This is an important distinction for teams adopting AI-assisted software development. At IT Path Solutions, we see independent validation as more than running a second review. Different reviewers should have clearly defined responsibilities, access boundaries, and evidence requirements. I'd also include seeded-defect testing to understand whether multiple reviewers can catch different classes of issues rather than simply agreeing on the same result.
Founder & CEO of Netsujo. Building trustworthy AI agent systems, with a focus on task boundaries, verification, and production reliability. Creator of Agent Role Contracts (ARC).
Thanks, Glen. I agree that seeded defects make reviewer independence testable rather than a matter of reviewer count.
I'd freeze the expected failure conditions before the review, then seed a small set of distinct defects: an out-of-scope write, a review tied to a stale artifact revision, and a false PASS supported by two readers using the same faulty evidence source.
Each reviewer would have a declared responsibility, access boundary, and evidence path. We'd record which defects each reviewer detected, which they missed, and whether a valid rejection actually stopped acceptance. Two green reviews against the same faulty source should not count as independent verification.
ARC currently checks the consistency of declared roles, scope, and review boundaries; it doesn't independently enforce runtime permissions or verify production effects. The seeded-defect and acceptance-gate tests would be a separate host/QC experiment.
From your team's experience, which class of seeded defect has been most revealing?
We're a place where coders share, stay up-to-date and grow their careers.
This is an important distinction for teams adopting AI-assisted software development. At IT Path Solutions, we see independent validation as more than running a second review. Different reviewers should have clearly defined responsibilities, access boundaries, and evidence requirements. I'd also include seeded-defect testing to understand whether multiple reviewers can catch different classes of issues rather than simply agreeing on the same result.
Thanks, Glen. I agree that seeded defects make reviewer independence testable rather than a matter of reviewer count.
I'd freeze the expected failure conditions before the review, then seed a small set of distinct defects: an out-of-scope write, a review tied to a stale artifact revision, and a false PASS supported by two readers using the same faulty evidence source.
Each reviewer would have a declared responsibility, access boundary, and evidence path. We'd record which defects each reviewer detected, which they missed, and whether a valid rejection actually stopped acceptance. Two green reviews against the same faulty source should not count as independent verification.
ARC currently checks the consistency of declared roles, scope, and review boundaries; it doesn't independently enforce runtime permissions or verify production effects. The seeded-defect and acceptance-gate tests would be a separate host/QC experiment.
From your team's experience, which class of seeded defect has been most revealing?