OpenAI Dots Explained: AI Agents That Can Work Independently Across Apps

OpenAI has introduced Dots, a new class of AI agents designed to work toward user-defined goals without requiring constant prompts. Unlike conventional chatbot sessions that typically wait for the next instruction, Dots can continue working in the background, use a browser, interact with connected applications and ask users for input when a decision or approval is required.

Powered by GPT-6 Astra, Dots are designed to handle multi-step tasks and adapt to user feedback and preferences over time. OpenAI is positioning them less as chat assistants and more as digital co-workers that can take responsibility for an ongoing task while keeping the user in control.

What are OpenAI Dots?

At their core, Dots are AI agents that users can assign a goal or task to. Once given the necessary instructions and permissions, a Dot can break that goal into multiple steps and work through them without requiring the user to manually guide every action.

Each Dot operates on its own cloud computer. Users can inspect what the agent is doing, review files, check browser activity and intervene whenever necessary. OpenAI also allows users to give a Dot access to their personal computer, although this permission is not enabled by default.

This setup allows Dots to work on tasks that may take considerably longer than a typical ChatGPT conversation. Instead of simply generating an answer, the agent can continue working toward an outcome and return to the user when it needs clarification, approval or additional information.

How do OpenAI Dots Work?

A user can create a Dot through ChatGPT and provide instructions about what needs to be accomplished. The agent can then use its cloud computer, browser and authorised connected applications to complete different parts of the task.

Dots can also learn from feedback and adjust their behaviour based on user preferences. This means that users do not necessarily need to repeat the same instructions every time they assign related work.

For example, a developer could ask a Dot to monitor customer feedback, identify recurring problems, make minor code changes, run tests and prepare a pull request for human review. The Dot can continue working through these steps rather than stopping after completing a single action.

What Can OpenAI Dots do?

OpenAI has highlighted several potential applications for Dots across software development, product management, research, sales and media workflows.

For developers, a Dot could monitor customer feedback, identify recurring issues, implement small fixes, run tests and prepare changes for review. Product teams could use Dots to update launch materials when product plans or requirements change.

Research teams could assign Dots to update analysis when new information becomes available. Sales teams could use them to revise proposals as customer requirements evolve.

Content teams could also use Dots for repetitive production work, such as identifying useful moments from longer videos, preparing show notes and drafting social media posts. Human users can retain final approval over the resulting content.

Dots can Work Through ChatGPT, Slack and Microsoft Teams

One of the more important aspects of Dots is their ability to fit into existing communication workflows.

Users can create and manage Dots through ChatGPT on desktop, the web and mobile. OpenAI says work started in ChatGPT can continue through Slack or Microsoft Teams without losing context.

This could make Dots particularly useful for workplace teams where tasks and decisions are spread across different communication platforms. Instead of opening a separate AI tool for every task, users can interact with their assigned agents through the platforms they already use.

Dots can also send progress updates, ask clarifying questions and request approvals when required.

OpenAI Dots can Work in the Background

The biggest difference between Dots and conventional chat-based AI is their ability to continue working after the initial instruction.

Once a user defines an objective, a Dot can pursue that objective in the background. It can provide updates when necessary and pause when it reaches a point where human input is required.

This makes the workflow more similar to delegating a task to a colleague. The user defines the desired outcome and relevant constraints, while the AI agent handles the individual steps within the permissions it has been given.

What About Permissions and Privacy?

Because Dots can interact with apps, files and websites, permissions are an important part of the system.

OpenAI says each Dot operates on a separate cloud computer, keeping its work environment separate from the user's own device unless the user explicitly grants access to their computer.

Users can also control which connected applications a Dot can access. Custom Rules allow them to specify which actions are permitted, blocked or require approval.

OpenAI says Dots can conduct proactive background research using read-only tools. These tools cannot send messages, modify application content or control the user's browser or computer.

More sensitive actions, such as changing passwords, continue to require user involvement.

When will OpenAI Dots be Available?

OpenAI says Dots are rolling out to Pro and Business Premium users in eligible markets. Enterprise customers, including Edu and Healthcare workspaces, can access the beta when it is enabled by an administrator.

The first Dot is included with Pro and Business Premium plans at no additional cost, according to OpenAI.

Users can create their first Dot through the ChatGPT desktop app or desktop browser, connect supported applications and later access the agent through ChatGPT on mobile.

OpenAI Dots vs Traditional AI Chatbots

The key difference is how the two approaches handle work.

A conventional chatbot generally responds to a prompt and waits for the user to provide another instruction. A Dot is designed to receive a goal, work through multiple steps, use authorised tools and continue working until it reaches an appropriate stopping point or needs human intervention.

That shift moves AI closer to an agent-based workflow, where the user delegates an outcome instead of simply asking individual questions.

Why OpenAI Dots Matter

Dots represent OpenAI's push to make AI useful for longer-running, multi-step work rather than limiting it to question-and-answer interactions.

The idea is relatively simple: users define what they want done, provide the necessary permissions and let the AI handle the individual steps. Human oversight remains part of the process through approvals, permissions, progress updates and the ability to intervene.

For businesses, the potential use cases range from software development and research to sales and content production. The effectiveness of Dots will ultimately depend on how reliably they can complete these tasks while operating within the permissions and rules set by users.