An overview of how to transition from simply "talking" to your local model to connecting it to your personal data and local apps.
A guide to Retrieval-Augmented Generation (RAG), which allows your local model to search through your private PDFs, notes, and emails for instant answers.
A look at the "hidden" part of RAG: how tools like ChromaDB or lanceDB store your files as mathematical points so the AI can find them.
A deeper dive into "Vision-Language Models" (VLMs) that allow you to ask your local AI questions about your personal photo library or screenshots.
The most advanced level: using tools like n8n or Autogen to let your local AI actually file your taxes, organize your folders, or send draft emails.