This article explores how to leverage Retrieval-Augmented Generation (RAG) to improve the performance of small language models (LLMs) on personal devices like MacBooks and Raspberry Pis. It discusses practical use cases, including code writing assistance, and highlights the challenges and opportunities of running LLMs locally.