@julianvelez712: Five RAG architectures worth knowing in 2026, and what each one actually costs you. 𝗛𝘆𝗯𝗿𝗶𝗱 𝗥𝗔𝗚 Vectors find meaning. BM25 finds exact strings. Ask a pure semantic index for policy AB-4471 and it returns five neighboring policies. Running both and fusing the rankings is an afternoon of work and removes a whole category of complaints. 𝗚𝗿𝗮𝗽𝗵𝗥𝗔𝗚 For questions that live in relationships, not in any single chunk. Two hop connections, supplier networks, org structures. The catch: you now own entity resolution, and that has eaten entire quarters on teams I have worked with. 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 Retrieval becomes a loop instead of a step. Plan, call tools, check, go again. Powerful, and also where predictable latency goes to die. Cap the iterations and log every planner decision. 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝘃𝗲 𝗥𝗔𝗚 A grader scores retrieved docs before the model sees them. Bad ones get rewritten or fall back to search. Retrieving nothing beats retrieving something irrelevant that the model then summarizes faithfully. In healthcare and finance that gap is not academic. 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗥𝗔𝗚 Enterprise knowledge is scanned forms, dashboards, and tables where layout carries the meaning. Text extraction deletes exactly the signal you needed. These stack in practice. Hybrid underneath, grader on the queries that matter, agent loop only for traffic that earns it. Every extra box costs latency and adds a new way to fail at 2am. Where does Agentic RAG end and a normal agent with a retrieval tool begin? I draw that line differently depending on the week. Save this one for your next architecture review. #programming #coding #developer #software #softwareengineer pb codewithbrij

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Sunday 20 September 2026 12:04:51 GMT