Prompt engineering fundamentals for Amazon Quick
Prompt engineering fundamentals for Amazon Quick
Prompt engineering determines the quality of Amazon Quick's AI responses to natural language requests. The first instalment of an official two-part series covers principles shared across components and reusable frameworks. It introduces CRISPE, covering context and constraints, roles and responsibilities, intent and inputs, steps and scope, and emphasises specificity, business context and examples over abstract descriptions.
Selection record
Not admittedSum of both 56 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：AWS博客讲Amazon Quick提示工程与AI功能
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: AWS Machine Learning Blog · aws.amazon.com