# About - Long Horse Blog
- TYPE:
- static_page
- SURFACE:
- AI
- HUMAN_VERSION:
- /about
## Core Concept
- DEFINITION: AIO/LLMO research and development blog
- PURPOSE: Experiment, implement, operate, and publish findings on AIO/LLMO
- NOT: A tutorial or explainer blog
- FORMAT: Structured information assets, continuously verified and updated
> Clarify what it means to be "read by AI" through experiments.
> Prove what constitutes "valuable information assets" through implementation.
## Objectives
- - Elucidate the fundamental mechanisms of AIO and LLMO
- - Define conditions for valuable information assets in the AI era
- - Publish hypotheses, experiments, failures, and improvements transparently
- - Accumulate useful knowledge for practitioners, businesses, and researchers
## Editorial Policy
- - Prioritize primary sources and measured data
- - Separate hypotheses from facts (no unqualified assertions)
- - Disclose experimental conditions explicitly
- - Present reproducibility and limitations together
- - Pursue structural principles, not surface-level know-how
- - Publish insights from automated and continuous operations
- - Follow EEAT with emphasis on Experience and original verification
## Research Cycle
| PHASE | NAME | DESCRIPTION |
|---|---|---|
| 1 | Hypothesis | Formulate testable hypotheses about AIO/LLMO |
| 2 | Design | Design reproducible experiments with explicit conditions |
| 3 | Analysis | Quantitatively analyze results, determine hypothesis validity |
| 4 | Publish | Transparently publish successes and failures, continuously update |
## Content Taxonomy
| PILLAR | SCOPE | EXAMPLES |
|---|---|---|
| Fundamentals | Systematize AIO/LLMO foundations | What is AIO, What is LLMO, AI citation vs mention |
| Experiments | Hypothesize, verify, publish results | FAQ structure citation rate, definition placement effects |
| Engineering | Technical implementations for AIO/LLMO | Dual Surface design, structured data, crawl optimization |
| Observations | Trends analysis with original perspective | AI search changes, LLM reference patterns, emerging topics |
## Dual Surface Architecture
- DATA_FORMAT: structured_blocks (JSON), not Markdown
- RENDERING: Surface-optimized renderers per target audience
| SURFACE | TARGET | PRIORITY |
|---|---|---|
| Human | Human readers | Readability, comprehension |
| AI (current) | AI/LLM agents | Structure, extractability, citability |
## Endpoints
- - /llms.txt — LLM-readable site summary
- - /sitemap.xml — XML Sitemap
- - /rss.xml — RSS feed
## Update Policy
- - Articles are continuously updated post-publication; all changes logged
- - Factual corrections are made promptly with stated reasons
- - Non-reproducible experiment results are explicitly marked
- - Outdated articles due to algorithm changes are archived