#305 RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI, Adjunct Professor at Stanford University, Inventor of RAG

133 snips

Jun 9, 2025

Douwe Kiela, CEO at Contextual AI and Stanford Adjunct Professor, delves into the evolution of Retrieval Augmented Generation (RAG). He debunks myths about RAG's decline, asserting its relevance in AI. The conversation highlights the integration of vector databases with large language models for high-stakes accuracy. Kiela also emphasizes the need for sophisticated RAG systems and the role of feedback loops in enhancing model performance. With AI agents on the rise, he explores their potential for dynamic reasoning, paving the way for innovative applications in various industries.

Ask episode

AI Snips

Chapters

Transcript

Episode notes

ADVICE

Prioritize Metadata and Entitlements

Focus on maintaining high-quality metadata and entitlements models for complex data governance.
Centralizing role-based access control saves big headaches when handling multiple disparate data sources.

ADVICE

Don’t DIY Your RAG Platform

Avoid building your own RAG platform from scratch.
Use proven platforms to focus on building valuable business applications instead of infrastructure.

INSIGHT

Re-ranker Enhances Retrieval Precision

A re-ranker refines initial retrieval results with a smarter model that can follow instructions.
This enables prioritizing data by preferences such as recency, source trustworthiness, and document type.

Get the Snipd Podcast app to discover more snips from this episode

Get the app

Retrieval Augmented Generation (RAG) continues to be a foundational approach in AI despite claims of its demise. While some marketing narratives suggest RAG is being replaced by fine-tuning or long context windows, these technologies are actually complementary rather than competitive. But how do you build a truly effective RAG system that delivers accurate results in high-stakes environments? What separates a basic RAG implementation from an enterprise-grade solution that can handle complex queries across disparate data sources? And with the rise of AI agents, how will RAG evolve to support more dynamic reasoning capabilities?

Douwe Kiela is the CEO and co-founder of Contextual AI, a company at the forefront of next-generation language model development. He also serves as an Adjunct Professor in Symbolic Systems at Stanford University, where he contributes to advancing the theoretical and practical understanding of AI systems.

Before founding Contextual AI, Douwe was the Head of Research at Hugging Face, where he led groundbreaking efforts in natural language processing and machine learning. Prior to that, he was a Research Scientist and Research Lead at Meta’s FAIR (Fundamental AI Research) team, where he played a pivotal role in developing Retrieval-Augmented Generation (RAG)—a paradigm-shifting innovation in AI that combines retrieval systems with generative models for more grounded and contextually aware responses.

In the episode, Richie and Douwe explore the misconceptions around the death of Retrieval Augmented Generation (RAG), the evolution to RAG 2.0, its applications in high-stakes industries, the importance of metadata and entitlements in data governance, the potential of agentic systems in enterprise settings, and much more.

Links Mentioned in the Show:

New to DataCamp?

Learn on the go using the DataCamp mobile app
Empower your business with world-class data and AI skills with DataCamp for business