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Wilson Tan
Business problem:
AI Agents are often setup with instructions that look fine in setup but fail in production because there’s no post-setup QA: gaps, conflicts, and unsafe promises slip through, creating bad answers, compliance risk, and extra human handoffs. Teams end up debugging by visual checking instead of a repeatable checklist, for example:
  • Frequent failure modes: conflicting rules (e.g., “auto-detect language” vs. hardcoded first message), undefined placeholders/links, and broken URLs.
  • Operational gaps: pricing shared without delivery country, multi-currency in a single reply, vague handoff criteria, and missing refusal scripts (delivery/stock/payment).
  • Resulting impact: lower trust/adoption, higher support load, slower time-to-live, and escalations that could have been prevented.
Desired outcome:
Provide a one-click “Validate instructions” action (right after Agent setup/edit) that scans the instruction set, flags issues with clear severity, and offers concrete, safe-by-default fixe — so teams can trust AI Agents confidently.
  • Readiness checklist: must-haves for handoff rules, consent copy, stop/unsubscribe variants, product links, and technical notes on demand instructions.
  • UX & reporting: inline validator with warnings for conflicting instructions