I created the Intro to AI Hackathon Toolkit because I believe the next million AI users will come from diverse disciplines—therapy, coaching, teaching, engineering, biology, science—and they deserve onboarding that meets them where they are.
This isn't your typical technical tutorial. It's a self-paced course that takes complete beginners from "what is AI?" to building and deploying their first AI-powered project, all without requiring any prior coding experience.
What Makes This Different
Most AI education assumes you already know how to code, or it stays so high-level that you never actually build anything. This toolkit bridges that gap with a human-centered approach that emphasizes creative problem-solving alongside technical implementation.
Core Philosophy
The toolkit focuses on human-centered explanations without jargon, creative approaches including "vibe code" methodologies, practical projects that build real things, and community support where learners help each other grow.
The Learning Path
The course is structured in six phases, each building on the last:
Phase 1: Understanding AI
We start by demystifying what AI actually is—and what it isn't. AI isn't magic; it's a tool, like a calculator or search engine, but much more powerful. The key insight is that AI learns from patterns in data to make predictions, and it works best with human guidance.
Phase 2: Talking to AI
This is where context engineering comes in. Context engineering is the skill of providing AI with the right background information, examples, and framing to get the results you want. Think of it like the difference between asking a stranger for directions without saying where you want to go versus giving them your destination, how you're traveling, and what you want to avoid.
“The more relevant information you provide, the better your results. Vague requests get vague responses.
Phase 3: Vibe Code and Creative Hacks
This is where things get interesting. Vibe coding, popularized by AI researcher Andrej Karpathy, describes a fast, improvisational approach to creating software where the developer and AI work together like pair programmers in a conversational loop.
The core philosophy emphasizes "fully giving in to the vibes"—embracing exponentials and focusing on creative flow over micromanaging implementation details.
Phase 4: Building Your First Project
With the foundations in place, learners move into practical project building. The toolkit provides templates, integration patterns, and step-by-step guides for creating everything from personal AI assistants to creative tools to problem-solving applications.
Phase 5: Sharing Your Creation
Building something is only half the journey. The toolkit covers documentation, getting feedback, and preparing your project for the world.
Phase 6: The Final Challenge
The capstone is a 24-hour sprint challenge using the 20/80 principle: we provide 20% of what you need to complete the remaining 80%. This includes project templates, AI integration patterns, essential tools, and troubleshooting resources.
The Three Pillars of Effective AI Collaboration
Throughout the toolkit, we emphasize three pillars that make human-AI collaboration work:
Pillar 1: Work Abstraction
Learn to abstract work at the right level. Too granular and you're micromanaging the AI. Too abstract and you lose control over quality. The sweet spot is "intent-level abstraction"—defining desired outcomes and constraints, not implementation details.
Pillar 2: Collaborative Tool Integration
Structure the partnership for maximum efficiency through incremental validation, role-based boundaries, documentation as context, and frequent feedback loops.
Pillar 3: Human Review
Maintain strategic control through regular review—not checking for errors, but ensuring alignment with goals, quality standards, and context consistency.
Who This Is For
The toolkit is designed for complete beginners with zero technical background, curious minds who want to understand AI without the jargon, creative people looking to add AI capabilities to their work, and anyone who wants to build something cool with AI.
“We believe that the next million AI users will come from diverse disciplines, and they deserve onboarding that meets them where they are.
Resources Included
The toolkit includes an AI glossary with simple definitions for AI terms, tool recommendations for our favorite AI platforms, project ideas for inspiration, and a troubleshooting guide for when things go wrong.
Get Started
The full toolkit is available on GitHub: Intro to AI Hackathon Toolkit
Whether you're preparing for a hackathon, exploring AI for the first time, or looking to add AI capabilities to your existing skills, this toolkit provides the foundation you need to start building.
The goal isn't perfection—it's completion and learning. Build something, share it, get feedback, and iterate. That's how we all grow together in this new frontier.
