Independent builder · Vienna

Building the trust layer around AI agents.

I build open-source systems for the parts between a model response and a reliable agent: memory with provenance, independent outcome checks, executable public claims, behavior compatibility, runtime conditions, and inspectable state.

358Soul MCP tests
53Postcondition tests
70Proofspec tests
73Behaviorlock tests
36Agent Invariants tests
446ANIMA tests
269 + 131tool pages + guides
How the work is made

AI-assisted. Human-directed. Publicly inspectable.

I use capable models as research, coding, review, and testing collaborators. I choose the architecture, resolve conflicts, validate results, manage releases, and remain responsible for every public claim.

01 / DEFINE

Start from a failure mode

A product needs a narrow problem, a threat boundary, and a reason to exist beyond “another agent framework.”

02 / FALSIFY

Design evidence before polish

Tests, clean installs, real protocol handshakes, external registry checks, and explicit limitations come before the launch story.

03 / SHIP

Make verification easy

Source, releases, package metadata, documentation, CI, and live public checks let people inspect the work without trusting a screenshot.

Interested in reliable agent systems?

Open an issue for a concrete technical question, inspect the active repositories, or get in touch about collaboration and applied AI infrastructure.