Flow
Assessment identity
Section titled “Assessment identity”- Repository:
kinra-ai/flow - Revision:
4cc53682493850098dd0ef1ff59f57cb8c5044ef - Assessment date: 2026-08-09
- Evidence class: bounded maintainer attestation; product and customer data remain private
Domain
Section titled “Domain”Flow coordinates a manufacturing account whose customer intent, commercial facts, and production reality arrive through differently authoritative and sometimes conflicting sources.
Mechanisms observed
Section titled “Mechanisms observed”- outside arrivals remain immutable evidence until a reviewed change advances the account;
- the account carries a monotonically advancing revision;
- proposed changes cite evidence, exact before and after values, rationale, uncertainty, and the observed revision;
- application refuses stale revision, incomplete provenance, or an invalid mutation and advances the coherent account atomically;
- current fields retain evidence and change ancestry;
- source authority is scoped rather than inherited from a system’s importance;
- generated, sent, acknowledged, and incorporated publication states remain separate;
- returned outside contributions enter as evidence; and
- deterministic reads expose current truth and provenance to the operator and AI Peer without requiring storage reconstruction.
What Flow paid to teach
Section titled “What Flow paid to teach”Flow made the delta the durable product output. The system can answer three different questions without collapsing them:
- What is currently believed?
- What changed and why?
- What exact account crossed an outside boundary at that time?
It also demonstrated that an interface is not the reconciliation boundary. A general operator reconciliation client was built and removed after use showed that the operating AI Peer needed governed reads, while outside people needed only focused projections.
Limits
Section titled “Limits”Flow’s customer-account schema, command catalog, role names, repository ledger, and specific review policy are not portable requirements. The implementation does not prove that Git is the right storage substrate for a high-concurrency or large-scale truth system. Outside adoption and business value remain separate claims from mechanical correctness.