Implementing advanced prompt engineering with Amazon Bedrock
Machine Learning Blog
This article provides an overview of advanced prompt engineering techniques for Amazon Bedrock, a fully managed service that offers high-performing foundation models (FMs) from leading AI companies. It covers methods like the COSTAR prompting framework, chain-of-thought prompting, Tree of Thoughts prompting, prompt chaining, prompt catalogs, and techniques to mitigate prompt misuses.
Specifically, the article covers:
- COSTAR framework for crafting effective prompts
- Chain-of-thought (CoT) prompting for improving reasoning abilities
- Tree of Thoughts (ToT) prompting for breaking down complex problems
- Prompt chaining to orchestrate sequences of prompts and models
- Prompt catalogs and templates for reusability and consistency
- Common prompt misuses like prompt injection, prompt leaking, and jailbreaking
- Prompt defense techniques like guardrails and unique delimiters
- Best practices for prompt engineering
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