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OpenAI Dots represent a shift from traditional assistants toward persistent digital agents. They can work toward defined goals, maintain context, use connected applications, and continue tasks between conversations.
According to OpenAI, Dots are powered by GPT-6 Astra and can work through ChatGPT, Slack, and Teams.
The technology could help with research, project coordination, content production, software development, and other multi-step workflows.
OpenAI is pushing AI assistants beyond the traditional question-and-answer model with its new Dots agents. The company describes Dots as always-on agents designed to work toward users’ goals in the background. Powered by GPT-6 Astra, each Dot has its own cloud computer and browser.
It can also connect with more than 4,000 apps through OpenAI’s plugin ecosystem. The idea is simple: instead of repeatedly telling software what to do, users can give an agent an objective and let it handle the work.
Traditional assistants generally wait for a prompt before doing anything. Dots are designed around a different model. A Dot can keep working after the user leaves the conversation. It can handle several projects, maintain context, and return with updates or questions when needed. Users can also redirect its work along the way.
This makes Dots feel closer to a digital coworker than a conventional chatbot. The distinction matters since many workplace tasks involve several steps rather than one simple request. An employee might provide a goal and expect research, analysis, drafts, revisions, and follow-up actions. Dots are designed to handle that longer chain of work.
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The potential applications cover a wide range of professional roles. A developer could have a Dot monitor customer feedback, identify smaller bugs, create fixes, test them, and prepare pull requests for review. A product manager could ask it to update launch materials when requirements change.
Researchers could use Dots to rerun analyses when new information arrives. Sales teams could use them to track customer requirements, update proposals, and prepare technical materials.
Content teams could also use them to turn interview transcripts into clips, show notes, and social posts. These examples point toward a different division of labor. People could spend more time making decisions while software handles repetitive coordination and preparation.
Another important part of the concept is where Dots operate. Users can communicate with their Dot through ChatGPT, Slack, and Microsoft Teams. The agent can carry context across those channels, so users don't have to restart the conversation each time. This could be particularly useful in businesses where work is scattered across multiple platforms.
For example, a project might involve email, spreadsheets, messaging platforms, documents, and project-management software. An agent that can work across those systems could reduce the manual coordination between them. OpenAI is also developing specialist Dots for organizations. These agents could have dedicated identities, credentials, and defined responsibilities inside company systems.
Giving software more independence also creates a bigger responsibility for users and companies. Dots can perform actions through connected services, so permissions matter. OpenAI provides Custom Rules, approval requirements, activity monitoring, and automated reviews for certain actions. Sensitive tasks, such as changing passwords or transferring money, still require the user to take control.
Another concern is that agents can make mistakes. A wrong email recipient, incorrect document change, or misunderstood instruction could have real consequences. Websites and documents can also contain malicious instructions designed to manipulate an agent.
According to OpenAI, Dots use safeguards against these risks, but the company still recommends reviewing consequential work.
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The bigger question is how persistent agents could change workplace roles. Automation has already taken over many repetitive tasks. Always-on agents could extend that automation into work that previously required coordination and judgment. This does not necessarily mean every task becomes fully automated. Human review remains important for decisions involving customers, money, legal commitments, research, or company strategy.
Instead, the workplace could shift toward a model where employees set goals while agents handle execution. OpenAI has started rolling out Dots to eligible Pro and Business Premium users, with Enterprise users able to access a beta when enabled by their administrators. The company also plans broader access and additional specialist agents.
Dots therefore go beyond another AI product launch. They represent a shift toward software that does not simply answer questions, but keeps working toward an objective.
If that model proves reliable, the next generation of workplace tools may feel less like applications and more like digital teammates.
OpenAI Dots are always-on agents designed to work toward user-defined goals beyond a single conversation. They can maintain context, use connected tools, and continue making progress between conversations. OpenAI says they are powered by GPT-6 Astra and have their own cloud computer.
Regular assistants generally respond when users send a request. Dots are designed for ongoing responsibility. They can continue working between conversations, handle multi-step tasks, and return with results or questions when they need human judgment.
Dots can support tasks involving research, writing, analysis, coordination, software development, and other recurring workflows. Their usefulness depends on the applications connected to the agent and the permissions granted by the user or organization.
Yes. OpenAI says Dots can work through ChatGPT, Slack, and Microsoft Teams. They can also use connected applications within the permissions provided to them. This allows them to work across tools instead of remaining inside one conversation.
OpenAI Dots are powered by GPT-6 Astra. OpenAI describes Astra as a model designed for demanding professional work, including computer use, browsing, software engineering, and other complex tasks.
