A serious course for software & IT professionals ready to move from AI-aware to AI builder — through concepts, patterns, and hands-on demos that actually work.
Every week there's a new demo. A new model. A new "game-changer." But when you try to build something real — it falls apart. Here's why.
LinkedIn's flooded with "10x developer" demos that wouldn't survive a code review — and the code they produce is plausible-looking slop nobody can maintain. Autocomplete at scale is not architecture.
Multi-agent systems go off-rails fast. Without the right patterns — spec-driven development, context engineering, handoff protocols — your agents will hallucinate and drift.
Every tutorial demos the sunny-day path. Nobody teaches what happens when sessions fail, context overflows, agents contradict each other, or the build stalls mid-execution.
The gap between knowing AI exists and using it to ship real software is a skill gap — and this course closes it.
You know the tools exist. You've tried a few prompts. But you're copy-pasting outputs you don't fully trust.
You direct a virtual dev team. You define the work, the agents execute, and you ship real software.
Each module builds on the last — from tool mastery to architecting multi-agent systems to shipping a real application.
Install and configure Claude Code. Understand the CLI, commands, and session model. Create custom commands, build agents, wire up MCP servers, and get hands-on with context management, memory, and usage patterns. By the end of Module 1 you are fluent in Claude Code.
Understand agentic AI from first principles — how agents collaborate, how handoffs work, and why drift and hallucination happen. Learn spec-driven development: defining requirements, backend, frontend, business rules, and testing strategy as structured specifications that anchor agents and prevent chaos.
Core patterns that separate toy demos from production systems: context engineering, clear and concise agent prompts, context management through /clear and handoffs, session resumption, and learning systems. Design a virtual team with defined roles — architect, backend, frontend, QA, orchestrator — and understand how each agent fits.
Create the virtual team, review specifications, kick off the agent system, and handle real practical issues that arise during execution. Test your application end-to-end using MCP Playwright. Walk away with a complete, working web application built by a multi-agent system you designed and orchestrated.
You'll work with the same production tools used in real agentic development systems — not toy examples.
Not "familiarity with AI tools." Specific, demonstrable capabilities you'll have on day one after completing the course.
Orchestrate a virtual development team of specialized agents — architect, backend, frontend, QA — using Claude Code as the backbone
Write specifications that replace code — define requirements, backend, frontend, and testing strategy as structured specs that agents execute reliably
Debug agent drift and hallucination with confidence — understand why it happens and use spec-driven techniques to prevent and recover from it
Configure and use MCP servers — wire up external tools and services to your agents using the Model Context Protocol
Ship a complete full-stack application built by a multi-agent system — Java/Spring backend, React frontend, Docker, tested end-to-end with MCP Playwright
This is not an intro to AI course. It's for technical professionals who want to lead in the agentic era — not just observe it.
You write code professionally. Now learn how to direct agents that write code — and understand the architecture of systems where AI does the heavy lifting.
You design systems and lead teams. Learn the architectural patterns of agentic systems — context flows, handoffs, specs, reliability — and the vocabulary to guide your team into the agentic era.
You manage and deploy systems. Learn how agentic AI changes the infrastructure story — containers, MCP servers, deployment pipelines, and automated testing.
Not a content creator. A practicing architect who's shipped real systems — and now teaches the patterns that actually hold up in production.
With 25 years of experience in the IT industry, I bridge the gap between complex theory and real-world application. As a former Technology Leader and Architect, I bring decades of hands-on expertise in Cloud Computing, AI/ML, and Software Architecture directly to the classroom.
My training methodology focuses on practical, enterprise-grade solutions. I specialize in teaching professionals how to navigate cloud migrations, design scalable full-stack architectures, and implement machine learning solutions that solve actual business challenges.
My goal is to equip teams with the architectural thinking and technical skills required to succeed in today's evolving tech landscape.
Four modules. Real demos. A complete application you built with agents. No hype. No slop. Just serious skill.