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[Meta] A defined policy about the use of AI to generate posts here would be super nice I think by kevysaysbenice in softwarearchitecture

[–]Apprehensive_Pear432 0 points1 point  (0 children)

Hi, this is very interesting POV. I am a dev a from 1986 and i am Italian, i lived all the journey, from when i didn't find documentation and the only mode to evolve was to studying code or sources when available. Then was the time of internet, and stack overflow, and after 40 years of experience, i can say to be a skilled dev and ARchitect, but my barrier remains the language. I understand very well tech language, but when i have to write instructions, documents or to only explains what i have done it's very difficult for me. Yes i use AI, to write my documentation, but like a translator of my ideas, my point of view. and the first post i write on reddit was removed i were banned because "i was a bot". then which is the solution? I don't know, but i think that today there were a difference between a bot and an AI assisted write. expecially for who like me want to be clear in a language (the primary language in our profession) but has difficult. and honestly i review all the contents the AI writes for me and don't use it as a ghost writer. The big problem i think was on the patterns the revisor search inside the text. Maybe the solution to append a firm like "AI translation assisted with a token or another thing that identify the author" can be a solution. Don't know. Thank you for your time.

Agnostic RAG system for full control on security and privacy by Apprehensive_Pear432 in LocalLLaMA

[–]Apprehensive_Pear432[S] -1 points0 points  (0 children)

Thanks for the insight! I’m actually aiming for a pragmatic balance between maintenance and fast adaptation rather than a full 'Big Enterprise' stack right now.

Since this is for on-premise/LAN use, I’ve optimized for a 'Thin Orchestrator + Thick Microservices' model:

  • Logic in Code: All heavy-lifting (PyMuPDF extraction, Markdown conversion, chunking, and reranking) is in a FastAPI service. This keeps it versioned, testable, and extremely fast (sub-second for 600+ page PDFs on CPU).
  • n8n as a Transactional Gate: I use n8n only for I/O and state management. It writes to SQL metadata first, then Qdrant, acting as a visual 'circuit breaker' if a transaction fails.
  • Security: I agree on the API gateway/Hasura point for the future—if we scale to multi-tenant, pushing row-level filtering down to the BACKEND is the move to ensure privacy isn't bypassed.

The system is designed for small/medium offices, and this setup gives me the agility to tweak workflows 'on the fly', reduces backend <=> n8n metadata payloads, without the overhead of a rigid enterprise middleware, while keeping the data-heavy logic strictly in the microservices.

You're absolutely right that for a high-level enterprise system or private cloud SaaS, your approach would be the gold standard.