This paper presents four complementary harness engineering methods addressing the primary failure modes in AI collaboration harnesses: steel-quench (adversarial structural validation), source-grounding-audit (phantom claimdetection), harvest-loop (session-to-harness self-evolution), and sim-conductor (pre-deployment transfer validation). Applied to forge-harness itself: 10 structural defects resolved (4 S-grade, 4 A-grade), phantom claim rate reduced from 6.4% to 0% (3/47 → 0/44), 100% skill reachability confirmed across 4 external personas, 80% HIGH-grade external contribution absorption rate.