Generative
Build systems that change over time using probability, mutation, and feedback.
- sample and hold
- Turing-style mutation
- feedback and slow modulation
Generative
Lesson 02: Probability And Mutation
Use probability to keep a system moving without letting it collapse into noise.
Markdown content
Theory, structure, and practical context are all driven from content files.
Related patches
Concrete repository anchors already exist for this lesson track.
Theory
Probability is one of the main tools that makes a modular patch feel alive.
It controls whether something should happen, not just what should happen.
That means it can affect:
- note density
- rhythmic variation
- trigger skipping
- pattern mutation
Why It Matters
A repeating patch becomes generative when repetition is softened by conditional change.
Probability gives the patch room to evolve while keeping a recognizable identity.
Patch Idea
Clock -> Probability gate -> Trigger stream
Trigger stream -> Sequencer / Envelope / Event logicPractice
Make one patch with highly stable behavior and one patch with higher variation.
Compare:
- how often events are skipped
- how much identity the pattern keeps
- when variation becomes too loose
Patch references
Use the linked patch entries below as concrete repository anchors for this lesson track.
Continue inside Generative
Adjacent lessons in the same track keep the topic progression coherent.
Hybrid routing overview
The first system diagram connects the modular engine, DAW layer, and visual output layer.