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multi-agent AI systems
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Timeline

Retrieval-Augmented Generation2026-04-22

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

Retrieval-Augmented Generation2026-04-21

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

Retrieval-Augmented Generation2026-04-16

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

Retrieval-Augmented Generation2026-04-06

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

Retrieval-Augmented Generation2026-04-03

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

multi-agent AI systems2026-03-25

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

Retrieval-Augmented Generation2026-03-25

Developer shares cautionary tale about RAG system failure at production scale

multi-agent AI systems2026-03-24

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

multi-agent AI systems2026-03-18

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

multi-agent AI systems2026-03-18

Three-agent architecture deployed for real-time fraud detection

Ecosystem

multi-agent AI systems

usesMesa1 src
usesRetrieval-Augmented Generation1 src
useslarge language models1 src
usesXGBoost1 src

Retrieval-Augmented Generation

useslarge language models6 src
usesFine-Tuning5 src
usesGoogle4 src
usesChunking Strategy1 src
usesContrastive Learning1 src
usesLangChain1 src

Evidence (2 articles)