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The best known examples of these at the time I write this are OpenAI's ChatGPT models, which can be accessed through an API at a cost proportional to the number of words in the prompt and response.
One interesting technique combines text generation and "embedding" (i.e. generating a vector representation of a document) to create a chatbot that can search a corpus of documents.
Simon Willison - Q&A against your documentation with GPT3, embeddings and Datasette
Writing an LLM Agent in 50 Lines of Code
Martin Fowler: Example of LLM prompting for programming
Ed Frank - Rebuttal to Society’s Tech Debt & Software’s Gutenberg Moment