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Local LLMs and workstation agents: Part 2

Conference Context

Session Description

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.

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Synthesized Breakdown

Local LLMs and workstation agents: Part 2 ## Conference Context - Date/time: 2026-06-29 · 12:10pm-1:10pm - Track/room: Workshops Day 1 · Track 6 - Speaker(s): Ahmad Osman - Session type/status: workshop · confirmed - Track: Workshops Day 1 - Room: Track 6 - Session type: workshop - Status: confirmed ## Session Description 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.

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