OpenAI Dots and ChatGPT use related technology, but they are built around different ways of getting work done. ChatGPT is primarily a place where you ask, refine, and receive. A Dot is designed to keep pursuing a goal in the background, across apps, even when you are not actively chatting with it.
That distinction matters more than model names. If you are deciding which tool fits a task, compare the workflow, the level of autonomy, and the permissions involved.
The short answer: conversation versus continuity
Use ChatGPT when you want a direct conversation, a fast answer, help thinking through a decision, or close control over each step. Use an OpenAI Dot when a task has several stages, changes over time, and benefits from an agent that can monitor progress and act within predefined boundaries.
A prompt in ChatGPT normally produces a response and then waits. A Dot receives a goal, runs on its own cloud computer, connects to approved services, and keeps the assignment moving. It can contact you when it needs missing information or permission. This is why OpenAI describes Dots as always-on agents rather than another chat mode.
How the workflows differ
Imagine that you need a market summary. In ChatGPT, you might request research, review the answer, provide corrections, ask for a document, and repeat the process next week. The interaction is user-led.
With a Dot, the goal could be ongoing: watch selected sources, update a report when important facts change, and notify a team when the new version is ready. The agent-led portion is larger, although the user still defines sources, boundaries, and approval points.
That makes Dots a better conceptual fit for recurring reports, evolving proposals, project follow-up, software prototypes, and multi-app coordination. ChatGPT remains better for one-off explanations, brainstorming, editing, tutoring, and tasks where you want to inspect every turn.
Do Dots replace ChatGPT, Codex, or ChatGPT Work?
No. Dots appear to orchestrate capabilities rather than replace them. Reuters reports that Dots can use Codex and ChatGPT Work for software, research, documents, and data analysis. Those products provide capabilities that a Dot can call while pursuing a broader objective.
The model underneath also matters. Dots launch with GPT-6 Astra, OpenAI’s model for complex work. For a clearer view of how that differs from the faster Sol and Luna options, see our GPT-6 Astra vs Sol vs Luna guide.
Dots require more trust and tighter permissions
A conversational answer can be wrong, but it usually does not modify another system on its own. An autonomous agent may read files, send updates, change documents, or run software tasks. The consequences of excessive access are therefore larger.
OpenAI says Dots can be governed by custom rules. Password entry and permanent deletion require explicit consent, and the agent should ask when it reaches a protected action. Organizations should still begin with the smallest set of apps and permissions required for the job. Our guide to AI agent permissions explains why limiting access is safer than relying on perfect instructions.
Connected content also creates exposure to prompt injection, where hostile text attempts to override the user’s intent. Before giving any agent broad access, it is worth understanding how prompt injection works and how to reduce the risk.
Which one should you choose?
Choose ChatGPT if the job can be completed in a session, benefits from discussion, or contains sensitive decisions you want to make personally. Choose a Dot if the goal is ongoing, spans multiple tools, and has clear success conditions plus safe permission boundaries.
For many people, the sensible setup will be both: ChatGPT for exploration and judgment, a Dot for well-defined execution. The key is to automate the stable part of the process, not the part that still requires human context.
Availability is another deciding factor
Dots are initially available to ChatGPT Pro, Business, and Enterprise customers, with one Dot per user at launch, according to Axios. ChatGPT itself remains the broader, more accessible product.
OpenAI Dots are not simply “ChatGPT that works longer.” They change the relationship from asking a tool for outputs to supervising an agent with continuing responsibilities. That can save time on the right assignment, but only when the goal, access, and approval rules are precise.