0.1.8 — Qualitative Diffusion (App Slot Machine Mode)

Qualitative Diffusion (QDAD)

Diffusion, re-implemented at a purely qualitative scale.

Algorithm Design Mode is replaced by App Slot Machine Mode — the Qualitative Diffusion App Designer.

Technique

Classical diffusion	Qualitative Diffusion
Continuous noise	Controlled qualitative noise at high temperature
Denoising network	Critic agents (reverse diffusion / score matching)
Latent basis	Nouns × verbs as orthogonal basis directions
Image from a prompt	Buildable agentic coding prompt from an aesthetic app prompt

Pipeline (LangGraph)

foundation → grid → noise → denoise⟲ → synthesize

1. Foundation — N nouns + N verbs (shared qualitative basis)
2. Grid — N×N FeatureAgents bound to noun[i] × verb[j]
3. Forward diffusion — parallel noisy features at Temperature Scale
4. Reverse diffusion — CriticAgents clean the matrix over Denoising Steps
5. Decode — Synthesizer emits a structured App Build Prompt + transparent matrix

Philosophy

• Language is the computational medium
• Nouns and verbs act as orthogonal basis directions
• High temperature = controlled qualitative noise
• Critic agents = qualitative reverse diffusion / score matching
• Vague Midjourney-style prompt → concrete, buildable app specification

Package

• deepthink/qdad/ — state, nodes, graph, pipeline, utils
• deepthink/chains/qdad_chains.py
• Brainstorming-identical frontend shell + QDAD controls (N, temps, steps)
• Tests: tests/phase_qdad.py

See README section New in 0.1.8 — Qualitative Diffusion and RELEASE_NOTES.md.