OpenAI introduced a new paradigm and product today that is likely to have huge implications for enterprises seeking to adopt and control fleets of AI agent workers. Called "Workspace Agents," OpenAI's new offering essentially allows users on its ChatGPT Business ($20 per user per month) and variably priced Enterprise, Edu and Teachers subscription plans to design or select from pre-existing agent templates that can take on work tasks across third-party apps and data sources including Slack, Google Drive, Microsoft apps, Salesforce, Notion, Atlassian Rovo, and other popular enterprise applications. Put simply: these agents can be created and accessed from ChatGPT, but users can also add them to third-party apps like Slack, communicate with them across disparate channels, ask them to use information from the channel they're in and other third-party tools and apps, and the agents will go off and do work like drafting emails to the entire team, selected members, or pull data and make presentations. Human users can trust that the agent will manage all this complexity and complete the task as requested, even if the user who requested it leaves. It's the end of "babysitting" agents and the start of letting them go off and get shit done for your business — according to your defined business processes and permissions, of course. The product experience appears centered on the Agents tab in the ChatGPT sidebar, where teams can discover and manage shared agents. This functions as a kind of team directory: a place where agents built by coworkers can be reused across a workspace. The broader idea is that AI becomes less of an individual productivity trick and more of a shared organizational resource. In this sense, OpenAI is targeting one of office work’s oldest pain points: the handoff between people, systems, and steps in a process. OpenAI says workspace agents will be free for the next two weeks, until May 6, 2026, after which credit-based pricing will begin. The company also says more capabilities are on the way, including new triggers to start work automatically, better dashboards, more ways for agents to take action across business tools, and support for workspace agents in its AI code generation app, Codex. For more information on how to get started building and using them, OpenAI recommends heading over to its online academy page on them here and its help desk documentation here. The Codex backbone The most significant shift in this announcement is the move away from purely session-based interaction. Workspace agents are powered by Codex — the cloud-based, partially open-source AI coding harness that OpenAI has been aggressively expanding in 2026 — which gives them access to a workspace for files, code, tools, and memory. OpenAI says the agents can do far more than answer a prompt. They can write or run code, use connected apps, remember what they have learned, and continue work across multiple steps. That description lines up closely with the capabilities OpenAI shipped into Codex just six days ago, including background computer use, more than 90 new plugins spanning tools like Atlassian Rovo, CircleCI, GitLab, Microsoft Suite, Neon by Databricks, and Render, plus image generation, persistent memory, and the ability to schedule future work and wake up on its own to continue across days or weeks. Workspace agents inherit that plumbing. When one pulls a Friday metrics report, it is effectively spinning up a Codex cloud session with the right tools attached, running code to fetch and transform data, rendering charts, writing the narrative, and persisting what it learned for next week. When that same agent is deployed to a Slack channel, it is a Codex instance listening for mentions and threading its work back in. This is the technical decision enterprise buyers should focus on. Building an agent on a code-execution substrate rather than a pure LLM-call-and-response loop is what gives workspace agents the ability to do real work — transforming a CSV, reconciling two systems of record, generating a chart that is actually correct — rather than describing what the work would look like. Persistence and scheduling In earlier AI assistant models, progress paused when the user stopped interacting. Workspace agents change that by running in the cloud and supporting long-running workflows. Teams can also set them to run on a schedule. That means a recurring reporting agent can pull data on a set cadence, generate charts and summaries, and share the results with a team without anyone manually kicking off the process. Here at VentureBeat, we analyze story traffic and user return rate on a weekly basis — exactly the kind of recurring, multi-step, multi-source task that could theoretically be automated with a single workspace agent. Any enterprise with a weekly reporting rhythm pulling from dynamic data sources is likely to find a use for these agents. Agents also retain memory across runs. OpenAI says they can be guided and corrected in conversation, so they improve the more a team uses them. Over time they start to reflect how a team actually works — its processes, its standards, its preferred ways of handling recurring jobs — which is a meaningfully different proposition from the static instruction-set GPTs that preceded them. The integrated ecosystem OpenAI's claim is that agents should gather information and take action where work already happens, rather than forcing teams into a separate interface. That point becomes clearest in the Slack examples. OpenAI's launch materials show a product-feedback agent operating inside a channel named #user-insights, answering a question about recent mobile-app feedback with a themed summary pulled from multiple sources. The company's demo lineup walks through a sample team directory of agents: Spark for lead qualification and follow-up, Slate for software-request review, Tally for metrics reporting, Scout for product feedback routing, Trove for third-party vendor risk, and Angle for marketing and web content. OpenAI also shared more functional examples its own teams use internally — a Software Reviewer that checks employee requests against approved-tools policy and files IT tickets; an accounting agent that prepares parts of month-end close

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