11 Sections
42 Lessons
4 Weeks
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Section 1: Smolagents 1.1 - Introduction to Smolagents
5
1.1
Lesson 1.1.1: From LLMs to Real Agentic Systems
1.2
Lesson 1.1.2: Smolagents as a Structured Agent Framework
1.3
Lesson 1.1.3: Tools, Agents, and the Manager-Worker Model
1.4
Lesson 1.1.4: Explicit Reasoning: Thought-Action-Observation
1.5
Lesson 1.1.5: First Tool Call with Smolagents (No Agent)
Section 1: Smolagents 1.2 - MCP Concepts
4
2.1
Lesson 1.2.1: MCP: Decoupling Agents from Tools
2.2
Lesson 1.2.2: The MCP Client-Server Architecture
2.3
Lesson 1.2.3: Discovery and Invocation of Remote Tools
2.4
Lesson 1.2.4: Practical Example
Section 1: Smolagents 1.3 - Smolagents Boilerplate with Simple Tools
5
3.1
Lesson 1.3.1: Local-First Architecture Overview
3.2
Lesson 1.3.2: Model Initialization: Establishing the Reasoning Engine
3.3
Lesson 1.3.3: Tool Design: Defining Explicit Capabilities
3.4
Lesson 1.3.4: Specialist Agents: ToolCalling Agents with Clear Ownership
3.5
Lesson 1.3.5: Manager Agent & Execution Flow
Section 1: Smolagents 1.4 - Smolagents Boilerplate Using MCP Tools
6
4.1
Lesson 1.4.1: What This Boilerplate Demonstrates
4.2
Lesson 1.4.2: MCP Server: Exposing Capabilities
4.3
Lesson 1.4.3: MCP Client: Discovering Remote Tools
4.4
Lesson 1.4.4: Worker Agent: Tool Execution Layer
4.5
Lesson 1.4.5: Manager Agent: Orchestration Only
4.6
Lesson 1.4.6: Full Code Implementation
Section 1: Smolagents 1.5 - Problem Statement
1
5.1
Lesson 1.5.1: Build a Real Weather Agent
Section 2: Langgraph 2.1 - Introduction to Langgraph
5
6.1
Lesson 2.1.1: Why Graph-Based Agents Exist
6.2
Lesson 2.1.2: What “Graph Design” Really Means
6.3
Lesson 2.1.3: Nodes: Units of Work, Not Intelligence
6.4
Lesson 2.1.4: Edges & Transitions: How Flow Is Controlled
6.5
Lesson 2.1.5: State, Checkpoints
Section 2: Langgraph 2.2 - LLM & Tool Integration in LangGraph
5
7.1
Lesson 2.2.1: Role of LLMs in a LangGraph System
7.2
Lesson 2.2.2: Tools as the Real Actors
7.3
Lesson 2.2.3: Memory and State: How Context Is Preserved
7.4
Lesson 2.2.4: Why LLMs Should Not Control Flow
7.5
Lesson 2.2.5: Putting It Together: A Clean Mental Model
Section 3: Langgraph 2.3 - Framework Comparison - Smolagents vs LangGraph
5
8.1
Lesson 2.3.1: What Smolagents Optimizes For
8.2
Lesson 2.3.2: What LangGraph Optimizes For
8.3
Lesson 2.3.3: Key Architectural Differences
8.4
Lesson 2.3.4: When Smolagents Is the Right Choice
8.5
Lesson 2.3.5: When LangGraph Becomes Necessary
Section 4: Langgraph 2.4 - Boilerplate for deterministic workflow and practice
2
9.1
Lesson 2.4.1: Boilerplate for deteministic workflow
9.2
Lesson 2.4.2: Practice example
Section 3: Practical Agents
4
10.1
Lesson 3.1: Research Agent
10.2
Lesson 3.2: Decision Agent
10.3
Lesson 3.3: Memory Agent
10.4
Lesson 3.4: Robust Agent: Human-in-the-Loop
Quiz
1
11.1
Quiz – L2 AI Agents
20 Minutes
10 Questions
Advanced AI Agents: Code-Based Frameworks & System Design
Curriculum
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