OpenAI is taking its AI assistant strategy beyond chat conversations with Dots, a new category of persistent AI agents that can continue working on tasks even after users leave ChatGPT.
Unlike traditional chatbots waiting for a new prompt, Dots are responsible for ongoing work, operate in the background, and return to users when their input or approval is needed. OpenAI says Dots are powered by GPT-6 Astra and have their own cloud computers, so they can work in a workspace between tasks.
The introduction of Dots is a step towards more AI companies positioning their products. And instead of just asking questions and writing content or brainstorming ideas for AI, users are increasingly setting an agent a goal and letting the agent do multiple steps at once.
OpenAI explains that Dots can work on behalf of users at any time, get feedback from other developers and connect with more than 4,000 apps through its plugin ecosystem. They can also be accessed using ChatGPT, Slack and Microsoft Teams.
What makes OpenAI Dots different from ChatGPT?
The biggest difference is persistence. A standard ChatGPT conversation is one of interaction: a user asks something, the AI answers and then the conversation continues, and the user replies when another prompt comes in. Dots are different because they take on an ongoing responsibility and are able to make progress without having to ask the user to stay in the conversation.
OpenAI says users can give a Dot a goal and define what it is allowed to do independently. The agent can then work through complex problems, determine what needs to happen next and bring the results back for review. When a decision requires human judgment, the Dot can turn to the user rather than simply proceed on its own.
This persistent setup also allows Dots their own cloud computing environment. According to OpenAI, each Dot has its own cloud computer and browser, which keeps connected tools on track and keeps the work running all the time. This also means the computer doesn’t have to be switched on while the Dot works.
How Dots can work while you sleep?
The phrase "work while you sleep" refers to the ability of Dots to carry out background tasks without having to be constantly connected. A user might write up a project that is ongoing, connect the applications to the user's work, and let the agent keep working after the user is done.
OpenAI describes Dots as suitable for recurring and complex work. The company's examples include maintaining work materials, processing information across connected applications, and tracking tasks. Dots can even delegate work to subagents and break larger assignments into smaller pieces.
It is essentially closer to having a digital worker assigned to a project than simply having a chatbot available for questions. Users can give feedback along the way while the Dot learns to become familiar with their preferences and expectations.
OpenAI Dots vs Claude Cowork And Meta Muse
OpenAI is entering a space in which other tech companies are also developing AI systems capable of completing multi-step tasks. Anthropic’s Claude platform includes agentic capabilities for long-term and complex workflows such as enterprise tasks and software-related tasks. Anthropic has also emphasized the need for containment and safety precautions as agents are given more access to tools and systems.
Meta is moving in a similar direction with Muse. Meta describes Muse as a personal AI agent that can do more than answer questions, like take action on behalf of the user, work towards long-term goals and run through a dedicated cloud-based secure computer. Muse can work on any application and is designed to go on doing what it is meant to do once a user has set a goal.
This means the competition between AI companies is moving beyond which chatbot is capable of delivering the best answer. The next question is how well and safely these systems can manage work over time, use external applications and work with little supervision.
Privacy, Security And Control remain vitally important.
Persistent AI agents also pose new challenges. An agent becomes more useful if it can access applications, files and other information more easily but that access also increases the potential to make mistakes or take unauthorized actions.
OpenAI says its Dots have several layers of security. Plugin permissions can restrict what an agent can access, and custom rules allow users to set more boundaries. OpenAI also says its systems conduct automated reviews of some planned actions and use safety monitoring while a Dot works. For example, before an email is sent, automated checks can check the recipient and message.
These protections are especially important for Dots because they are not designed to operate under constant supervision. OpenAI accepts that agents may still encounter situations where they must be clarification- or approval-oriented. So the company’s approach is to provide agents more autonomy while keeping human oversight.
Who could benefit from OpenAI Dots?
For users who use AI mainly for quick questions, rewriting, brainstorming or occasional research, the difference between Dots and conventional ChatGPT might not immediately feel significant. The larger change is likely to be for users managing recurring workflows.
Businesses and professionals could utilize persistent agents for projects that require repeated monitoring, follow-ups, research or coordination among applications. Because Dots can remain in the cloud and connect to external tools, they are designed for work that does not end with a single answer.
OpenAI says Dots are currently available for Pro users in all eligible markets and Business Premium users can access them in supported ChatGPT regions. Enterprise, Edu and Healthcare users can also try a beta if their workspace administrator agrees. Availability is still open to some extent, but will be limited by OpenAI's rollout and local restrictions.
At its core, Dots represent a shift in the role that OpenAI wants AI to play. ChatGPT established a conversational model of AI interaction through prompts and responses. Dots help take the discussion towards persistent digital workers who can carry on performing an assignment after it’s over.
The success of that approach will not only depend on how capable the agents become, but on whether users are comfortable allowing them access to their applications, data and ongoing responsibilities.
And as OpenAI, Anthropic and Meta keep developing agentic systems, the most important AI competition will likely be who can build agents that are able to work independently without human control but are predictable, secure, and keep the system up to date.
