How to Run AI Agents Fully Locally: Memory, Tools, and Models on Your Laptop
Last Updated on January 20, 2026 by Editorial Team
Author(s): Luna
Originally published on Towards AI.
How to Run AI Agents Fully Locally: Memory, Tools, and Models on Your Laptop
If you’ve ever tried to build an “agent” that helps with real work (not just a demo), you usually hit the same wall quickly: your data leaves the machine, costs become unpredictable, and the whole setup is hard to reproduce, even for yourself a week later.
This article presents an approach to creating a full-local agent stack that runs models, stores memory, and separates tools, allowing for predictable performance, privacy, and the ability to run operations offline. It discusses the architecture and components required to set up such a stack, including Agno for orchestration, SurrealDB for memory management, and Ollama for local LLM serving, along with practical use cases for user memory, document handling, and multimodal workflows using ComfyUI. The article underscores the significance of clear boundaries in the system to ensure safety and maintain a manageable codebase.
Read the full blog for free on Medium.
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