Boris Cherny, the creator of Claude Code, said something recently that matched my own experience: “I don’t prompt Claude anymore… my job is to write loops.” Peter Steinberger put it more bluntly: “You should be designing loops that prompt your agents.”

I’ve been building LLM-powered pipelines on top of Spring Integration for a while, and those two lines named what I had been doing without quite realizing it. My time had stopped going into prompts. It was going into the loops around them.

I’ve spent the last few weeks building a documentary video generation pipeline. A topic goes in (say: “Sankebetsu brown bear incident 1915 Hokkaido”) and a finished mp4 comes out (a ten-minute narrated documentary, 27 scenes, original visuals, voiced by a documentary-grade TTS), all running on a homelab cluster.

Between those two endpoints sits a chain of eight passes that hand off to each other. Several fan out to “do N things in parallel and aggregate.” Several produce artifacts measured in MB per scene that should not be shoved through a message broker. A few are the right place to put a human in the loop, where one minute of editorial review saves hours of GPU time downstream.

My AI assistant and I share the same brain. Not metaphorically, we literally read and write to the same knowledge base. When I update a project note in Emacs, Nabu (my AI) sees the change. When Nabu logs something it learned, I see it in my daily file. This post is about how it works.

How It Works#

Nabu connects to my self-hosted Matrix server and it has access to my org-roam knowledge base via an MCP server I built. But it’s not just access, it’s integration. Nabu treats org-roam as its source of truth: