Local LLMs and workstation agents: Part 2

From the guy who said "Buy a GPU," "Opensource AI Must Win," and "Local AI FTW": this session shows what you build around the models running locally so agents can actually be effective and efficient when using local models.

A local chatbot gives you private text generation. A useful agent needs a system around it: search, scraping, traces, document ingestion, agentic harness integration, and other practical components. The focus of this workshop is setup, not hardware. We will walk through the practical pieces that turn local inference from a model endpoint into the reasoning layer inside a real workflow.

The live demo target will be a 2x RTX PRO 6000 Blackwell machine running models locally and using it across different agentic harnesses. The goal is to show how Local AI can be more than private and offline: it can be useful, inspectable, controllable, and built into infrastructure you actually own.

Attendees should leave with a practical mental model for building Local AI systems that can read, search, cite, act, and evaluate themselves.