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The 5 Principles of Effective AI Prompting - AI Foundations Day 3

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Principle 4: Evaluate Quality

2:41 with Travis Alstrand

Build verification into the prompt itself: chain-of-thought at three levels, self-evaluation checks, the debate pattern, and giving AI explicit permission to say "I don't know." Includes the 2026 update on when not to use chain-of-thought.

Vocabulary

  • Chain of thought — Asking a model to reason step-by-step before answering. Helps standard models; hurts reasoning models, which already do it internally.
  • Hallucination — When AI states something made up as if it were fact — an invented statistic, a study that doesn't exist. It generates what sounds likely, not what's verified.
  • Reasoning model — A model that works through a problem internally before answering (o3, o4-mini, Gemini Pro, Claude with extended thinking). Don't tell these how to think — just say clearly what you want.

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    The difference between an okay prompt and a great prompt is verification. 0:00
    Build self-checking into your prompts so the model catches its own mistakes before 0:01
    they reach you. 0:05
    Chain of thought prompting is to guide the model to think step-by-step before 0:08
    answering. 0:12
    You can accomplish this with three levels. 0:13
    Basic, think step-by-step before you answer. 0:16
    Guided. First, analyze the customer's complaint to 0:19
    identify the core issue. Then, consider 0:23
    which of our policies applies. Finally, draft a response that addresses 0:26

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