One of the biggest weaknesses in day-to-day ChatGPT use has been collaboration.
It has been easy for one person to do useful work with a chat. It has been much harder to turn that work into something a team can actually reuse without losing context along the way.
OpenAI's update allowing users to share entire ChatGPT Projects is a meaningful fix.
Previously, if you wanted to reuse work, you typically shared a single conversation. That meant passing around outputs without the full setup that made them useful in the first place.
Shared Projects are different because they can hold:
That makes them much better suited to team workflows.
Instead of saying, "Here is the output I got," you can now say, "Here is the environment we use for this kind of work."
That distinction matters.
The clearest use cases are recurring collaborative tasks such as:
For example, a team can create a Project containing:
Anyone joining the Project starts from the same base rather than rebuilding that context individually.
At the same time, OpenAI introduced more explicit control over how long ChatGPT 5 should "think" before responding.
That has practical value:
Auto for everyday tasksFast for speed-sensitive workThinking for more complex analysisBut for most organisations, the more important update is still shared Projects.
Thinking-time controls help individuals tune answers. Shared Projects help teams standardise work.
OpenAI also introduced Pulse, a format for structured recurring conversations with ChatGPT.
The interesting thing about Pulse is not scheduling on its own. It is continuity. It suggests a future where AI interactions become persistent routines rather than isolated requests.
That is a useful direction, but it is still early.
This Projects update also fits neatly with the wider connector ecosystem.
When ChatGPT can access the tools your team already uses, the practical value of a shared Project increases. It becomes easier to ask questions against a live working context rather than a manually assembled one.
That is why shared Projects matter more than they might first appear. They are not just a collaboration feature. They are part of a shift from one-person chat sessions towards shared AI workspaces.
The organisations getting the most from AI are not simply handing employees access to a model and hoping for the best.
They are creating:
Shared Projects support exactly that.
For teams that want to move beyond ad hoc prompting, this is one of the more useful product changes OpenAI has shipped.
Where to next
If this topic is relevant to your team, these pages are the best next stop.
Explore how we train editorial, communications, and creative teams to use AI without flattening quality.
See how we help brand, retail, and customer-facing teams move faster without losing control of voice or quality.
See a real client example of bespoke AI training inside a fast-moving consumer business.
We tested all eight ChatGPT personalities so you don't have to. Default wins for most tasks, Candid cuts waffle by 16%, and Cynical is the sharpest strategic voice. The other five? Skip them.
OpenAI has made ChatGPT Projects much more useful as a working knowledge base. Links from Slack and Google Drive, saved responses, and more controlled deep research all make Projects far more practical for business use.