Bengaluru AI architect details 5-layer quality framework built across production systems

B KumaraSwamy, an AI quality architect based in Bengaluru, spent a year building and refining five production AI systems — including ARIA, an AI tutor targeting 1.6 billion children — and documented the quality failures he encountered along the way. He found that traditional binary software QA methods are inadequate for AI, which behaves probabilistically and can degrade silently without visible errors. To address this, he designed a five-layer quality architecture covering input validation, output evaluation, behavioral monitoring, cost controls, and adversarial resistance. One key example involved ARIA, which scored 94% on automated evaluations but only 22.2% on live Socratic compliance, highlighting how surface metrics can mask real-world failure. His framework includes tools such as prompt versioning with automatic rollback, RAG context quality thresholds, and circuit breakers that prevent hallucination when retrieved context is insufficient.