Uploaded November 2024 | Updated September 2026, 2 hours ago
Hey everyone! Thank you so much for watching the 109th episode of the Weaviate Podcast with Erika Cardenas! Erika, in collaboration with Leonie Monigatti, have recently published "What is Agentic RAG". This blog post that was even covered in VentureBeat with additional quotes from Weaviate Co-Founder and CEO Bob van Luijt! This podcast continues the discussion on all things Agentic RAG, covering the basics of Agents, how Agentic RAG changes the game compared to Vanilla RAG systems, Multi-Agent Systems and CrewAI / OpenAI Swarm, Letta, DSPy, and many more! The podcast also anchors by discussing Agentic Generative Feedback Loops and how we are using Agents to improve the quality and expand the capabilities of Generative Feedback Loops!
I hope you find the podcast interesting! As always we are more than happy to continue discussing these ideas with you or answer any questions you have! Thanks so much!
Chapters
0:00 Weaviate in NYC!
0:26 Welcome Erika!
1:22 What are Agents?
3:00 Agentic RAG vs. Vanilla RAG
5:28 Planning in Agents and o1
12:40 Multi-Agent Systems
15:25 Letta
18:57 Evals
21:00 Vertex Agent Builder and UX for Agents
22:21 LLM-as-Judge
25:45 Agentic Generative Feedback Loops
Here is the recording of Erika's talk in NYC! - youtube.com/watch?v=AOSjiXP1jmQ
To keep up to date with future Weaviate events, please see - weaviate.io/community/events
Weaviate Blog, "What is Agentic RAG": weaviate.io/blog/what-is-agentic-rag
VentureBeat, "How agentic RAG can be a game-changer for data procssing and retrieval": venturebeat.com/ai/how-agentic-rag-can-be-a-game-changer-for-data-processing-and-retrieval
Agentic RAG examples on Weaviate Recipe: github.com/weaviate/recipes/tree/main/integrations/llm-frameworks
Additional resources on the mentioned topics:
ReAct: arxiv.org/abs/2210.03629
Chain-of-Thought: arxiv.org/abs/2201.11903
Tree of Thoughts: arxiv.org/pdf/2305.10601
MuZero: arxiv.org/abs/1911.08265
DSPy: github.com/stanfordnlp/dspy
Letta: github.com/letta-ai/letta
Letta Docs: docs.letta.com/introduction
LLM Juries: arxiv.org/abs/2404.18796
More Agents Is All You Need: arxiv.org/abs/2402.05120
Are More LM Calls All You Need? arxiv.org/pdf/2403.02419
Network of Networks: arxiv.org/pdf/2407.16831
Generative Feedback Loops: weaviate.io/gen-feedback-loops
STORM: arxiv.org/abs/2402.14207
BioDiscoveryAgent: arxiv.org/abs/2405.17631
The AI Scientist: arxiv.org/abs/2408.06292
Hey everyone! Thank you so much for watching the 109th episode of the Weaviate Podcast with Erika Cardenas! Erika, in collaboration with Leonie Monigatti, have recently published "What is Agentic RAG". This blog post that was even covered in VentureBeat with additional quotes from Weaviate Co-Founder and CEO Bob van Luijt! This podcast continues the discussion on all things Agentic RAG, covering the basics of Agents, how Agentic RAG changes the game compared to Vanilla RAG systems, Multi-Agent Systems and CrewAI / OpenAI Swarm, Letta, DSPy, and many more! The podcast also anchors by discussing Agentic Generative Feedback Loops and how we are using Agents to improve the quality and expand the capabilities of Generative Feedback Loops!
I hope you find the podcast interesting! As always we are more than happy to continue discussing these ideas with you or answer any questions you have! Thanks so much!
Chapters
0:00 Weaviate in NYC!
0:26 Welcome Erika!
1:22 What are Agents?
3:00 Agentic RAG vs. Vanilla RAG
5:28 Planning in Agents and o1
12:40 Multi-Agent Systems
15:25 Letta
18:57 Evals
21:00 Vertex Agent Builder and UX for Agents
22:21 LLM-as-Judge
25:45 Agentic Generative Feedback Loops
Here is the recording of Erika's talk in NYC! - youtube.com/watch?v=AOSjiXP1jmQ
To keep up to date with future Weaviate events, please see - weaviate.io/community/events
Weaviate Blog, "What is Agentic RAG": weaviate.io/blog/what-is-agentic-rag
VentureBeat, "How agentic RAG can be a game-changer for data procssing and retrieval": venturebeat.com/ai/how-agentic-rag-can-be-a-game-changer-for-data-processing-and-retrieval
Agentic RAG examples on Weaviate Recipe: github.com/weaviate/recipes/tree/main/integrations/llm-frameworks
Additional resources on the mentioned topics:
ReAct: arxiv.org/abs/2210.03629
Chain-of-Thought: arxiv.org/abs/2201.11903
Tree of Thoughts: arxiv.org/pdf/2305.10601
MuZero: arxiv.org/abs/1911.08265
DSPy: github.com/stanfordnlp/dspy
Letta: github.com/letta-ai/letta
Letta Docs: docs.letta.com/introduction
LLM Juries: arxiv.org/abs/2404.18796
More Agents Is All You Need: arxiv.org/abs/2402.05120
Are More LM Calls All You Need? arxiv.org/pdf/2403.02419
Network of Networks: arxiv.org/pdf/2407.16831
Generative Feedback Loops: weaviate.io/gen-feedback-loops
STORM: arxiv.org/abs/2402.14207
BioDiscoveryAgent: arxiv.org/abs/2405.17631
The AI Scientist: arxiv.org/abs/2408.06292
