Today, we're joined by Dan Jeffries, founder and CEO of Kentauros AI to discuss the challenges currently faced by those developing advanced AI agents. We dig into how Dan defines agents and distinguishes them from other similar uses of LLM, explore various use cases for them, and dig into ways to create smarter agentic systems. Dan shared his “big brain, little brain, tool brain” approach to tackling real-world challenges in agents, the trade-offs in leveraging general-purpose vs. task-specific models, and his take on LLM reasoning. We also cover the way he thinks about model selection for agents, along with the need for new tools and platforms for deploying them. Finally, Dan emphasizes the importance of open source in advancing AI, shares the new products they’re working on, and explores the future directions in the agentic era.
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📖 CHAPTERS
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00:00 - Introduction
2:15 - Kentauros
7:00 - LLM reasoning
9:27 - AI agents definition
10:42 - Why agents are stupid and what we can do about it
12:14 - Core use cases of AI agents
24:38 - Tackling real-world challenges
29:52 - Path to next-level abstractions
35:56 - Barriers in agents
50:29 - Model selection
55:05 - MLOps
1:00:34 - Open source
1:03:59 - Recap and future directions
🔗 LINKS & RESOURCES
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Why Agents Are Stupid & What We Can Do About It - https://www.youtube.com/watch?v=TbnIA0Er5jA
Kentauros AI - https://www.kentauros.ai/
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