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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.

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