Collaborate on AI Conversations with Your Team

Learn how to create shared AI threads, invite teammates to co-prompt, comment on responses, and control thread visibility in WorkLLM.

Team AI turns AI conversations into a collaborative workspace. Instead of each person running their own private chat in isolation, your team works together inside shared threads — sending prompts, reacting to responses, leaving comments, and building on each other’s context in real time. Every team member sees the same conversation history, so no one has to repeat context or work from stale information.

What is a shared thread?

A shared thread is an AI conversation that multiple people can view, contribute to, and comment on. It behaves like a standard chat — you send messages and receive AI responses — but with team access controls and collaboration features layered on top. Shared threads carry context across all contributors, so the AI understands contributions from every team member who has participated.

Creating a shared thread

1. Start a new thread

   Click New Chat in the left sidebar to open a conversation.

2. Open sharing settings

   Click the Share icon in the top-right corner of the chat. The visibility panel opens.

3. Invite specific teammates

   To invite individuals rather than a whole team, type their names or email addresses in the Invite people field.

4. Save and share

   Click Save. Invited teammates receive a notification and can join the thread immediately.

Co-prompting with your team

Once a thread is shared, any contributor with edit access can send messages. WorkLLM shows each message alongside the sender’s name, so the full conversation is easy to follow.

Multiple contributors

Any team member with edit access can send prompts. The AI receives contributions from all senders and maintains a unified context across the thread.

Real-time updates

Messages and AI responses appear in real time for everyone in the thread. You do not need to refresh to see what teammates have added.

Shared context

The AI carries full thread history — including messages from all participants — so contributors can reference prior work without re-explaining it.

Visible authorship

Each message shows who sent it. This makes it easy to see who asked what and follow the thread of reasoning across the team.

Commenting on AI responses

You can leave comments on any AI response in a shared thread. Comments are separate from the main conversation — they do not affect the AI’s context — and are visible to all thread participants.

To comment on a response:

1. Hover over the AI response you want to comment on.
2. Click the Comment icon that appears on the bottom of the response.
3. Type your comment and press Enter to post it.

Use comments to flag a response for review, add editorial notes, or suggest a follow-up prompt — without cluttering the main conversation flow.

How Team AI preserves context

WorkLLM uses Team Memory to maintain shared context across a thread even when different people contribute at different times. When a team member opens a shared thread, they see the full conversation history, including prompts and responses from all contributors. The AI treats the entire thread as its context window, regardless of who sent each message.

This means:

• A teammate can pick up a thread where someone else left off without re-prompting background information.
• The AI understands decisions and details established by any participant, not just the person currently typing.
• Context accumulated over multiple sessions remains intact — you do not start over each time someone new joins.

Thread visibility settings

Visibility	Who can see it	Who can contribute
Private	Only you	Only you
Shared	All members with whom the thread has been shared	All members with whom the thread has been shared

Changing a thread from Private to Shared makes all prior messages in the thread visible to those users. Review the thread content before broadening access.

Can I limit who sees a thread within my team?

Yes. Invite people to share the thread with specific individuals only. This lets you collaborate with a subset of your team without making the thread visible to everyone.

Can a Viewer role participate in a shared thread?

No. All members have the same permission in a shared thread. 

What happens to a shared thread if the creator leaves?

Threads can be archived, but people cannot leave the threads. 

Is there a limit on how many people can be in a thread?

There is no fixed limit on thread participants.