How to Share ChatGPT With Your Team Without Losing Context
There are three ways to share ChatGPT with your team, and they share different things. A shared link sends a read-only copy of one conversation. A ChatGPT workspace plan for teams lets people share custom GPTs and projects inside the workspace. To share what the team knows with every member’s AI, including people who use Claude or Cursor, keep that knowledge as notes in one shared place the assistants can read.
Most teams start with the first option, outgrow it in a week, and then argue about the second. The question to ask first is what you actually need to share: one answer, a set of instructions, or the background every chat should start from.
What does each sharing option actually share?
| Option | What it shares | Who can use it | Stays current | Works with other AIs |
|---|---|---|---|---|
| Shared link | A snapshot of one conversation | Anyone with the link | No, it’s a copy | No |
| Custom GPT | Instructions and files for one job | People you share it with | When the owner updates it | No |
| Workspace plan (shared projects, GPTs) | Projects, GPTs and admin controls in one workspace | Members of the workspace | Yes, inside ChatGPT | No |
| Shared notes over MCP | The team’s knowledge as linked notes | Every member’s AI that connects | Yes, any AI can update it | Yes |
None of these is wrong. They answer different needs, and many teams end up using two of them.
When is a shared link enough?
When you want a colleague to see one answer. ChatGPT can create a link to a conversation that others can open and read, and continue in their own account. OpenAI’s help article on shared links covers how they work and how to delete them.
The limits show up fast. The link is a snapshot, so it won’t update when the plan changes. The context someone else built up in that chat doesn’t carry into their next one. And a link to a long conversation is something people skim, not something they reuse.
When does a workspace plan make sense?
When your team lives in ChatGPT and needs admin control. OpenAI’s plans for teams put everyone in one workspace with shared custom GPTs, shared projects and billing in one place. Check OpenAI’s pricing page for what the current plans include, since features move between tiers.
A shared custom GPT is the most useful part for most small teams. Put the brand rules, the product facts and a few examples in it, and everyone who writes a client email starts from the same base.
What a workspace doesn’t solve:
- It only covers ChatGPT. The designer who prefers Claude and the developer in Cursor don’t see it.
- Knowledge sits inside instructions and files. Updating a fact means someone editing the GPT, and people often don’t know it changed.
- What the team learns in chats stays in chats. A decision made in one person’s conversation doesn’t reach the shared GPT unless someone copies it there.
How do you share what the team knows with every AI?
Keep it outside any single assistant. The pattern is a shared knowledge base made of short notes: one note per client, product, decision or rule, linked to each other, in plain text every AI can read.
MCP (Model Context Protocol) is what makes it reachable. It lets ChatGPT, Claude, Cursor and other assistants use an outside tool, such as a notes vault, while they work. Each person connects their own AI once. From then on, their assistant can search the team’s notes before it answers and save new notes when a decision is made. What is MCP explains it in plain words.
What goes in the shared notes:
- Clients and brands. Who they are, how they talk, what they never say.
- Decisions. What you chose and why, so nobody’s AI suggests the idea you already rejected.
- Facts. Prices, plan limits, specs, links, anything an AI would otherwise guess.
- How you work. Templates and checklists the team reuses.
Shared knowledge base for teams goes deeper into structure and who should edit what.
Who should be able to change shared notes?
Not everyone, and not every note. A useful split:
| Role | Can do | Fits |
|---|---|---|
| Owner or admin | Everything, including who has access | Founders, team leads |
| Member | Read and write the notes they can open | People who make decisions and write |
| Viewer | Read only | Freelancers, new hires, clients |
Limit sensitive vaults, like one client’s notes, to the people who work on that client. And keep a history of edits, so when an AI or a person changes a fact, you can see who changed it and put it back.
How Valta handles it
Valta’s Team plan gives the team shared vaults of Markdown notes that every member’s AI reads and writes over MCP: ChatGPT, Claude, Cursor or any other assistant that supports it. Each person signs in with their own account and connects their own AI. Roles are owner, admin, member and viewer, and a team vault can be limited to the people on its access list.
Every note records who created it, who edited it last and from which AI, and earlier versions are kept. If the team stops paying, its vaults turn read only and stay exportable. The setup guide covers connecting each assistant, and the plans are on the home page.
FAQ
Can two people use the same ChatGPT account?
OpenAI’s terms tie accounts to individuals, and sharing one login mixes everyone’s chats and memory. A workspace plan gives each person their own seat in a shared workspace instead.
Can my team see my ChatGPT conversations?
Not by default. A conversation is shared only when you create a link or share it in a workspace feature that supports it. Check your workspace’s settings for what admins can see.
How do I share a custom GPT with my team?
From the GPT’s sharing settings, choose who can access it: people with the link, your workspace, or the public GPT store. In a workspace plan you can limit it to members.
Does ChatGPT memory work across a team?
No. ChatGPT’s memory is per user. To give every member’s AI the same background, keep it in shared instructions or in shared notes their AI can read.
Can a team share notes between ChatGPT and Claude?
Yes, if the notes live outside both. A vault connected over MCP can be read and written by ChatGPT, Claude and other assistants, so the whole team works from the same notes whichever AI each person uses.