---
title: "Local LLMs and workstation agents: Part 2"
category: "talks"
date: "2026-06-29"
time: "12:10pm-1:10pm"
track: "Workshops Day 1"
room: "Track 6"
speakers: ["Ahmad Osman"]
sourceLabels: ["Official conference schedule", "Public YouTube metadata"]
scheduleTrack: "Workshops Day 1"
scheduleRoom: "Track 6"
scheduleLabels: ["Workshops Day 1", "Track 6", "workshop", "confirmed"]
---
# 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. 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.

## Media Evidence
No related AI Engineer channel video found yet.

## Evidence Graph
This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

### Media Signals
No linked video, transcript, or slide source has been attached yet.

### Agent Reading Notes
Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

## Transcript Status
No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

## People
- [[ahmad-osman]]

## Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.

## Synthesis
### 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.

### Speaker And Company Context
- [[ahmad-osman|Ahmad Osman]] — Founder & CEO at [[osmantic|Osmantic]].

### Topics Covered
- [[agent-security]]
- [[agentic-search]]

### Derived Links And Source Material

### Novel Concepts / Clever Methods
- No highlighted novel concept has been detected yet.

### Evidence Boundary
This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.