Human-in-the-loop (HITL) frameworks play a critical role in strengthening the reliability, accuracy and accountability of generative AI systems. This article outlines the practical benefits of HITL design, including improved validation, bias mitigation and contextual decision-making in real-world deployments.
This article explores the shift from retrieval-augmented generation (RAG) tutorials to production-ready architectures, focusing on latency, cost control, reliability and compliance in real-world deployments.