Building AI agents that don't hallucinate — Anil Pervaiz

Retrieval, guardrails, and human-in-the-loop design patterns that keep production AI agents grounded and trustworthy.

Hallucination is the wrong framing. The real question is: what does your agent do when it's uncertain?

Production AI agents fail gracefully. They cite sources, expose confidence scores, and escalate to humans at the right threshold — not as a bug fix, but as a core design pattern.

I walk through three architectures I've shipped: a citation-grounded RAG system for legal research, a multi-step approval agent for content publishing, and a real-time support bot that hands off with full context. Each pattern includes the retrieval setup, the guardrail layer, and the fallback UX that keeps users trusting the system even when the model is unsure.