Traditional Chatbot vs LLM: Differences That Actually Matter
How a chatbot with intent classification works, how one based on LLM works, and when to choose each approach with concrete examples.
AI Coding Patterns
Understand what an agent does, what to ask it, and when to correct it. Visual, interactive, short courses for those who prefer a diagram to a 350-page book.
Try it — can you solve this?
You: "Hi, I'm Ana"
AI: "Hello Ana! How can I help?"
You: "What's my name?"
AI: "I don't have that information."Why doesn't the AI remember your name?
Visual, short, straight to the point. No spam.
How you learn here
Every concept is explained with diagrams, simulations, and interactive exercises. No reading 50 pages to understand a loop.
You don't watch — you participate. Each lesson puts you in the driver's seat, making decisions like you would in a real project.
Short, focused courses. Get the idea, try it, move on. No filler, no detours.
What's coming
From scratch: set up your environment, learn to give effective instructions, and build your first project with AI.
Understand how embeddings work, build a semantic search engine, and connect it to your application.
Design multi-agent systems: orchestration, memory, tools, and production evaluation.
Go deeper
How a chatbot with intent classification works, how one based on LLM works, and when to choose each approach with concrete examples.
Set up autoMode.environment so the classifier understands your infrastructure and stops interrupting you with false positives.
An LLM predicts the next most probable token. It doesn't understand. So how does it produce outputs that seem to require real comprehension?