Start Here

Our Learning Philosophy

Most AI education focuses on surface-level APIs and toy examples. We go deeper.

You'll learn the mental models, architectural patterns, and production constraints that experienced engineers use. This means:

• Understanding why things work, not just how
• Learning patterns that transfer across tools and frameworks
• Building intuition for tradeoffs and failure modes
• Developing the judgment needed for real-world decisions

This takes time. This takes effort. But this is what separates engineers who ship production systems from those who follow tutorials.

What We Expect From You

You should:

• Have basic programming experience (Python or TypeScript preferred)
• Be comfortable reading technical documentation
• Have patience for concepts that take time to internalize
• Be willing to experiment, fail, and iterate
• Question assumptions and test your understanding

How Tutorials Are Structured

Each tutorial follows a consistent pattern:

1. Mental Model First — We establish the conceptual framework before code
2. Working Examples — Production-quality code, not quick hacks
3. Failure Modes — What breaks, why it breaks, and how to handle it
4. Tradeoffs — When to use this pattern and when not to

Tutorials are cumulative. Later tutorials assume you've internalized earlier ones. Don't skip ahead unless you're confident in the prerequisites.

Understanding Versioned Tutorials

AI tooling moves fast. Instead of deleting or overwriting content, we version tutorials.

Each tutorial has a latest stable version, but older versions stay available. When APIs change or better patterns emerge, we publish a new version with clear explanations of what changed and why.

Curriculum Roadmap

The tutorials follow a deliberate progression. Start at Tutorial 1 and work forward.