Video course · 5 chapters · 29 min · certificate
Why Your Copilot Outputs Feel Generic (And How to Fix Them)
Lisa Crosbie teaches why Copilot outputs feel generic and how to fix them with human judgment, work context, and critique. The chapters cover the AI doom loop, the thinking model, Work IQ, messy prompts, and a practical Copilot framework.
What you'll learn
- Recognize the AI doom loop and why generic content spreads.
- Explain the thinking model and why human judgment belongs at the end.
- Use Copilot's Work IQ layer with your own files, chats, and context.
- Apply your expertise to critique AI output instead of accepting it blindly.
- Prepare messy, human inputs instead of waiting for a perfect prompt.
- Review AI drafts against intent, structure, and voice before sharing.
Chapters
5 chapters · 28:59-
2:36
01Doom loop Free preview
Are you in an AI doom loop?
A short lesson on recognizing when AI content feels same and choosing curiosity over overwhelm.
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2:14
02Thinking model Members
Lesson 1: The thinking model
A lesson on placing human judgment at the end of AI work instead of relying only on the prompt.
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12:16
03Work IQ Members
Lesson 2: Intelligence on tap and Work IQ
A lesson on using AI beyond your expertise and grounding it in your actual work context.
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9:04
04Messy prompts Members
Lesson 3: You don't need a perfect prompt
A lesson on giving Copilot messy human context and examples instead of over-engineering prompts.
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2:49
05Copilot framework Members
Framework for using Copilot effectively
A closing framework to treat AI as a draft-and-review process, not a final-answer machine.
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