> People who like to have a go at langchain seem to argue that this is “so trivial” you could just do it yourself… but also not flexible enough, so you should do it yourself.

At least for now and for the most popular usecases, this _is_ true. The framework seems as though it was written by people who had not actually done ML work prior to GPT4's announcement. Regardless if that's true or not; the whole point of a highly robust large language model is to be so robust that _every_ problem you have is easily defined as a formatted string.

The whole idea of deep learning is you don't need rules engines and coded abstractions, just English or whatever other modality people are comfortable communicating with. This is not necessarily true for all such cases at the moment. RAG needs to do a semantic search before formatting the string, for instance. But as we go forward and models get even more robust and advanced, the need for any abstraction other than plain language goes to zero.