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Like you shouldn't lock yourself to a specific cloud provider, you shouldn't lock yourself to a LLM as a service provider.

You could build your tools with a generic access to the best LLMs of the market. Today Claude is great, but perhaps Gemini, Mistral, ChatGPT, Command-R, or some wizard-dolphin-mixtral-carrots-merge-v3 can be descent replacements.

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Totally, spending time developing the muscles to build more advanced RAG workflows is first and foremost a data modeling and data engineering challenge -- developing the hierarchical data modeling expertise, taking advantage of the structure and flexibility of the document model, chunking, and real time memory requirements combined with the power of vector embeddings and advanced query and filter capabilities is a skill that will last, irrespective of the popular model, service provider, cloud platform or framework du jour.

> is a skill that will last

As a user, why would I bother to learn these things, aside from a hobby? If it works well, I expect a product to come along soon.

You wouldn't bother as consumer. The advice above was for developers I think

Where do you start learning these workflows, as in do you have any you would recommend?

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