SEO Intelligence Bot
The unfair advantage in SEO isn't writing faster than everyone else — it's knowing what to write before the opportunity is gone. This is the system I built to know first.
The problem
Most SEO content calendars are reactive by the time they're built. A trend surfaces, someone notices it in a Slack channel two days later, a brief gets written, and by the time the article ships the search opportunity has already peaked — or ten competitors beat you to it.
News alone isn't a strategy either. Everyone reading the same headlines produces the same content. The actual edge comes from layering signals that arrive before the obvious ones — market anomalies, rising search queries, your own ranking movements, competitor gaps — and having something fast enough to catch all of them at once.
The system
Seven signal sources run on independent schedules — from 15-minute news sweeps to daily Search Console pulls. Every raw signal gets passed through an LLM interpretation layer before it ever reaches a human: the model decides whether it's noise, assigns a priority, and writes a specific content angle rather than just flagging that something happened.
News & narrative
RSS from major crypto outlets, scanned every 15 minutes
Market anomalies
Price, volume, and funding-rate spikes via CoinGecko / CoinGlass
Search trends
Rising queries before they show up in competitor content
Own performance
Search Console pulls flagging striking-distance rankings
Competitor gaps
What rival academy blogs just published, and what they missed
Token unlocks
Scheduled events with predictable market impact
See it work
A simulated version of the live feed below — same format, same priority tiers, same interpretation-before-alert pipeline as what actually runs in production. Real output stays private since it reflects live competitive strategy.
What this demonstrates
This is the difference between doing SEO and building the system that does SEO for you. Seven independent data sources, a shared interpretation layer, deduplication so nothing repeats, and a delivery channel that meets me where I already am. It's the same instinct from materials engineering applied to content strategy: stop reacting to individual failures, build the system that catches them before they happen.