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EvidentLoop

Infrastructure for trustworthy AI coding workflows — CrossReview + Sopify

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The Problem

AI coding assistants are effective producers. But they're not reliable self-verifiers.

A shared session accumulates local assumptions, abandoned approaches, and retry artifacts — each reinforcing "the previous call was right." When review reuses that context, it inherits the author's framing instead of independently re-deriving correctness.

You can verify every diff and still miss the bigger picture.

Philosophy

Every meaningful AI coding task is a closed loop:

produce → verify → accumulate → produce

  • Loop-first — No step is done until independently verified
  • Wire-composable — Loops connect through machine contracts, not chat history
  • Surface-shared — Knowledge persists across sessions, models, and hosts

CrossReview implements verify. Sopify implements wire and surface.

Two Products, One Loop

Loop Role What It Does Project
verify Context-isolated cross-review — same model, clean session, independent second pass CrossReview
wire + surface Full workflow orchestration — checkpoints, blueprints, traceable decision chains Sopify

CrossReview — Verification primitive for AI coding. Same model, clean session, independent second pass on your output. Atomic and composable — runs standalone or as a verification step inside broader workflows.

Sopify — AI coding workflow orchestration layer. Manages state, plans, and decisions across the full lifecycle — checkpoints when facts are missing, resumes from state, not from scratch. CrossReview is designed to slot in as its verification step.


CrossReview is the verify — atomic, isolated, independent.
Sopify is the wire + surface — connecting loops, accumulating knowledge.
Together, they close the loop.

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  1. sopify sopify Public

    按任务复杂度推进 AI 编程流程,让关键决策可追踪、产出质量可验证,并把计划、审查和历史沉淀为项目资产

    Python 87 4

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