A full practical sequence to test AI apps before launch — risk mapping, journeys, model probes, safety, fallbacks, severity, and ship/wait/block gates.
Read →A full AI app launch checklist covering journeys, model behavior, safety, fallbacks, ownership, and how to use it without false confidence.
Read →How to use an AI launch risk self-check honestly, interpret urgency, avoid false precision, and turn the result into next actions.
Read →Clear ship, wait, or block criteria for AI features — adversarial coverage, data exposure, fallbacks, write gates, ownership, and examples.
Read →A practical guide to testing RAG hallucinations: grounding accuracy, retrieval misses, citation honesty, tenant isolation, and fallback behavior—without turning a demo into proof.
Read →A practical checklist for prompt injection testing: what probes to run, what to measure, how to define pass/fail, and how to connect results to product release decisions.
Read →A product-first guide to testing AI agents with tools: approval gates, schema validation, partial failures, rollback behavior, and “what the user sees” on errors.
Read →A practical comparison of LLM evals and product QA for AI apps—where each succeeds, where each misses, and how to connect both to release gates and severity-ranked findings.
Read →Free tools first, or a triage call if you want an independent pass before launch.