Hey @rosie ,
The prompt engineering techniques I found quite interesting are:
1. ReAct Prompting:
How it works: It works by breaking down the task into series of steps & then prompting LLM to explain its reasoning & an action for each step. The reasoning trace is a description of the LLM’s thought process for each step & the action is specific thing that LLM needs to do to complete the step.
Potential impact: By using this prompting, we can tell the LLM to perform complex tasks that would be difficult to program for.
Useful resource: Unlocking the Power of React Prompting
2. Self-Consistency Prompting:
How it works: It works by guiding the generation of content by instructing AI model to provide responses that are consistent, by maintaining coherence/continuity by adhering to specific context/constraint.
Potential impact: This ensures the content the LLM produces to be cohesive & on-topic.
Useful resource: Master Prompting Techniques: Self-Consistency Prompting