Some context:I posted earlier versions of this idea in r/OpenTelemetry (trace topology angle) and r/aiengineering (Telegram bot PoC). Main pushback was around span attributes vs topology-level signals, and whether tool permissions alone are enough. That feedback shaped this version deterministic, no LLM in the loop, fail-closed by default.
Most AI failures I’ve seen weren’t hallucinations or wrong answers.
They happened when systems executed actions by default.
This project explores the idea of a “Judgment Boundary”:
explicitly separating judgment from execution, and treating
STOP / HOLD as first-class outcomes.
Instead of optimizing answer accuracy, it focuses on:
- preventing default execution,
- making non-execution observable,
- and preserving human responsibility.
The repo is documentation-first and meant as a public map
for people working on agents, governance, or execution safety.
Feedback welcome especially from platform and infra folks.
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