OpenAI is expanding ChatGPT's utility beyond one-off queries, introducing workspace agents designed to embed AI into day-to-day, repeatable work. These agents aim to streamline workflows that previously required manual intervention and constant context-setting.
Unlike traditional, deterministic API workflows, these agents are probabilistic, interpreting context and making bounded decisions within defined parameters. They are best suited for tasks that are repeatable, structured, time-based or event-driven, and require interaction with specific tools or systems.
Anatomy of an Agent
An agent comprises three core components: a trigger (schedule or manual initiation), a process with specialized skills, and the tools or systems it can connect to, such as Slack or CRMs.
- Trigger: Initiates the agent, e.g., a schedule or manual run.
- Process and Skills: The sequence of actions the agent takes, including data review, drafting, and handoffs.
- Tools and Systems: Approved applications and integrations the agent can access for information or actions.
Workflow Automation
OpenAI has identified several common agent workflow patterns, including briefing generation, triage and routing, analysis and recommendation, content creation, and planning and coordination. These patterns showcase how agents can automate complex, multi-step processes.
For instance, a sales team could use an agent to compile daily account briefings by pulling data from CRM, call logs, and Slack. Similarly, product teams can leverage agents for feedback triage, automatically categorizing and routing user input to the appropriate owners.