2-Week Masterclass

Build an End-to-End
Agentic AI System

Build an end-to-end agentic AI system: agentic RAG, text-to-SQL, tool use, multi-step workflows, and production deployment. Go from understanding agents to shipping one.

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You understand AI agents in theory. Now build one.

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Tutorials show toy agents

Simple tool-calling demos. But production agents need guardrails, error recovery, and multi-step reasoning.

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RAG alone is not enough

Real systems combine RAG with SQL queries, visualizations, and multi-agent coordination.

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No end-to-end reference

Pieces exist everywhere. A complete, deployable agentic system from architecture to UI? That is rare.

What you will build

Turn plain English questions into SQL queries — automatically
Coordinate multiple specialized agents to answer complex data questions
Add guardrails that stop bad queries before they hit your database
Generate charts and visualizations from query results
Ship a chat interface your team can actually use to explore data

Who this is for

Software engineers

who understand AI basics and want to build real agentic systems

AI engineers

who want hands-on experience with multi-agent architectures

Backend developers

looking to add agentic AI capabilities to existing products

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One masterclass. One complete agentic system. Lifetime access.

FAQ

Frequently Asked Questions

What prerequisites do I need?
Basic Python knowledge and familiarity with LLM concepts. Ideally, you have taken the Building AI Agents resource or have equivalent experience.
What will I build?
A complete agentic RAG system that converts natural language to SQL, auto-generates visualizations, and runs on a LangGraph multi-agent architecture.

In 2 weeks:

A deployed agentic AI system you built end-to-end

Or more blog posts bookmarked and never built

Ship an agent. Not another bookmark.

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