Introduction
Source Code
Downloadables
Module 1 | Intro to AI Agents
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Intro to AI Agents Module (1:13)
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1. AI Pyramid (6:05)
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2. What are AI Agents? (3:58)
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3. RAG vs Agentic RAG (5:44)
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4. AI Agent Tech Stack (8:05)
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5. What we'll build? (Demo) (6:22)
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6. System Design (4:07)
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7. Tools Setup (8:12)
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8. Frontend Code Overview | React.js (8:46)
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9. Backend Code Overview | Node.js | Ingest API (16:49)
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10. Backend Code Overview | Node.js | Chat API (14:45)
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11. Langsmith | Observability (18:11)
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12. Run App (0:59)
Module 2 | Deploy Local LLM (Ollama)
Module 3 | Model Context Protocol (MCP)
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Intro to MCP Module (0:53)
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1. The problem MCP is solving (4:11)
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2. MCP is the solution (9:15)
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3. MCP Capabilities (3:42)
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4. What is a Protocol? (5:58)
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5. Transport modes (8:07)
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6. MCP Messages (1:07)
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7. MCP Conversation (6:28)
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8. App Demo (8:26)
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9. Frontend Code Changes for MCP (2:12)
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10. Backend Code Overview | MCP Client (15:52)
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11. MCP Server | Streamable HTTP (13:16)
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12. MCP Server | STDIO (3:11)
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13. MCP Client-Server Architecture (2:17)
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14. Using API vs MCP Server (12:44)
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15. Web Search API Setup (0:45)
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16. Run App (6:04)
Module 4 | Multi-Agent Systems | LangGraph
Module 5 | Multi-Agent Systems | Agent2Agent
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Intro to Agent2Agent Module (1:05)
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1. Intro to Agent2Agent Protocol (8:11)
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2. A2A Definition (9:47)
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3. LangGraph vs A2A (6:10)
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4. Demo App: AI Trip Assistant (A2A) (6:50)
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5. System Design (4:30)
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6. Frontend Code (11:37)
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7. Backend Code | Orchestrator (26:02)
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8. Backend Code | Agents Files (12:49)
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9. Setup App: AI Trip Assistant (A2A) (6:33)
Module 6 | Multi-Agent Systems | Career Assistant
Congratulations
