OpenAI’s Dot agent is enterprise software that can also order your dinner

by | Oct 3, 2026 | Technology

OpenAI’s Dot agent is enterprise software that can also order your dinner

OpenAI introduced Dots earlier this week, a new agent platform featuring anthropomorphic avatars designed primarily for workplace tasks. Similar in appearance to Meta’s Muse with blobby characters and customizable names, Dots function as software that can interact with other applications. Currently, users receive one Dot per account, with the option for multiple agents planned for the future. The platform emphasizes enterprise functionality rather than personal assistance, distinguishing it from competitors like Meta Muse and Instinct.

Dots are available initially through OpenAI’s premium subscription tiers, including the $100-per-month Pro account, positioning the tool as business-oriented software despite its approachable interface. The agent operates through a virtual machine that can access design applications like Blender and GIMP, connect to a user’s personal computer via the desktop ChatGPT app, and enable voice communication for collaborative work. This stands in contrast to competing free agents currently available from other providers.

Testing revealed mixed results across various tasks. When attempting to schedule an internet service provider installation, the agent navigated most of the process but encountered security verification challenges requiring human intervention. It struggled with finding promotional options on some websites and encountered repeated obstacles with security checks, particularly on e-commerce and service platforms. The agent’s cloud browser footprint appeared to trigger security protocols more frequently than competing systems.

Performance improved significantly when given access to controlled environments. When tasked with redesigning a personal website, Dots demonstrated substantial capability, allowing iterative refinement through voice conversation and text input. The agent processed extended verbal instructions and generated meaningful design updates across multiple rounds of revision. This suggested the platform functions most effectively when working with comprehensive data sets and projects under direct user control, rather than navigating third-party websites with security restrictions.

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