Text-to-Text Prompt Techniques

Task Specification:

  • Clearly state what you want the LLM to do to get precise answers.

Contextual Guidance:

  • Give detailed directions to keep the LLM's output on the right topic.

Domain Expertise:

  • Use specific jargon to help the LLM create accurate content in specialized areas.

Bias Mitigation:

  • Include clear instructions to avoid biased responses.

Framing:

  • Define the prompt's limits to keep the LLM's responses within the desired scope.

Zero-shot Prompting:

  • Design prompts that let AI models respond well even without previous examples.

User Feedback Loop:

  • Improve prompts by revising them based on the LLM’s answers and user comments.

Few-shot Prompting:

  • Use example cases in your prompt to train the LLM for better results on similar tasks.

PreviousCommon Tools and Platforms for Prompt EngineeringNextInterview Pattern Approach

Last updated