In press and marketing, terms like “agent-based” and “agentic” are often used interchangeably, creating confusion even among seasoned technologists. This distinction isn’t just semantic nitpicking—understanding the difference has profound implications for how we build, deploy, and govern AI systems.

When tuning AI models, particularly Retrieval-Augmented Generation (RAG) systems, many teams focus either overindex or confuse accuracy and precision. This fundamental misunderstanding leads to systems that either hit near the mark occasionally but scatter wildly in practice, or consistently miss the mark (or hallucinate) in the same way repeatedly.