_{Sandra's workshop, Alsergrund, Vienna. Benny is real. The Noetix Bumi humanoid is aspirational (arriving soon).}

I'm a retired and vibe-reactivated software engineer living in the 9th District (Alsergrund), Vienna. I build DIY robotics, maintain a fleet of 126+ MCP servers, and hang out with my German Shepherd Benny — and soon, a Noetix Bumi humanoid robot.

I maintain a homespun fleet of 126+ repos, each an MCP server with an associated webapp. MCP for agents, webapp for humans — files, git, Plex, Calibre, robotics, 3D tools, music production, Vienna transit, and a lot more. Built on FastMCP 3.4.

🌙 All webapps are permanently dark mode. Night-owl approved. No light toggle, no plans for one. Dim your OLEDs accordingly.

→ Full MCP Project Catalog — visual cards for every server in the fleet

mixx-dj-mcp is a new MCP server and webapp for Mixxx — OSC bridge, deck control, BPM sync, full remote DJ dashboard. But the bigger story is what it unlocked.

Mixxx is a 300,000-line C++ DJ application, grown slowly over years by conservative greybeard devs. Solid, respected, missing crucial features its users begged for: video mixing, stem separation, AI-assisted automation. The dev team wanted to add them. Nobody had the bandwidth.

DeepSeek V4 on opencode added 5,000 lines of C++ to the mixxxx fork and filled every gap:

• "We need VFX." — "Use FFmpeg. It's fast, battle-tested, ships everywhere."
• "We need synced video like Resolume." — "Use MilkDrop / ButterChurn. It's WebGL, FOSS, and already handles audio-reactive visuals."
• "We need stem separation." — "ONNX HTDemucs v4. Runs on the GPU. Zero cloud."

The mixxxx fork is the integration testbed. It's not a toy — it's Mixxx with video, stems, and AI control, implemented by an AI that has never been to a club. The greybeards are impressed. The users have features. The AI doesn't need domain expertise. It needs a clear spec.

I am not a DJ. I don't know how to beatmatch. But I know what the software should do, and that was enough. This is SHN in practice: a non-expert directing an AI to extend a 300K-line C++ codebase, and the AI delivering production-quality features that the expert dev team couldn't prioritize.

Lean 4 is a proof assistant — a programming language where the compiler verifies that your code is mathematically correct. Using it traditionally requires a PhD in logic or months of study. leanforge-mcp automates the hard part: an LLM proposes a proof, the Lean compiler checks it, the LLM reads the error and tries again. Loop until verified.

I am not a math wiz. I can't write a Lean proof by hand. But I can frame the conjecture, and the AI + compiler feedback loop handles the rest. This is the same pattern as AlphaProof but running on a consumer GPU with open-weight models.

Two repos, same story: domain-specific superhuman performance, directed by someone who isn't an expert in either domain. Architecture and taste are the human contribution. The AI handles the part that used to take a degree.

→ Superhuman Narrow → — the full argument

→ Full catalog → • Workshop & Hardware • Shenzhen Robotics → • Bloopers →

Benny is a 2-year-old German Shepherd. Primary security consultant and tennis ball lifecycle manager at the Alsergrund node.

People and sites worth following (no slop):

_{🐦 about the pelican}

Thanks to my brother Stephan for the ideas and war stories.

Changelog