Practical Lessons from Deploying AI Assistants Based on LLMs
summary
How to deploy LLM-based AI assistants over large, scattered corporate knowledge bases using Retrieval-Augmented Generation (RAG). Covers preparing and structuring knowledge for RAG, choosing LLM and RAG configurations for accurate responses, monitoring and evaluating answer quality, implementing security/compliance guardrails, and applying cost monitoring and FinOps to keep solutions scalable.
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chapters (11)
- 0:00Introduction
- 2:32LLM chatbot use cases
- 5:21Advanced RAG components
- 8:09Building knowledge base
- 12:48RAG system evaluation
- 16:36RAG parameter tuning
- 20:50Reducing hallucinations
- 23:42Monitoring and error analysis
- 27:33LLM security
- 30:44Trust quality future
- 31:48Q&A
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