3e:I[58016,["/_next/static/chunks/0jjo8hz~ewue4.js","/_next/static/chunks/0abq8zp15pmva.js","/_next/static/chunks/05gz47kazl1ze.js","/_next/static/chunks/139o5utivfajl.js","/_next/static/chunks/0a~e7k..h6jfc.js","/_next/static/chunks/0d1e9m2ig9v3v.js","/_next/static/chunks/0fg30bidui1gn.js","/_next/static/chunks/0rizq9ux3s1w3.js","/_next/static/chunks/0bbc2ioe2xmkf.js","/_next/static/chunks/0z7avafhgjcyr.js"],"ProcessEpisodeButton"] 40:I[185,["/_next/static/chunks/0jjo8hz~ewue4.js","/_next/static/chunks/0abq8zp15pmva.js","/_next/static/chunks/05gz47kazl1ze.js","/_next/static/chunks/139o5utivfajl.js","/_next/static/chunks/0a~e7k..h6jfc.js","/_next/static/chunks/0d1e9m2ig9v3v.js","/_next/static/chunks/0fg30bidui1gn.js","/_next/static/chunks/0rizq9ux3s1w3.js","/_next/static/chunks/0bbc2ioe2xmkf.js","/_next/static/chunks/0z7avafhgjcyr.js"],"SendEmailButton"] 41:I[45269,["/_next/static/chunks/0jjo8hz~ewue4.js","/_next/static/chunks/0abq8zp15pmva.js","/_next/static/chunks/05gz47kazl1ze.js","/_next/static/chunks/139o5utivfajl.js","/_next/static/chunks/0a~e7k..h6jfc.js","/_next/static/chunks/0d1e9m2ig9v3v.js","/_next/static/chunks/0fg30bidui1gn.js","/_next/static/chunks/0rizq9ux3s1w3.js","/_next/static/chunks/0bbc2ioe2xmkf.js","/_next/static/chunks/0z7avafhgjcyr.js"],"SignupCTA"] 36:["$","path",null,{"strokeLinecap":"round","strokeLinejoin":"round","strokeWidth":2,"d":"M8 7V3m8 4V3m-9 8h10M5 21h14a2 2 0 002-2V7a2 2 0 00-2-2H5a2 2 0 00-2 2v12a2 2 0 002 2z"}] 37:["$","time",null,{"dateTime":"2025-10-06T20:13:40.000Z","children":"Mon Oct 06 2025"}] 38:["$","p",null,{"className":"text-base text-foreground/80 leading-relaxed","children":"Episode Two of AI Agents dives deep into the mechanics of how these autonomous systems actually work. Host Leo Finch breaks down the three core components: large language models serving as the \"brain\" for reasoning and planning, tools and APIs acting..."}] 3f:T4c6,Episode Two of AI Agents dives deep into the mechanics of how these autonomous systems actually work. Host Leo Finch breaks down the three core components: large language models serving as the "brain" for reasoning and planning, tools and APIs acting as "hands" to execute actions in digital environments, and memory systems with feedback loops enabling long-term learning and improvement. The episode explores different agent architectures, comparing single agents to sophisticated multi-agent systems, and explains techniques like task decomposition and recursive planning that allow agents to handle complex problems. Leo uses the analogy of a highly capable personal assistant who doesn't just take notes but actually books flights, negotiates, and remembers your preferences, making the technology's "magic" tangible and understandable.

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How AI Agents Work