In my experience there's really only three true prompt engineering techniques:
- In Context Learning (providing examples, AKA one shot or few shot vs zero shot)
- Chain of Thought (telling it to think step by step)
- Structured output (telling it to produce output in a specified format like JSON)
Maybe you could add what this article calls Role Prompting to that. And RAG is its own thing where you're basically just having the model summarize the context you provide. But really everything else just boils down to tell it what you want to do in clear plain language.
- In Context Learning (providing examples, AKA one shot or few shot vs zero shot)
- Chain of Thought (telling it to think step by step)
- Structured output (telling it to produce output in a specified format like JSON)
Maybe you could add what this article calls Role Prompting to that. And RAG is its own thing where you're basically just having the model summarize the context you provide. But really everything else just boils down to tell it what you want to do in clear plain language.