ChatGPT Work – Multi-Step Deliverables, Delegation, and Supervision
Lesson 4: Real-World Agent Use Cases and Boundaries
Lesson Objectives
By the end of this lesson, students should be able to:
- Design research-to-deliverable workflows
- Use agents for controlled operations and content production
- Identify tasks requiring direct human relationships or professional authority
- Measure quality, cost, time, and error rate
Lesson Content
Useful Work workflows include: research a topic and build a cited brief; gather files and draft a project status report; compare options and prepare a spreadsheet; create a content package from an approved brief; inspect a repository and prepare a code change proposal; or monitor a public condition and report meaningful changes.
ChatGPT Work and agentic tools cannot supply missing authority. They cannot consent for another person, provide licensed professional judgment, guarantee truth, understand unshared organizational politics, or accept moral and legal accountability. They also cannot access systems, files, or the physical world unless a permitted tool actually provides that access.
Measure more than speed. Track factual error rate, correction time, unnecessary tool calls, duplicate actions, approval burden, and whether the final output is actually used. A Work run that appears fast but creates expensive review work is not productive.
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