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RAG explicado: cómo darle a un LLM tu propia información

Un modelo de lenguaje sabe mucho del mundo, pero no sabe nada de tu empresa : tus manuales, tus políticas, tus productos.

  • RAG technique allows LLMs to access and use specific company information
  • Indexes documents into numerical embeddings stored in vector databases
  • System prompt instructs model to use provided context for responses

How I Built Memory for a Local AI Companion Without Sending Chats to a Server

A chatbot can sound convincing for five minutes without remembering anything. Then you mention the job interview you were stressed about last week, the name of your dog, or a small detail from a…

  • Chat history and long-term memory separated for efficiency
  • SQLite database stores memories per character without merging
  • Vector embeddings enable semantic search for related memories

Stop chasing fads. Operate Claude like a startup founder.

I am running an AI-native startup. Early on though, I would spend so much time staying ahead of every new AI hot take that I lost focus on what I needed to do to move the company forward.

  • Focus on core business needs, not AI trends
  • Use Claude's three layers: Extend, API call, Embed
  • Implement prompt caching to reduce costs significantly

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