Best Chain of Thought Episodes on AI Agents
How agents work: architecture, memory, context, frameworks.
Jerry Liu argues that context quality matters more than the framework around an agent. The episodes that follow examine other layers of that system: Richmond Alake on memory, Mikiko Chandrasekhar on engineering discipline and João Moura on the agent stack. The final panel introduces the workflows and architecture behind those choices.
- 5 episodes
- 6 guests
- 4 hours of listening
- 2 jump-to moments
- 1
The AI Framework Era Is Over: Why Context Is the Moat | Jerry Liu of LlamaIndex Jerry Liu, LlamaIndex Jerry Liu on why the advantage in agents moved from the framework to the context you feed it. Jump to the moment · 8:12 · Context beyond frameworks → - 2
Agent Memory: The Last Battleground in the AI Stack | Richmond Alake, Oracle Richmond Alake, Oracle Richmond Alake on engineering memory for agents that need to carry information across sessions. Jump to the moment · 2:23 · Why memory needs engineering → - 3
Mastering Multi-Agent Systems | MongoDB’s Mikiko Chandrasekhar Mikiko Chandrasekhar, MongoDB Mikiko Chandrasekhar on when many agents beat one, and the coordination problems that come with them. - 4
The Emerging AI Agent Stack | CrewAI’s João Moura João Moura, CrewAI CrewAI’s João Moura maps the emerging agent stack: the layers you assemble when you build one. - 5
Got Agents? Agentic Workflows & Architecture | Weaviate, Unstructured & CrewAI Brian Raymond, Bob van Luijt & João Moura A foundational panel on agentic workflows and architecture, covering how an agent is put together before the hype.
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