What is the real difference between an LLM, Generative AI, an AI Agent, and Agentic AI? In this video, we will understand all four concepts using one practical developer example: Building a complete e-commerce website with a frontend, backend, database, REST APIs,...
What is the real difference between an LLM, Generative AI, an AI Agent, and Agentic AI?
In this video, we will understand all four concepts using one practical developer example:
Building a complete e-commerce website with a frontend, backend, database, REST APIs, authentication, admin panel, testing, debugging, and Hostinger VPS deployment—with the help of Claude Code or OpenAI Codex.
Instead of learning complicated theoretical definitions, we will follow one complete journey from idea to production.
You will understand:
✅ What an LLM actually does
✅ How an LLM generates answers token by token
✅ Why Generative AI creates content but may not perform the action
✅ How AI agents use tools, terminals, files, browsers, and MCP servers
✅ What MCP, or Model Context Protocol, means
✅ How Mermaid MCP can help generate and render diagrams
✅ How coding agents can create files and run commands
✅ How AI can test an application, identify errors, fix code, and test again
✅ What makes an AI workflow “agentic”
✅ Why agentic behaviour is a level of autonomy—not necessarily a separate product
✅ How Claude Code or Codex can prepare and deploy an application using Hostinger tools
✅ Why critical production actions should still require human approval
The easiest way to remember the difference:
🧠 LLM provides the intelligence
✍️ Generative AI creates
🛠️ AI agents act
🔁 Agentic systems plan, act, observe, and adapt
Or even more simply:
Generative AI = The Talker
AI Agent = The Worker
Agentic AI = The Outcome Owner
The same tool can demonstrate all these capabilities.
For example:
When Claude Code generates a React component, we are using its generative capability.
When it adds that component to the actual project and runs commands, it is acting as an AI agent.
When it plans an entire feature, implements it, runs tests, examines failures, fixes the code, and continues toward the final goal, it demonstrates agentic behaviour.
This video is especially useful for developers who want to understand how modern AI coding tools such as Claude Code and OpenAI Codex actually work.
Want me to build the complete e-commerce application—from a single prompt to a live Hostinger deployment?
Comment “BUILD IT” below.
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TIMELINE
00:00 Introduction to Artificial Intelligence
00:40 LLM vs Generative AI vs AI Agent vs Agentic AI
00:55 What Is an LLM?
01:26 How Does an LLM Generate Output?
02:55 Our E-commerce Website Mission
03:25 Generative AI: Planning the Project
05:55 AI Agent: The Doer
08:00 AI Agent in Action
09:00 Understanding the AI Agent Loop
09:40 Agentic AI: The Owner
