daBongo LMS AI Training Courses

← Back to Course

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:

  1. Productivity and research: build a Project that produces a verified decision brief and reusable workflow.
  2. Business operations: design a supervised GPT/app or Work workflow with permissions and approval gates.
  3. Software engineering: use Codex on a repository to implement and test a bounded feature or bug fix.
  4. Developer application: design or build an API-backed feature with structured output, tools, tests, and monitoring.
  5. 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.

Enroll to continue this lesson.

The preview above shows the lesson objectives and opening lesson content. Enroll to view the full lesson, complete the practice work, and take the lesson quiz.

Log In / Create Account Back to Course

← Back to Course