Prompt engineering by Quick component: Patterns and pitfalls
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Part 2 of our Amazon Quick prompt engineering series goes component by component. Learn the prompt patterns that get the best results from Amazon Quick Research, Quick Flows, Quick Sight, chat agents, and action integrations, plus the common pitfalls to avoid.
In Part 1 of this series, we covered the foundational principles of prompt engineering in Amazon Quick: specificity, context-setting, few-shot examples, and the CRISPE framework for complex requests. Those principles apply universally. In this post, we go component by component, showing you how each Quick capability interprets prompts differently and what patterns get the best results from each one. You might use Amazon Quick Research for market analysis, Amazon Quick Flows for automation,…
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