Most ChatGPT users already know how to use AI for one-off tasks—like drafting, summarizing, brainstorming, or answering questions. The next phase of AI use is broader and more embedded in day-to-day work. Instead of helping with isolated moments, AI is increasingly being used to support repeatable workflows that depend on shared systems, standard handoffs, consistent outputs, and real-world constraints like timing, accuracy, and process.

That’s where workspace agents in ChatGPT fit. They’re designed to be used for repeatable workflows—work you’d otherwise do manually, re-explaining the steps each time, and copying information between tools. Learn more about workspace agents in our blog post.

If you’re new to agent building, let’s focus on the core concepts first so when you start building, you’ll know how to set up your workspace agent for consistent results.

Generally speaking, an agent is a system that carries out a task with three components: a trigger, a process that may include specialized skills, and tools or systems it can connect to.

A schedule (“Every weekday at 9am”) or a manual run (“Run now”).

The steps the agent follows to complete the task the way you expect

Reviewing inputs, checking for missing information, drafting an output, and handing it off or taking the next action.

The approved tools and integrations the agent can use to gather information and, if allowed, take actions.

Slack, a CRM, internal documentation, a ticketing system, or a shared document

Structured: There’s a clear format for the output (so you can tell if the agent is doing a good job)

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