Build a QA Wall That Catches Bad AI Outputs Before Clients See Them

Before you scale AI content delivery, install a three-layer QA Wall that catches bad outputs with golden-set tests, lightweight LLM judges, and strategic human sampling—plus spend guards that prevent runaway costs while you're offline. Kira shares how a fabricated citation that reached 11,000 LinkedIn followers taught her to build redundancy at every level, from automated heuristics that catch PII and broken JSON to dual-judge systems that escalate disagreements to humans. You'll get the exact golden-set template, judge rubric, sampling math, and Slack alert payloads that keep clients happy and your margins intact.