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AI Agents & Workflows - The Practical Guide

Getting Started
- Welcome To The Course (1:22)
- What Is An AI Agent? (2:13)
- General vs Task-specific Agents (2:39)
- Where Agents Run / Execute (2:07)
- AI Agent Harnesses, LLMs & Limitations (3:25)
- How Agents Use Tools (5:15)
- Understanding Session Context (2:17)
- Core AI Agent Building Blocks - Overview (2:25)
- AI Agents vs AI Workflows (2:18)

Using & Steering AI Agents
- Module Introduction (0:57)
- Three Main Ways For Controlling AI Agents You Should Know (0:49)
- Managing Agent Tools & The Environment (3:42)
- Choosing The Right Model (1:17)
- Understanding Developer-provided System Instructions (1:39)
- Providing Your Own Instructions & Understanding AGENTS.md / CLAUDE.md (3:29)
- Understanding Agent Skills (8:28)
- Understanding Agent Memory (3:23)
- Sometimes Key: Humans In The Loop (2:57)

Building Agents & Workflows - An Overview
- Module Introduction (0:36)
- Options For Building Agents & Workflows (2:46)
- WHO Builds It,



WHERE Does It Run? (3:36)
- Options When Building WITH Code (0:52)
- Choosing Your Agent Building Blocks (1:56)

Building AI Workflows & Applications
- Module Introduction & Expectations (1:35)
- Building Workflows - The Basics (1:20)
- Workflows vs Agents (2:39)
- Building Visually with n8n - First Steps (2:38)
- Running a Demo n8n Project Locally (1:41)
- Exploring n8n & Its Workflow Builder (6:44)
- Exploring & Understanding a Realistic Workflow (4:24)
- Onwards To A Code-based Solution (3:15)
- Exploring & Understanding A Code-based Workflow (6:20)
- Module Summary (1:11)

Building AI Workflows & Applications [LEGACY]
- About This LEGACY Section
- Module Introduction (2:21)
- No Code vs With Code (2:07)
- Building AI Apps & Using AI Programmatically (4:12)
- Proprietary vs Open (Local) LLMs (5:51)
- Using Open LLMs
- Understanding Our Development Environment (2:29)
- Creating a New Python Project (using "uv")

📌 How Agents Use Tools (Alipur)
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