At the top of this page is an interesting experiment in using LLMs (large language models, like ChatGPT) to explore the content of a library of content. In this case, my blog. It scans across all of the blog posts and tries to figure out which ones are relevant, then use the relevant ones to construct an answer to the query/task. It's a great way for people to find content that I might have written years ago, or convert what I've written into easier to understand language. It's much better than keywords for finding certain content, and it synthesizes the content to smaller summaries for the reader.
The service uses lambdas (on AWS) that scan through pre-generated summaries of the articles (or the whole article if it's short enough) to identify the relevant posts. The prompt for this is:

