OpenAI has introduced dots, a new class of always-on AI agents designed to keep working toward a goal even when you are not actively chatting. The pitch is bigger than a smarter chatbot: each dot gets a cloud computer and browser, can connect to thousands of apps, and can return with progress as a project changes.
For readers, the useful question is not whether dots sound futuristic. It is whether the new agents are available on your plan, what they can safely access, and where human approval still matters. Here is the practical version.
What are OpenAI dots?
A dot is a persistent agent inside the OpenAI ecosystem. OpenAI says dots are powered by GPT-6 Astra and can be assigned ongoing work rather than a single prompt. A user might ask one to track a developing sales opportunity, research a purchase, organize a trip, update a proposal as requirements change, or build a working software demo for review.
Each dot has its own cloud computer and browser. It can also connect to more than 4,000 apps through plugins, which gives it a way to gather context and act across the services a person or team already uses. OpenAI says people can communicate with dots in ChatGPT, Slack and Microsoft Teams, with text-message access planned later.
That persistent setup is the main distinction. A dot is meant to notice new information, continue a task in the background and bring back a useful result without making the user reopen the same conversation and restate the entire job.
Who can use dots now?
The rollout is gradual, so two people on the same plan may not see the feature at the same time. OpenAI says access is beginning for eligible Pro, Business Premium and Enterprise customers in supported markets. Enterprise access is controlled by workspace administrators and is off by default.
OpenAI is initially including one primary dot with eligible Pro and Business Premium plans at no additional charge. The company also describes a launch-period allowance for deeper work, but work delegated by a dot to Codex or ChatGPT Work can count against those products’ usage limits. That makes the included dot different from unlimited background labor.
If the feature is absent from your account, the most likely explanation is the staged rollout or a workspace setting—not necessarily an unsupported device. Enterprise users should check with an owner or administrator before assuming the account is ineligible.
What dots can actually do
OpenAI’s examples position dots as general-purpose project workers rather than simple reminders. Depending on the connected apps and permissions, a dot can:
- Monitor a changing project and revise a deliverable when new information arrives.
- Research across the web and connected sources, then summarize findings.
- Prepare documents, presentations and analysis for review.
- Use Codex to build or update software and return a working demo.
- Coordinate through ChatGPT, Slack or Teams instead of requiring one permanent browser tab.
- Remember feedback about how the user wants recurring work handled.
The reader benefit is continuity. Instead of asking for isolated outputs, you can define a result and let the dot keep the project moving. That can be useful for travel planning, competitive research, recurring reporting, launch preparation and other jobs where the inputs change over time.
How dots differ from a normal ChatGPT conversation
A standard conversation is usually reactive: you ask, ChatGPT answers, and the next step waits for another message. A dot is designed to be proactive and persistent. It can keep a project open, observe permitted sources, and decide when new information is important enough to act on or report.
Dots also have a dedicated cloud environment. That separation matters because the agent is not simply taking over your personal computer by default. OpenAI says local computer access requires permission, while the cloud computer remains a separate workspace unless you explicitly connect more capabilities.
That does not make a dot infallible. It changes the operating model from ‘answer this prompt’ to ‘work toward this goal,’ which increases both usefulness and the need for careful rules.
Privacy, permissions and human approval
OpenAI gives users and administrators several controls intended to limit what a dot can do. Custom Rules can allow an action, require approval before it happens, or block it entirely. An Activity View provides a record of what the dot has been doing, while automatic review systems are intended to check consequential actions.
OpenAI says especially sensitive actions—such as changing passwords or permanently deleting data—require explicit consent. Business customer data is not used to train OpenAI models by default. Personal-plan users can manage whether conversations and dot activity are used to improve models through their data controls.
These protections are meaningful, but they do not remove the need for review. A dot can still misunderstand a goal, use stale information or produce an incorrect draft. The safest starting point is a narrow task with clear approval rules and a result that a person can inspect before it reaches customers, colleagues or the public.
Read-only research has an important boundary
When a dot is proactively researching while you are away, OpenAI says connected-app tools are restricted to read-only access. In that mode, the agent can inspect available information but cannot send messages, change content, or control a browser or computer.
That boundary is reassuring, but it is also easy to misunderstand. A dot may gain broader abilities when you are actively working with it and approve an action, or when workspace rules explicitly permit one. Users should review both the current task and the configured rules instead of assuming every dot interaction is permanently read-only.
A sensible first configuration is to allow reading and drafting, require approval for messages or file changes, and block destructive actions unless there is a compelling reason to enable them.
What enterprise teams should know
Enterprise workspaces do not automatically gain an unrestricted agent. Owners can decide whether dots are available, whether Slack or Teams connections are allowed, whether local computer access is permitted, and which Custom Rules apply.
That makes deployment a governance decision as much as a productivity decision. Teams should identify the systems a dot may read, the actions it may propose, who approves consequential changes, and how Activity View records will be reviewed. Regulated teams should also confirm that their existing data-handling and retention requirements match the chosen configuration.
OpenAI’s administration guide says phone messaging is not available for Enterprise at launch. The company also cautions that the rollout is gradual and that individual capabilities may not appear immediately.
Limits and questions to watch
The launch leaves several practical questions that only real-world use will answer. Long-running agents can consume more compute than a short chat, so allowance details and delegated-tool limits matter. Reliability also matters: Reuters reported that some voice-update demonstrations encountered problems during the live launch event.
Users should also watch how well a dot distinguishes a useful update from noise, how clearly it explains the actions it took, and how easily a project can be handed back to a person. An always-on agent that requires constant correction is not much of a time-saver.
Finally, availability remains uneven. OpenAI has announced the product, but the feature is still rolling out. Treat broad demos as examples of the intended experience, not a guarantee that every integration and channel is already enabled on every account.
Who should try a dot first?
Dots make the most sense for people who already have a recurring, multi-step workflow with clear inputs and a reviewable output. Strong first experiments include a weekly market brief, a monitored travel itinerary, a product-research watchlist, a draft status report or a software prototype that must be reviewed before release.
Avoid starting with high-stakes or irreversible work. Do not make the first test a password change, a public announcement or an unsupervised customer message. Begin with read access, drafting and explicit approval. Expand permissions only after the dot has shown that it understands the job.
A practical setup for voice updates and calls
If you plan to communicate with an agent through frequent calls or voice updates, a comfortable USB headset for computer calls can make long sessions easier and keep audio more consistent than a laptop microphone.
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The bottom line
OpenAI dots are a significant shift from on-demand chat toward persistent software that can keep working across apps. The most compelling features are the dedicated cloud computer, broad plugin connectivity and the ability to maintain a project as conditions change.
The tradeoff is that persistence raises the stakes. Availability is limited, usage is not boundless, and permissions deserve careful attention. Readers who get access should start with a narrow, reversible workflow, keep approval gates around consequential actions, and judge the product by the quality of its Activity View and finished work—not by the promise of an agent that is always on.
Sources
- OpenAI: Introducing dots
- OpenAI Help Center: Manage dots in ChatGPT workspaces
- Reuters: OpenAI takes on Meta with always-on dots agent