Workspace agents

April 22, 2026

Understand, build, and use agents for repeatable work in ChatGPT.

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.

What is an agent?

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.

Component

Description

Examples

Trigger

What starts the agent

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

Process and skills

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.

Tools and systems

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

Agents are most useful when the work is:

Repeatable: The same task comes up regularly

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

Time-based or event-driven: It runs on a cadence or is triggered by an event

Tool-based: It requires reading from or writing to systems your team uses

For open-ended thinking, brainstorming, or exploratory writing, regular chat is often a better fit—especially for one-off tasks.

Agents are also different from traditional API workflows you may have built in the past. Traditional workflows in other tools are often deterministic, meaning each step is explicitly defined, and the system follows the same path each time unless you change the logic. Agents are more probabilistic. They still operate within instructions, tools, and guardrails, but they use a model to interpret context, make bounded decisions, and adjust how they move through the work.

Anatomy of an agent

A helpful way to design a workspace agent is to break it into parts. Think about what you would clarify before handing work to a person: what they are responsible for, when they should begin, what should make them pause or stop, which tools and information they can use, the process they should follow, and the rules they must stay within. An agent may require access to plugins. Learn more about plugins in ChatGPT.⁠

See some examples of agent breakdowns below:

Marketing campaign summary agent

Product feedback triage agent

Sales pipeline summary agent

Objective: What is the overall goal of the agent?

Analyze campaign performance and recommend optimizations

Summarize new product feedback and route to the right owners

Monitor pipeline changes and highlight risks and opportunities

Trigger: What starts the work?

Every Monday at 10 AM

Form submission from Slack

Every weekday at 8 AM

Process: What steps should it follow?

Pull KPIs, identify trends, draft a summary, propose next steps, assign owners

Review feedback, group related items, summarize key themes, suggest owners for follow-up

Review pipeline, flag risks, propose next steps

Tools: What systems or applications do you need access to?

Analytics tools and a shared summary document

Slack, ticketing system, and a summary document

CRM, email or Slack, and a pipeline tracker

Governance: What controls do you need? When should it stop and escalate?

Draft recommendations; approval required before budget changes

Create draft tickets; escalate high-priority issues; approval required before submission

Draft insights and recommendations; notify owners; no direct outreach without approval

Agent workflow examples

The examples below can be thought of as agent workflow patterns: common, repeatable patterns of work that show up across teams and functions. Each one represents a core type of workflow an agent can carry out. The specific tools, data, and outputs may vary, but the underlying pattern stays consistent.