RAG Architecture in Production: The Decisions That Actually Determine Quality
By Ama Senevirathne | Full-Stack Engineer | .NET / Angular / Agentic AI
Tags: rag, ai, software-architecture, llm, dotnet, vector-databases, information-retrieval
Retrieval-Augmented Generation (RAG) is the architecture that lets you ask an LLM questions about your own data — your internal documentation, your product knowledge base, your codebase, your customer records — without fine-tuning the model and without stuffing your entire corpus into the context window.
The concept is simple: before generating a response, retrieve the relevant documents; include them in the context; generate against real evidence rather than training-data approximations.
