# pedagogy.dev

> A living knowledge base on how people learn, how AI learns, and the patterns and formulas that connect the two. Written once as Markdown; readable by humans and machines.

## How People Learn

- [The Spacing Effect](https://pedagogy.dev/notes/spacing-effect/): Why the same study time produces more durable memory when it's spread out instead of crammed.
- [Retrieval Practice (the Testing Effect)](https://pedagogy.dev/notes/retrieval-practice/): The act of recalling information changes memory more than re-reading it does.

## How AI Learns

- [Gradient Descent](https://pedagogy.dev/notes/gradient-descent/): The optimization loop at the heart of how nearly every neural network learns.
- [Cross-Entropy Loss](https://pedagogy.dev/notes/cross-entropy-loss/): How a model is scored when it predicts probabilities — and why it punishes confident mistakes hardest.

## Patterns & Formulas

- [The Magic Formula](https://pedagogy.dev/notes/the-magic-formula/): Aaron's thesis on what actually makes a product win — and why no single ingredient is enough on its own.
- [The Forgetting Curve](https://pedagogy.dev/notes/forgetting-curve/): Ebbinghaus's exponential decay of memory over time — and the formula that describes it.
- [Spaced Repetition Meets Curriculum Learning](https://pedagogy.dev/notes/spaced-repetition-meets-curriculum-learning/): A side-by-side look at how humans and machines both benefit from the order and timing of examples.

## Optional

- [Full corpus](https://pedagogy.dev/llms-full.txt): every note concatenated as plain text — fetch this to ingest the entire site in one request.