I'm building an agent in Copilot Studio Classic that needs to search through a SharePoint list with around 2,000 records.

Since I'm limited to the Classic Experience, I've tried two approaches:

1. SharePoint Get Items

• Works, but only a limited number of records can be returned to the agent, making it difficult to reliably search the full dataset.

2. Exporting the data to a text file and using it as Knowledge

• The agent can answer questions based on the file, but the results are not always reliable.
• It seems to retrieve relevant information rather than deterministically evaluate every record matching the criteria.

My challenge is finding a way to search a large dataset and return consistent results when users ask for records matching specific criteria.

REST API was in the old experience. I can't find it anywhere in the new experience. Is this a feature that is coming back?

I am struggling with recreating an existing agent in the new orchestration. The original agent worked perfectly, but I am now rebuilding it using the new orchestration and cannot get it to behave in the same way.

The agent is designed to answer questions using knowledge sources stored on SharePoint. It answers the questions accurately, but it always seems to ask follow-up or leading questions afterwards, such as: “Would you like me to provide a general list of common steps?”

What I want is for the agent to only answer the question that has been asked and then end the conversation. It should not ask follow-up questions, offer additional information, or suggest what it could do next.

With the old orchestration, I found that adding strict rules to the instructions was enough to achieve this behaviour. However, I have recreated the agent using the new orchestration and, even with the same strict instructions, it continues to ask follow-up questions and offer additional help.

Is there a different configuration or approach in the new orchestration that I need to use to replicate the behaviour of the original agent?

Hello! I'm building an agent to act as a sort of "live database" over a government API. Basically, the government here publishes a public API with all the data on public works projects, and I wanted an agent that plugs into it and works as a search tool.

When I set it up as a custom connector, it works great for me. The problem is sharing it: when I share the agent with someone else, they hit a wall needing permissions to the custom connector itself before they can use it.

I thought switching approaches would fix it, so I rebuilt it using the "REST API" tool option instead of a traditional custom connector. It worked just as well functionally, but under the hood it still creates something that behaves like a custom connector, and I'm back to the same sharing problem.

Is there another way to plug an API into an agent that doesn't require the people I share it with to also have permissions on the underlying connector? I only need to share this with a small group, not the whole org, but I'd like it to just work for them without extra setup on their end.

Any pointers appreciated

I've recently been exploring the new GitHub Copilot harness in Microsoft Copilot Studio and comparing it with the standard harness.

I'm curious to hear from others who are already testing or working with the new experience.

Do you think Microsoft will eventually retire/deprecate the standard harness and move Copilot Studio completely toward the GitHub Copilot harness?

1. Or do you think both will continue to coexist because they serve different use cases — for example, standard harness for more predictable/rule-based agents and GitHub Copilot harness for more autonomous, reasoning-heavy and multi-step agents?
2. For organizations that already have production agents built using topics, flows, connectors and existing Copilot Studio capabilities, how are you thinking about the long-term architecture? Are you continuing with standard harness or starting to design new agents around the GitHub Copilot harness?
3. Has anyone seen any official Microsoft communication, roadmap item or documentation suggesting that the standard harness could eventually be deprecated?

One more important question:

What sources do you follow to stay ahead of Copilot Studio changes?

I have been unable to access the new experience for a couple weeks now (no toggle at top of page as it once was).

This was fine as I was able to access my GHCP harnessed agents (built in new experience) via the old experience, however today upon logging in all my agents are just gone. Disappeared.

Has anyone had a similar experience?
Has anyone spoken with an MS rep?

Hey there,

I am working on a Environment Strategy. I was wondering, why I had so many agents in the default environment. Then i came to my mind, that all those agents are agents from the copilot studio lite / Agent Builder. M365 Chat Agents, you get it. Those little agents that are build within your copilot chat experience :D It seems like all of them are deployed as default into the personal productivity / default environment.

Since there might be scenarios, where they need credits - is there any way to change this and select a dedicated environment, where new deployments are routed?

If not, how do you guys / girls deal with this issue?

Kind Regards

TL;DR: My Copilot Studio agent works flawlessly in the Test panel and in M365 Copilot, but in Teams 1:1 chat it's unreliable - it answers the first message, then goes silent on follow-ups (even a plain "Hi"). Intermittent, and seems per-user. I've tried everything I can find. Looking for anyone who's actually resolved this vs. just worked around it.

[Image in the comments]

Setup

- Custom agent built in Copilot Studio (generative orchestration ON, default sonnet model).

- Knowledge/tools: Confluence via an MCP tool (getConfluencePage), grounded HR content.

- Auth: Authenticate with Microsoft.

- Published to Teams, admin-approved, installed as a personal app.

- Low volume (single-digit conversations/day — pilot stage).

The symptom

- First message in a fresh chat → responds fine (within ~30-60s).

- A few minutes later, follow-up messages → **no response at all.** Shows typing then stops.

- Happens even with trivial inputs like "Hi" / "Hello."

- In the Copilot Studio **Activity log**, the turn shows **"Completed"** — so the message reaches the agent, it just doesn't render a reply in Teams.

- **Works consistently in:** Copilot Studio Test panel. Teams 1:1 chat is flaky.

What I've already tried (no luck)

- ✅ Inactivity-reset topic ("user is inactive for a while" → Clear variable values and conversation hostory→ End conversation), set to 30 min.

- ✅ Verified all connections — not stale.

- ✅ `/debug clearstate` — clears fine, but next message still hits the "connect first" prompt or silence.

- ✅ Uninstalled + reinstalled the agent in Teams (I know ConversationStart doesn't re-trigger on reinstall, but tried anyway).

- ✅ Confirmed personal scope / installed as personal app.

- ✅ Checked there are no topic errors.

What I think is going on (but want confirmation)

This looks a lot like the intermittent "typing-then-no-response in Teams" issue several orgs reported starting ~Jan 2026 (including one with ~400 users), still seemingly unresolved by MS. Pattern matches: works on web/M365 Copilot, flaky only in Teams, inconsistent per-user.

We need to launch this agent today. Panicking on these last minute issues.

Just noticed on the left pane, the icon that used to go to AgentOps is now missing for me. Is anyone else experiencing this issue?

What’s the best way of creating a copilot studio agent that can be a second brain?

I’m intending to throw it links of files I find useful, transcripts, thought leadership articles etc. and it converts these to markdown / knowledge store with some kind of indexing.

I’m expecting over time this will grow to be hundreds of files - so a typical ‘add the source file as knowledge source’ will be too unwieldy, and also not efficient for the model given having the files as MD will be much more efficient.

I’m intending to be able to throw it links via chat and it can process these into the brain.

Hello, i was wondering if there was any resources anyone has on saving chats and loading them up again. Right now im hosting my copilot agent in .net and want to have chats save and loaded depending on the user. I have it authenticated using Entra ID, but I'm imagining it wouldnt work with that or be different? I first had used a threadID in localstorage, which would persist a message even if a refresh happened, but not if the server crashed. That option doesnt really help with loading chats back however.

Thanks for any help

I've built a general-purpose agent in Copilot Studio (Claude model, several MCP tools connected — Work IQ, Tavily, IFTTT, HTTP — plus a couple of connected agents for research/QA tasks). It works well reactively, but I want it to be more proactive and to adapt to my preferences over time.

Curious what methods you all use:

1. Do you rely mostly on the Instructions field, or do you iterate with structured skills/knowledge sources?
2. Any tricks for making agents proactive (e.g. triggers, scheduled runs, Power Automate flows) instead of purely request-response?
3. How do you handle "memory" — do you store user preferences somewhere the agent can read, or re-inject context each session?
4. Do multi-agent setups (orchestrator + specialist agents) actually improve output quality for you, or just add latency?

Would love to hear what's worked (or failed) for others.

I am in an impossible position...

My organization has asked me to help "create" AI for my division. The problem is, I know next to nothing.

I have studio in a test environment and I can do very basic things. Point to a knowledge source, connect to an API...but my goodness...I can't get anything to work at a "production" level.

This is not my background...everyone is speaking over my head. I'm panicking a bit.

Is there anyone here that is "good at this"? This is a far fetched ask, but anyone willing to tutor me? YouTube videos only get me so far....

Hi everyone,

I’m testing an agent built in Microsoft Copilot Studio that uses the Microsoft Learn documentation MCP tools to retrieve Microsoft documentation and answer user questions.

I’m facing a strange difference between the Copilot Studio Test Pane and Microsoft Teams.

The issue is:

In Copilot Studio Test Pane:

• I ask a question → I get the correct answer.
• I ask the same question again → I get the answer again.
• I can repeat the question multiple times → The agent continues to respond correctly.
• The Microsoft Learn MCP tool is able to retrieve the relevant documentation.

In Microsoft Teams:

• I ask the question → I get an answer.
• When I ask the same or similar question again, sometimes Teams becomes silent / doesn't return an answer.
• The same question still works correctly in the Copilot Studio Test Pane.

So the behavior looks something like:

>

>

The agent is using Microsoft Learn MCP tools for retrieving Microsoft documentation, so I'm wondering whether the issue could be related to how the MCP tool call, grounding, conversation state, or published agent is handled through the Teams channel.

I have already tried republishing the agent and starting a fresh Teams conversation.

Has anyone experienced this with a Copilot Studio agent + Microsoft Learn MCP Server/tools + Teams?

I'm particularly interested in knowing what I should check in Application Insights / Copilot Studio logs to determine whether:

• The Teams request is reaching the agent.
• The Microsoft Learn MCP tool is being called on subsequent turns.
• The MCP tool returns results but the agent doesn't generate a response.
• Conversation/session state is affecting the second or third question.
• There is a difference between the Test Pane runtime and the Teams published runtime.
• Grounding / "Allow ungrounded responses" is affecting subsequent turns.
• Teams is using an older published version or cached conversation state.

Any suggestions or similar experiences would be really helpful. Thanks!

In the sence of, if you don't have a direct link to the website saved its like impossible to find. You google "Copilot Studio" on google, and in the first page there are no direct links to the page, only links to microsoft pages explaining what copilot studio is. Even worse on those pages most links lead keep you on the microsoft FAQ page. Trying to access it thru powerapps or power automate (Same thing, there is no direct link if you google them, usually have to scroll down couple links) you open the apps menu there and search "Copilot studio" there is nothing. Fully feels like they are trying to hide this app.

Hi everyone,

I'm working on a multi-agent architecture in Copilot Studio and I'm trying to understand whether the performance I'm seeing is expected or if there are optimization opportunities.

Current Setup

• Using Copilot Studio (New Experience).
• All agents are running on GPT-5.5.
• I have approximately 90 documents distributed across 9 specialized agents.
• Documents include:
  • PPTX
  • DOCX
  • XLSX
  • Markdown files
  • Other documentation formats
• Each agent is responsible for a specific domain/topic and only contains the documents relevant to that area.
• There is a single orchestrator agent that routes questions to the appropriate specialized agents.
• The orchestrator is the agent shared with end users.
• For each agent, I've also created summaries describing the purpose of each document and the scope of the agent's knowledge.

Problem

Most user questions are taking around 2 minutes to receive a response.

The responses are generally correct, but the latency feels too high for a production-like experience.

My Questions

1. Is this latency mainly related to the model having to search and interpret a large number of documents at runtime?
2. Can having many agents behind a single orchestrator significantly impact response time?
3. Does the file type matter? For example, are PPTX/XLSX documents typically slower to process than Markdown or text-based documentation?
4. Could poorly optimized agent instructions cause the orchestrator to spend too much time deciding which agent should answer?
5. Are there any recommended best practices for reducing latency in multi-agent RAG scenarios in Copilot Studio?
6. Has anyone seen substantial improvements by consolidating agents or restructuring their knowledge sources?

Additional Context

One thing I'm wondering is whether I'm over-segmenting the knowledge base. My original goal was to improve answer quality by separating content into specialized agents, but I'm now questioning whether the orchestration overhead is outweighing the benefits.

I'd be interested in hearing how others structure:

• Number of agents
• Number of documents per agent
• Use of orchestrators
• Prompt/instruction design
• Knowledge source organization

Has anyone faced similar response times and found an effective optimization strategy?

Thanks!

https://preview.redd.it/aphmr9la6djh1.png?width=621&format=png&auto=webp&s=3cd7d229e49ae6ad48772bde04ffb0f84fec60a5

I am trying to get this issue resolved. I have tried every single suggestion from Copilot, and none have worked. I also have absolutely no idea what I am doing, so any suggestions would help.

Hello - I think the answer is a 'Yes' but i wanted to double check since the change is significant.

We do have one or two agents with several topics with some "easy" routing rules. I am reading into the new feature/tab Workflows right now

Hey, I'm trying to set up ServiceNow KB articles as a knowledge source in Copilot Studio, but I want the access to be governed by RBAC, so that a user only gets results from the documents/articles they're actually authorized to see.

Setup:

Copilot Studio agent using the ServiceNow connector to pull Knowledge Base articles

KB articles in ServiceNow already have role-based/user-criteria restrictions configured

What I'm trying to achieve:

When the agent searches or retrieves KB articles, I want the results to respect the requesting user's access level in ServiceNow, not return everything regardless of who's asking. Essentially: user asks a question, agent only surfaces articles that user has permission to view.

Questions:

Has anyone actually gotten this working end-to-end? What did the setup look like?

Does the ServiceNow connector pass through the end user's identity, or does it always run under a service account (in which case RBAC wouldn't naturally apply)?

If it's a service account, how did you enforce the restriction — filtering in Copilot Studio itself, or some pass-through auth (SSO/OAuth on-behalf-of) so ServiceNow applies its own RBAC at query time?

Would really appreciate hearing from anyone who's solved this, especially if you were dealing with sensitive KB content (HR, compliance, security) where RBAC actually mattered.

I am using the new UI in copilot studio and I have added some suggested prompts. I have saved all changes and published the agent to Teams and M365. However, I cannot see the prompts anywhere. I already tried deleting the installations and then I published my agent again but it didn’t work.

Has anyone else had similar issues with the new UI?