This person runs their primary AI infrastructure on a Bosgame M5 Strix Halo (Ryzen AI Max+ 395, Radeon 8060S iGPU, 128GB LPDDR5X unified memory with 96GB reserved for the iGPU). Everything is accessed through one nominated Telegram chat, so the whole stack is usable from a phone.
Eight workflows run daily, each with a separate agent and persona: personal reflection and diet tracking, health and fitness monitoring, music gig tracking, a finance 'board of advisors', coding and automation scripting for work in a media organisation, research and literature analysis, PDF/spreadsheet/Drive document processing, and diary/travel planning. Because the agents and models are separate, they can repair each other when one breaks, an approach adopted after a less reliable single stack kept failing on upgrades.
The owner describes this as primary infrastructure rather than a hobby. The main draw is privacy and offline access for financial and personal records, and avoiding the loss of long chat history they experienced when a cloud provider wiped conversations. Local file management, document processing and private work are where local wins outright; creative writing and complex reasoning still go to Claude Pro, and Claude Code is used for a few structured tasks while the raw data stays local. The acknowledged downsides are the hardware cost, dense-model speed, and context-window management, which they are still learning.
Reported anonymously by an r/LocalLLM contributor · score 2