AI Practice Knowledge BaseAI Self-Growth System
Information Gap Arbitrage
PremiumThe world is flat, but information spreads with lag. That lag is your profit.
Information Gap Arbitrage: Build an Automated Time Machine
"The future is already here -- it is just not evenly distributed." -- William Gibson
What you will get in this chapter
- A minimum viable information gap system (MVS)
- Arbitrage SOP and filtering rules
- Core metrics and acceptance criteria
One-sentence definition
Information gap arbitrage = capture source info -> localize and reframe -> publish fast.
You profit from time lag + context lag.
Minimum viable arbitrage system (MVS)
| Step | You need | Acceptance result |
|---|---|---|
| Sources | 1-2 Tier 1 sources | Stable new content every day |
| Filtering | Scoring model | Keep only the Top 10% |
| Rewrite | Localization template | Output has viewpoint and structure |
| Distribution | 1 channel | Publish within 24 hours |
Qualified signal: from capture to publish <= 6 hours.
Arbitrage SOP (standard process)
- Monitor: watch high-value sources (PH/HN/GitHub)
- Filter: use the scoring model to keep only high-potential items
- Rewrite: craft a viewpoint in the local context
- Publish: push to channel/site/newsletter
- Review: log clicks and saves, feed back into the scoring model
Information gap scoring model (core)
Scoring dimensions
- Time Lag: information diffusion delay
- Intent: user action intent
- Fit: relevance to your domain
- Virality: propagation potential
Scoring formula (0-100)
GapScore = 30*TimeLag + 25*Intent + 25*Fit + 20*ViralityDecision rules
- >= 75: must do (P0)
- 60-74: optional (P1)
- < 60: record only
Core metrics (must track)
Definition (default):
- Time window: unless stated otherwise, use the last 7 days rolling.
- Data source: use one trusted source (GA4/GSC/platform console/logs) and keep it consistent.
- Scope: only the current product/channel, exclude self-tests and bots.
| Metric | Meaning | Pass line |
|---|---|---|
| Time-to-Publish | Capture to publish | <= 6 hours |
| Signal Validity | High-score items / total items | >= 15% |
| CTR | Clicks / impressions | >= 1% |
| Save Rate | Saves / impressions | >= 3% |
Acceptance checklist
Sources are confirmed and produce steadily
Scoring model is defined and can filter Top 10%
Publishing can be done within 6 hours
Common mistakes
- Direct translation -> no value added
- No filtering -> low signal-to-noise, user churn
- Publishing too slow -> time lag disappears
Community case addendum (from developer communities)
The following are public community shares. Metrics are self-reported or taken from public pages and are not independently verified:
- HN Show HN: PingNews provides real-time alerts for HN/Reddit keywords with AI TL;DR. The author says Google Alerts is too slow and manual search does not scale, so they use real-time alerts to capture time lag. Link: https://news.ycombinator.com/item?id=43339885
Summary
Key takeaways
1. Information gap arbitrage is reprocessing, not copying.
2. Use a scoring model to filter and avoid noise.
3. Speed is a moat. Publishing within 6 hours is optimal.
Next chapter, we will cover Aggregation as a Service -- how to turn filtered information into a stable product.