OpenAI Dots: Always-On Agents, Their Limits and Real Cost

A Dot keeps working for you after you close the chat, and every Codex task it launches draws on a five-hour allowance window that OpenAI sizes at roughly 5 to 45 Astra messages on Plus and about five times that on the Pro plans a Dot actually requires. OpenAI announced Dots at DevDay on 29 September 2026 in San Francisco as "always-on agents powered by GPT-6 Astra" (per AlphaSignal and TechCrunch coverage of the event). Talking to one costs nothing against your allowance. The work it hands to Codex or Work does.

Short answer: a Dot is a persistent cloud agent with its own computer, browser, memory and approved-app access. It reads freely, asks before it changes anything, and stays alive between conversations. You budget it like a contractor, not a chatbot. Set the allowance it may spend, decide which accounts it may touch, and review its drafts before they leave your name. Five documented limitations, covered below, mean approval rules reduce risk but do not remove it.

What a Dot is

Each Dot gets a persistent cloud computer, a browser, long-term memory and a defined set of approved apps. It has a name, an avatar and a handle in the form @yourname-dot. You reach it in ChatGPT, Slack, Microsoft Teams or by voice call, and it can launch parallel background agents and create Codex tasks (per OpenAI help documentation). Coverage counts the app integrations differently, with "thousands" in OpenAI's wording and 4,000 or more through plugins in one outlet's count.

The difference from a normal chat agent is persistence. A chat agent stops when you stop. A Dot keeps its computer, browser session and memory running after your laptop closes. That is the feature, and also the thing that makes budgeting necessary.

The approval model

OpenAI splits a Dot's actions into two classes. Idle research is read-only, so a Dot can browse, read documents and summarise without asking. Anything that changes an account or sends information out needs either a standing integration permission or an explicit approval from you.

An automated reviewer sits between the Dot and the action. For each step it decides one of three outcomes: proceed, ask for approval, or return the task to the Dot. You can add custom rules that force draft review, for example "never send an email without showing me the draft". When a task needs a login the Dot cannot complete, a "Take over" button hands you the browser.

The sensible setup is to start with every write action on draft review and relax rules one integration at a time. Give calendar read access before calendar write. Give a sandbox Slack channel before your company workspace. The gap between "can read" and "can act" is where every agent incident so far has lived.