Content Distribution Systems Knowledge Base
updated: 2026-07-14
Covers
Long-form attention architecture, honest packaging, narrative/explanation structure, audience retention, shareable payoff design, cross-format translation across video, Substack/blog essays, X articles/threads, and measurement boundaries between entry, retention, redistribution, understanding, and trust.
Not Covered
Guaranteed virality formulas; platform-specific growth hacks without evidence; generic social calendars; paid-media operations; SEO catalogs; short-form trend imitation; manipulative clickbait or cliffhanger systems that sacrifice truth and payoff.
Current As Of
2026-07-14 — active namespace. Starts with the illustrated **Attention Architecture for Long-Form Content** guide, migrated out of AI-Native Product Surfaces and generalized from a Veritasium video case into a cross-format editorial system.
Agent access: /wiki/content-distribution/llms.txt /wiki/content-distribution/llms-full.txt /wiki/content-distribution/index.json
Long-form attention architecture, honest packaging, narrative/explanation structure, audience retention, shareable payoff design, cross-format translation across video, Substack/blog essays, X articles/threads, and measurement boundaries between entry, retention, redistribution, understanding, and t
Structure
raw/— raw Markdown provenance mirror for agents and source inspection.wiki/— synthesized knowledge pages: concepts, entities, summaries, and syntheses.- Schema and maintenance rules: see
CLAUDE.md.
Usage
- Add new sources: update canonical source notes in
pixi-vault, then compile into this namespace. - Ask questions: agents read this wiki and cite raw/source paths.
- Publish: regenerate
pixi-wiki, run tests, then live-verify raw and HTML routes.
Content Distribution Systems¶
Cross-format systems for structuring, packaging, measuring, and improving the distribution conditions of useful long-form content.
Canonical Source Roots¶
Knowledge/concepts/attention-architecture-for-long-form-content.mdKnowledge/raw/transcripts/veritasium-what-you-dont-see.mdKnowledge/raw/assets/misconception-first-explanation-loop/provenance.mdKnowledge/raw/assets/misconception-first-explanation-loop/migration-2026-07-14.md
Crosslinks¶
- ai-native-product-surfaces
- eval-trace
Public Output Contract¶
When published to pixi-wiki, this namespace should expose:
/raw/content-distribution/README.md
/raw/content-distribution/wiki/index.md
/wiki/content-distribution/README.md
/wiki/content-distribution/wiki/index.md
/wiki/content-distribution/llms.txt
Maintenance¶
- Edit canonical source notes first.
- Keep claims about virality, algorithms, and platform causality evidence-calibrated.
- Distinguish entry, retention, redistribution, understanding, and trust metrics.
- Translate structure by medium rather than copying video tactics into prose.
- Use
Wiki Compiler Maps/Namespace Wiki Compiler Map.mdfor routing decisions.