OpenAI final evaluation — Verified Real-World Workflow
Lesson 1: Final Evaluation Brief — Build a Verified OpenAI Workflow
Lesson Objectives
By the end of this lesson, students should be able to:
- Choose a real problem with measurable value
- Select ChatGPT, ChatGPT Work, GPT/plugin, Codex, or API components appropriately
- Define deliverables, evidence, boundaries, and success criteria
- Plan privacy, safety, and verification before execution
Lesson Content
The final evaluation proves applied judgment, not memorization. Choose one track:
- Productivity and research: build a Project that produces a verified decision brief and reusable workflow.
- Business operations: design a supervised GPT/app or Work workflow with permissions and approval gates.
- Software engineering: use Codex on a repository to implement and test a bounded feature or bug fix.
- Developer application: design or build an API-backed feature with structured output, tools, tests, and monitoring.
- Creator workflow: produce a complete content package using text, research, images, files, and a quality rubric.
Your project brief must include user, problem, starting state, desired outcome, non-goals, data classification, tools, risks, deliverables, verification, and definition of done. Choose a project small enough to finish and deep enough to demonstrate judgment.
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