The core primitive

What is a Yawn?

A Yawn is a container for uncertainty collapse.

The root question

What should we do next to reduce uncertainty and increase agency without violating coherence?

Anatomy

Every Yawn Contains

Question

A latent or explicit question driving the yawn

01

Plans

Candidate paths, experiments, and moves to reduce uncertainty

02

Proof

What evidence counts as progress

03

Feedback

Channels for sensing change and learning

04

Promotion / Split rules

When to promote, split, retire, or kill

05

A Yawn is not a task list. It is a decision-control unit.

The cycle

Spec → Act → Prove → Learn

Every Yawn runs this loop continuously. Each cycle collapses uncertainty by one move.

Spec

Define what you want and what "done" looks like

Plan

Design candidate paths with hypotheses and success criteria

Prove

Gather evidence and verify against spec criteria

Learn

Update beliefs, surface tensions, and spawn next cycle

In practice

How It Works

01

Dump your thoughts

Type whatever is on your mind. No structure needed. Your messy input is the raw material.

02

Explore your options

Yawn organizes your uncertainty into moves — concrete next steps with proof requirements.

03

Let Yawn handle the rest

The autonomous loop executes, proves, learns, and surfaces what to do next. Repeat until done.

The holarchy

Yawns Nest Inside Yawns

Every Yawn is both a whole and a part. They spawn children, split when complexity grows, promote when proof is met, and retire when uncertainty is resolved.

yawn.ai — root identity
Platform — infrastructure, auth, deploy
Intelligence — agents, orchestration, models
Experience — UI, chat, feed, dashboard
Distribution — growth, marketing, network
Economics — pricing, revenue, rewards
Knowledge — templates, docs, patterns
Organization — identity, coherence, legal

Spawn

When uncertainty exceeds the control capacity of the parent, a child yawn is born.

Split

When working memory is exceeded — too many moves, too many agents — the yawn divides.

Retire

When uncertainty is resolved or the yawn produces no actionable proof, it dies. Death is healthy.

The core invariant

Yawn does not optimize action. Yawn optimizes the collapse of uncertainty into agency-preserving action — at every scale.