Elena Fontaine

LLMs need fresh data at runtime to avoid confident hallucinations about recent changes.

Vendor hallucination rates measure different things, making them unreliable procurement signals.

Retrieval-augmented systems close a 60-point accuracy gap that unaided language models cannot cross.

When agents blend conflicting sources, the problem sits in the architecture, not the prompt.

Agentic retrieval beats single-shot on complex reasoning by 55 points.

Most AI research agents search once and call it done, missing contradictions and outdated claims.

Agents stall in production without reliable APIs for multi-step research and retrieval.

Semantic search matches intent through geometry, not keywords.

Retrieval beats fine-tuning for enterprise AI deployment speed and cost.

Learn the three-stage architecture that makes production AI systems work reliably.