Hey makers! 👋

I built this because I kept having the same conversation over coffee and at events:

Smart people in tech would ask "how does GPT actually work?" and I'd watch them struggle with one of three options:

1. YouTube videos that oversimplify (feels wrong immediately)

2. Papers that need 3 PhDs in math (way too steep a cliff)

3. Blog posts that are just walls of text (easy to zone out)

So I spent a wekend building something interactive.

Goal: understand enough to have real conversations about LLMs without needing a PhD or 40-hour course.

What surprised me while building: how many incredibly smart people have been too intimidated to even try understanding this.

That gap felt worth fixing.

You'll learn:

- Why tokenization literally makes models fail at spelling

- How chain-of-thought prompting grants models more compute

- What makes DeepSeek-R1's emergent reasoning different

- Why your prompts work better when you paste documents

Takes about 20 minutes. Built for product people, engineers, founders who've nodded along to technical conversations but never actually understood.

Happy to answer questions about design decisions, which concepts were hardest to explain, or why we chose specific metaphors (like Move 37 for illustrating RL discovery).

What's been the most confusing thing about LLMs for you?

That's probably the gap we need to fill.