Selfhosted on Hullabalooing

I Pushed Local LLMs Harder. Here's What Two Models Actually Did.

Mon, 02 Mar 2026 00:00:00 -0700

In Part 1 of this series, I set up Claude Code against local LLMs on dual MI60 GPUs and watched it scaffold a Flask application from scratch. Small tasks worked. Complex ones did not. I ended with three ideas I wanted to test: running a dense model, trying Claude Code’s agent teams feature, and building a persistent memory layer for coding sessions.

I started the experiment that mattered most: giving a local LLM a project with real scope and seeing what happened. I ran the same project against two different models. The results were instructive, and not in the direction I expected.

I Ran Claude Code on Local LLMs for a Month. Here's What Worked for Me.

Mon, 16 Feb 2026 00:00:00 +0000

I have been running local LLMs on dual AMD MI60 GPUs for over a year, and recently pointed Claude Code at them to see how close I could get to frontier-quality agentic coding on my own hardware. I wanted to know: how close can local models actually get to Anthropic’s Claude for building real software?

This is the first post in a series documenting that experiment. Future posts will cover specific agentic coding sessions, hardware and model setup, and the tools I am building to close the gap.

I Built an AI Health Coach That Actually Knows Me

Wed, 11 Feb 2026 00:00:00 -0700

Every health app wants to coach you, but none of them know you. They do not know your baseline. They do not know that your blood pressure spikes after certain meals, or that your ketones tank when you are stressed. They offer generic advice based on population averages and call it personalized.

So I built my own. It runs on my infrastructure, stores everything in a time-series database I control, and uses Claude to understand what I am eating, estimate the macros, and give me context on every measurement I log. Not generic advice. Insights based on my data.