Monday, 23rd January 2023
I think prompt engineering can be divided into “context engineering”, selecting and preparing relevant context for a task, and “prompt programming”, writing clear instructions. For an LLM search application like Perplexity, both matter a lot, but only the final, presentation-oriented stage of the latter is vulnerable to being echoed.
It is very important to bear in mind that this is what large language models really do. Suppose we give an LLM the prompt “The first person to walk on the Moon was ”, and suppose it responds with “Neil Armstrong”. What are we really asking here? In an important sense, we are not really asking who was the first person to walk on the Moon. What we are really asking the model is the following question: Given the statistical distribution of words in the vast public corpus of (English) text, what words are most likely to follow the sequence “The first person to walk on the Moon was ”? A good reply to this question is “Neil Armstrong”.