Google's 9 Hour AI Prompt Engineering Course In 20 Minutes

20 minutesIntermediateBuilderTina HuangPrompt Engineering

Tina Huang. Tina presents a five-part task/context/references/evaluate/iterate framework and four named iteration moves. Those elements can help you draft a candidate schema, but the agent and chain-of-thought examples reflect the course's time and context. Test any extracted pattern on representative cases before adding it to an approved library.

AI Expert note

Use the framework as historical course material to test, not as a complete library standard. Approval should depend on your current model, policy, data boundary and evaluation results.

What you should get from this

Extract a candidate prompt structure, then add ownership, versioning, evaluation, limits and fallback fields before review.

Watch or know first

Comfortable prompting on your own; this is about turning that into shared assets.

Last reviewed: Aug 11, 2026

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