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Cross-AI Workflowsexpert · ~240 min

Implement It Twice on Purpose — a Cross-AI Differential Harness That Finds the Hole in Your Own Spec

When one AI writes your billing rule and then writes the tests for that rule, what exactly did the green test suite prove?

This project answers that uncomfortable question by having a second AI from a different company implement the same written specification with no sight of the first, and then letting a deterministic harness hunt for a single input where the two disagree — because every disagreement is a sentence missing from your specification, and the tests written by the author of the code could never have found it.

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Implement It Twice on Purpose — a Cross-AI Differential Harness That Finds the Hole in Your Own Spec

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What you'll do

A differential verification harness you own for one money-critical business rule: a written specification with an explicit list of what it does not yet decide, a hand-computed golden table that outranks every AI in the project, two independent implementations produced from that specification by AI systems from different companies with no sight of each other, a pinned no-network sandbox both run inside, a property-based generator whose input domain comes from the specification and whose coverage of your named edge cases is asserted rather than assumed, a triage rule that resolves every disagreement against your specification instead of against a model's opinion, a permanent frozen corpus of every counterexample ever found, a set of invariant properties that catch the failures differential testing is structurally blind to, and an append-only ledger recording which tool produced which implementation, under which specification version, and who decided what correct meant.