New RAG paradigm with iterative retrieval at multiple reasoning steps achieves 15-20% accuracy gain on HotpotQA

Positioned as go-to technique for dynamic, fact-heavy applications with frequently changing information

Research exposed a critical vulnerability where just 5 poisoned documents can corrupt RAG systems.

Clarification article published explaining distinction between RAG and fine-tuning for LLM applications

Publication of a framework moving RAG systems from proof-of-concept to production, outlining anti-patterns and a five-pillar architecture.

Ethan Mollick declared the end of the 'RAG era' as dominant paradigm for AI agents

First comprehensive empirical benchmark for deploying multi-agent LLM systems in production financial environments published

Development of multi-agent architecture for improving LLM debate and reasoning

Technical framework published outlining four architecture patterns and a three-layer governance model for enterprise deployment

Three-agent architecture deployed for real-time fraud detection