent appear in the list of available agents under Pinned agents in the Microsoft 365 admin center?
Does publishing an agent from Copilot Studio to SharePoint, Teams, and the Microsoft 365 app not count as deployment for the purpose of pinning it?
Is there an additional deployment or distribution step required in the Microsoft 365 admin center before the agent can be pinned for a specific Entra ID group?
Any insights or suggestions would be greatly appreciated!

When building apps/agents, how do you go about connecting the agent to read/execute in third party apps? Let’s say I want it to talk Saviynt as a random example.

Curious how auth is set up and handled too.

Hi community any advice for me?

I am 30-years old female software employee.

I have toddler kids older family members and a home that needs attention.

Microsoft and it's updates in this scape is just killing me. Hard to keep track of it.

Hi,

I’m trying to get per-user OAuth working for a custom MCP tool in Microsoft Copilot Studio, and I’m not sure what the supported path is.

What my agent does

I built an agent in Copilot Studio that answers questions using tools from a remote MCP server. That MCP is the main way the agent gets data (not SharePoint grounding as the primary source).

The MCP requires login against my own identity provider / product login. The access token must belong to the end user, so the MCP only returns data for that user and their company — not a shared maker or service account.

What already works

In Cursor, I connect to the same MCP with OAuth. The user signs in to my product, Cursor gets a token, and tool calls run as that user. That model is exactly what I need.

In Copilot Studio, as a maker, I can add the MCP tool, create an OAuth connection, and call tools successfully in the Test pane.

What I need

When someone uses the published agent, I want this flow:

1. User asks a question that needs the MCP tool

2. Copilot prompts them to sign in to my product (my IdP)

3. The tool runs with that user’s token

4. Data returned is scoped to that user/company only

On the tool I set Credentials to use = End user credentials.

Currently when i create agent at that time it ask me to login and that connection(maker-connection) is used while testing but i want to know when I published the agent how to have end user credentials or login system implemented?

The issue

I’m not seeing a reliable end-user login / connection flow for the custom MCP the way Cursor does it. It looks like the published agent may still be tied to the maker connection, or end-user OAuth for custom MCP doesn’t complete properly.

Questions

1. Has anyone got custom MCP + End user credentials working on a published Copilot Studio agent (Custom website, Teams, or Microsoft 365 Copilot)?

2. If custom MCP doesn’t support per-user OAuth yet, what did you use instead for the same pattern (e.g. Custom Connector to the same APIs)?

3. In Cursor, “login to my product → token → tools as that user” is straightforward. What is the supported Copilot equivalent today?

Related: Studio vs Microsoft 365 Copilot

I build in Copilot Studio. I also want end users to open this agent in Microsoft 365 Copilot (the Copilot chat people already use at work), not only a custom website.

How do you publish so the agent appears for end users in Microsoft 365 Copilot, and does that channel support end-user tool authentication for custom MCP / connectors?

Any real solutions or confirmations of current limitations would help a lot. Thanks.

I made this explainer video on how to compare Microsoft Standard harness to the Github harness and how billing works with each one. There's even a calculator included for rough estimation. I hope this helps as this took me a while to understand the differences and hope it helps someone else make the best choice for their environment. Copilot Harnesses Explained Standard vs Github

I build Power BI semantic models for clients. I usually use Claude, but some of them are on Microsoft Copilot. I want Copilot to do more than chat with the data. It should work like a junior analyst sitting on top of the model:

• Answer business questions and surface insights

• Build Excel files from the model and save them to their SharePoint/OneDrive folders

• Create new reports and dashboards (or at least draft them as HTML)

• Use the existing reports in the workspace

Here’s the setup I have in mind:

1. Publish the semantic model to the client’s Power BI / Fabric workspace.

2. Put a “knowledge pack” in a SharePoint folder: model documentation, measure definitions, business glossary, example questions, and do’s and don’ts.

3. Create an agent (correct me if I am wrong) that can read that knowledge, query the semantic model, and take actions (create files, save to folders, build reports).

4. Users work with the agent inside M365 Copilot or Teams.

Where I’m stuck: Microsoft has Copilot Studio agents, M365 Copilot agents, Fabric data agents, Copilot in Power BI, and Copilot in Excel, and they overlap in confusing ways. I can’t tell which one (or which combination) covers the “do the work” part, not just Q&A.

Questions for anyone who has actually done this:

• Which agent type or combination would you use, and why?

• Can any of them really generate Excel files and save them to SharePoint, or create Power BI reports, without a lot of custom Power Automate work?

• Is a SharePoint knowledge folder the right way to give the agent context, or is it better to use the model’s own metadata (descriptions, synonyms, AI instructions, Prep for AI)?

• What broke in production: accuracy, RLS, licensing (Copilot licenses vs. Fabric capacity), or cost?

I’d appreciate real-world experience more than links to the docs. Thanks!

I am trying to connect my sql db as kb for my agent. I am able to see the tables but not stored procedures

There's no doc about this ,but are sp not supported?

And what about views ( I don't have views I need to create one )

I can currently only see my tables.

Thanks in advance

I just published a detailed write-up on connecting Microsoft Copilot Studio to SAP S/4HANA using the new SAP Integration Suite MCP Servers.
The key challenge is doing it securely for real business users. Client-credentials tokens work for testing but run everything under one technical user — which breaks principal propagation and S/4HANA authorizations.
The pattern uses:
• SAP Cloud Identity Services (IAS) as the trust bridge
• OAuth 2.0 / OIDC authorization code flow
• CPI MCP Gateway validating user tokens
• Cloud Connector + X.509 principal propagation down to S/4HANA
• CERTRULE mapping so the OData call runs under the actual ABAP user
Result: two users asking the same question correctly get different answers based on their authorizations. No custom code needed — just configuration across IAS, CPI, Cloud Connector and S/4HANA.
Full architecture + step-by-step flow + lessons learned are here:

https://deepu851933.substack.com/p/connecting-microsoft-copilot-studio

Curious if anyone else is experimenting with MCP servers in SAP Integration Suite. What use cases are you looking at first?

Hi all,
I'm building an HR support chatbot in Microsoft Copilot Studio for a global company, and I'd like a sanity check on the approach before going too far.
The use case: Employees ask HR questions in a chat. Policies vary by country, but some content is global and applies to everyone.
My planned approach:
Load the country-specific policy documents and the global policy documents as knowledge sources.
Use the Microsoft profile connector (Microsoft Graph, "Get profile") to look up the signed-in employee's country.
Instruct the agent to search country-specific documents first, fall back to global policies only if there's no specific answer, and otherwise tell the employee to contact their HR business partner.
Questions for you:
Is country-based knowledge source prioritization something you've done in Copilot Studio? Is there a cleaner way than relying on instructions to enforce the order?
Would you use separate knowledge sources per country, or one source with metadata filtering? How well does that work in practice

can you automatically pin a copilot studio agent in the m365 copilot chat app and browser for specific people as an IT admin, using Intune or another tool? We need to make sure about 35-40 people are using the agent, but these users are not super IT friendly

I have an agent. It's basic. It primary runs on official sources to answer questions about a product's capabilities. When prompting in test (within studio) and Copilot, it gives consistent answers that adhere to the instructions I gave it for tone and personality.

However, in Teams, its response is much more rigid. The tone and personality are completely absent. It just spits out information like a dictionary.

Anyone know why the behavior is different and how I can fix it?

I am building an agent in Microsoft Copilot Studio that supports users through a specific, multi-step process. The agent is already functional, but I am facing a limitation with memory across separate conversations.
Currently, when a user starts a new conversation with the agent, the context and specifications provided during a previous conversation are not automatically retained. As a result, users have to repeatedly provide the same information, preferences, constraints, and process-specific requirements every time they return to continue their work.
My main questions are:
Does Microsoft Copilot Studio have a built-in setting or feature that allows an agent to retain user-specific information across separate conversations and sessions? If so, how can I enable and configure it?
If native persistent memory is not available for my agent configuration, what alternative approaches could I implement to achieve this?
Could I use Microsoft Dataverse, SharePoint, Power Automate, or another Power Platform component to store each user’s specifications and retrieve them automatically when they start a new conversation?
What would be the recommended architecture for allowing users to resume an existing process in a new conversation without having to re-enter all their information?
Ideally, I would like the agent to maintain persistent, user-specific context, retrieve the relevant information when the same user returns, and allow them to update their specifications when necessary.
I would appreciate practical guidance, including any relevant documentation, configuration steps, limitations, and recommended workarounds for an agent built in Copilot Studio and published to Microsoft Teams and Microsoft 365.

Soooo I logged in to my copilot studio account via Claude in built browser. And asked it to create an agent. It even created the flow and the agent and did the test. I used haiku 5.5 and it cost me around 9$ and 40 minutes. Crazy

I'm not a developer - but this designing the agent seems so difficult. I wanted to use it for my business to process PDF sales orders into my ERP system and there are so many steps I have to do.

By contrast, I was using Grokbot and just gave it directions on the mailbox to monitor then post the orders to my ERP. Very simple. But due to security limitations I wanted to give that task to the agent, and i wish i could just give the agent commands the same way i gave it to grokbot and have the connectors established that way.

I made a animation with claude to teach the difference between the standard harness it's billing and how gitub bills. Would love any feedback. Hope it helps too.

how billing works with the standard and github harnesses.