AI Model Selection, Tasks, and Responsible Use Cases
Lesson 3: Build, Buy, Configure, or Avoid
Lesson Objectives
By the end of this lesson, students should be able to:
- Compare simple prompting, product features, workflow automation, and custom model work.
- Identify when custom training is unnecessary.
- Include maintenance and cost in tool choice.
Lesson Content
Not every task needs a custom model. Many tasks can be handled with a good prompt, a saved template, a built-in product feature, a retrieval workflow, or a simple database rule. Custom training or advanced model work should have a strong reason: enough data, repeated task value, measurable improvement, and ownership for maintenance.
Buying or configuring a tool can be smarter than building. Building can be smarter when the workflow is unique, the data is proprietary, or the quality bar requires control. Avoiding AI is also a valid professional decision when the task is high-risk, data is poor, or rules are clear enough without AI.
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.