ChatGPT Dots are always-on agents inside ChatGPT. They keep working on your goals between chats, on their own cloud computer, instead of waiting for your next prompt the way a one-off ChatGPT reply does. OpenAI introduced them on September 29, 2026.
That difference is the whole story. ChatGPT answers when you ask. A Dot keeps going when you walk away. To see how Dots fit next to other agents and assistants, see our map of AI tools.
What ChatGPT Dots are
OpenAI describes Dots as always-on agents built to handle ongoing work. They launched on GPT-6 Astra, and since a November 3, 2026 update OpenAI also uses GPT-6.1 Terra, so your Dot can draw on different models for different parts of its work (OpenAI). Dots keep learning from your feedback and can connect to the apps you already use through ChatGPT's plugin ecosystem (OpenAI cites more than 4,000 apps).
You can talk to your Dot in ChatGPT on desktop, web, and mobile. You can also reach it in Slack and Microsoft Teams. Voice calls are part of the product, and texting is on the roadmap.
Your first Dot is yours to name and shape. Over time OpenAI wants teams of Dots working together, plus specialist Dots that companies can set up with their own identity and access for clear jobs inside an organization.
Day-to-day Dot vs one-off ChatGPT
Think of ordinary ChatGPT as a sharp colleague you ping when you need an answer. You open a chat, ask, get a reply, maybe iterate, then close the tab. The work stops when the conversation stops.
A Dot is closer to a junior teammate who already has context and a computer:
- It has its own cloud computer and browser, so it can keep working without sitting on your laptop.
- It can run several projects at once and take new tasks without forcing you to juggle separate threads for every step.
- It learns preferences over time: how you write, what good looks like, which standards matter.
- It can work in the background (OpenAI calls some of this proactive research) using connected apps in a read-only mode until you widen permissions.
- It brings you finished drafts and decisions that need your judgment, instead of dumping every intermediate step into one long chat.
OpenAI's own examples are ordinary work, not sci-fi: a developer Dot that turns recurring customer feedback into pull requests with demo videos; a launch lead whose Dot revises assets when scope changes; a scientist whose Dot updates figures when new data arrives; a sales lead whose Dot keeps a proposal current through technical review; a creator whose Dot turns an interview transcript into clips, show notes, and social drafts.
The pattern is the same each time. You set direction. The Dot moves the work forward. You review and approve the parts that matter.
