Official Prompt Engineer Recommendations from Claude
Optimize LLM prompts with Claude's official techniques: clarity, XML tags, few-shot examples, and task chaining for superior AI outputs.
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As large language model (LLM) parameters increase and instruction-following capabilities improve, combined with recent Agent development increasingly relying on nodes like ReAct, Prompt optimization has become more important than ever before.
By chance, I came across a series of recommendations and best practices for Prompts in Claude’s official documentation, which are suitable for improving prompts. Or for AI-generated Prompts, you can also try using the rules below to guide optimization.
Overview of Core Principles
Several core principles summarized from Anthropic’s documentation, including but not limited to: