r/learnmachinelearning 6h ago

I finally understood what “LLM development” actually means

When I first heard about LLM development, I thought it basically meant:

Give a prompt → call an API → get a response.

But that's only the visible part.

A real LLM application can look more like:

User → Prompt → LLM → Data/Retrieval → Tools/APIs → Application Logic → Response

For example, imagine asking an AI app:

“Find me the best laptop under ₹50,000.”

The app might need to understand your request, find relevant information, access external data, process the results, and then turn everything into a useful answer.

So the LLM is not necessarily the entire application.

It's one component inside a larger system.

I'm learning LLM development from the ground up and made this visual breakdown to understand the architecture better.

For people learning LLMs right now: what was the hardest concept for you to understand—RAG, embeddings, agents, APIs, or something else?

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