A popular technique for interacting with Large Language Models such as ChatGPT is Few-Shot Prompting: providing a few examples of the desired task as part of the prompt, effectively providing the model a guide for how to structure its responses. Recently, I’ve taken this framework of “providing some examples” to ChatGPT to a larger scale — on the scale of many files often spanning multiple directories — and using that as a baseline to rapidly iterate on new ideas. This has worked surprisingly well across a range of domains, from working on reports to creating new codebases.
Example-Driven Development
Example-Driven Development
Example-Driven Development
A popular technique for interacting with Large Language Models such as ChatGPT is Few-Shot Prompting: providing a few examples of the desired task as part of the prompt, effectively providing the model a guide for how to structure its responses. Recently, I’ve taken this framework of “providing some examples” to ChatGPT to a larger scale — on the scale of many files often spanning multiple directories — and using that as a baseline to rapidly iterate on new ideas. This has worked surprisingly well across a range of domains, from working on reports to creating new codebases.