Build AI Employees with Django – Agentic AI for Developers

Build autonomous AI agents from scratch
Multi-agent orchestration — three agents collaborating and making decisions autonomously
RAG with ChromaDB — give agents access to real documents so they never hallucinate
Live streaming agent activity — watch every tool call and decision stream in real time
Turn Django ORM queries into AI tools — your existing skills become superpowers
Production ready multi-agent customer support system — built end to end from scratch

Requirements

Basic Django knowledge — models, views, URLs, templates
No AI or machine learning experience needed
Anthropic API key (new accounts may receive $5 free credits — enough to complete the course)

Description

Are you a Python/Django developer who wants to stay ahead in the AI era?
This course teaches you how to build real AI Employees — autonomous AI agents that work for your business 24/7, handle customer queries, collaborate with each other, assess fraud risk, and make decisions — all without human intervention.
What You Will Build
A complete AI-powered customer support system for a fictional AC company called CoolBreeze AC. By the end of this course, you will have built
- Maya — an AI support agent that handles customer queries, checks orders, verifies delivery status, and decides when to escalate
- A manager agent that reviews escalated cases and makes refund decisions
- A risk agent that assesses fraud patterns and gives the manager a verdict
- A RAG system that gives agents access to real company documents and policies — no hallucination, real answers
- A live streaming support dashboard where staff can monitor every agent decision in real time
- Full deployment on Railway — your system live on a real URL

What You Will Learn

- How Agentic AI actually works — the agent loop, tool calling, and decision making under the hood
- How to turn Django ORM queries into AI agent tools
- How to write effective tool schemas that guide an LLM's decision making
- How to build multi-agent systems where agents collaborate and hand off tasks autonomously
- How to implement RAG using ChromaDB and pypdf so agents answer from real company documents
- How embeddings and vector similarity search work
- How to stream live agent activity to a dashboard using Server Sent Events (SSE)
- Prompt engineering techniques for controlling agent behavior and tone
- How to deploy a production Django + AI application on Railway
Why We Start Without Frameworks
Most AI courses jump straight into LangChain or AutoGen. We don't — and it's intentional.
LangChain, AutoGen, and CrewAI are all built on the same agent loop, tool calling, and multi-agent orchestration you'll learn in this course. If you learn the framework first, you're memorizing syntax without understanding what's happening underneath.
We build everything from scratch first. Then, in the LangChain edition — coming as a free update — you'll see the exact same CoolBreeze project rebuilt using these frameworks. You'll understand immediately what they're doing for you, when to use them, and why.
Build the foundation first. The frameworks will make complete sense after.

Who this course is for

Django developers who want to add Agentic AI to their skill set
Python developers who want to build real AI powered applications from scratch
Anyone who wants to future proof their career by learning the most in demand skill of 2026 + Next 10 Years.

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