5 Things I Learned Building Qdrant + RAG That Aren't in the Documentation
5 Things I Learned Building Qdrant + RAG That Aren’t in the Documentation You want to design a Qdrant + RAG system. This means taking your documents, breaking them into pieces, converting them to vectors, storing them in a vector database, and pulling them out when needed using “cosine similarity.” So you’re not teaching the system anything - you’re just building your own smarter DB system. Wait a minute, wouldn’t it be pretty much the same if you just trained an LLM? Yes, exactly… Our learning mechanism isn’t that different either. How many of us question what we’ve learned and go after something better? Or how many of us reject information we’ve already learned? Answer: none of us. ...