Berlin · ex-COO of Fyrfeed (acquired 2024) · founder at ai1 Ventures
I build evidence-bounded AI systems: agents that must cite their sources, pass eval gates in CI, and escalate to a human when they can't back a claim. Policy lives in code, not in prompts — a model can argue, but it can't talk its way past a verifier.
Right now that means a fully autonomous content pipeline shipping short-form video daily (research → script → render → schedule, built on Claude Code), an installable MCP server for running AI transformation programs, and the repos below.
| ai-transformation-90 | A transformation copilot for the first 90 days of an AI program — playbook, costed business cases, working prototypes, and the method itself as an MCP server with evidence-gated scoring. Swap in your own org and it runs your program. |
| snakeoil-radar | A reaction radar for viral health misinformation, as a Claude Code skill — finds high-reach claims, checks them against PubMed fail-closed, never asserts what it can't cite. |
| know-no-hearsay | A reference architecture for evidence-bounded generative media — no pipeline step may increase the epistemic strength of a claim without evidence. |
| sorting-hat | An LLM-classified document inbox: drop scans into one folder, get named, filed paperwork out. Boring, useful, runs daily on my machine. |
| inanimatus | LLM-driven CAD, done declaratively — geometry-tested CadQuery models from dimensioned specs, as a documented method + Claude Code skill. |
The common thread: grounded beats plausible. Every one of these rejects output it cannot back — with tests in CI to prove it.
📫 LinkedIn · 🎬 the daily-shipping pipeline in action: @dabigredbutton