Self-Improving SEO Engine: Loop Engineering with AI Agents That Write, Judge & Publish
The script explains “loop engineering” for AI SEO, where a builder agent writes content and a separate judge agent grades it out of 100, lists flaws, and forces revisions until a passing score (e.g., 90%+) is reached, then the content publishes automatically. The speaker shares results showing a site growing to about 222 clicks per day and ranking #1 in Google AI Overviews for “best AI community,” arguing the key is removing the human from repetitive review so “the machine becomes the loop.” It demonstrates setting a definition of done, choosing builder/judge models (including free or cheap options), setting iteration limits, and running the loop inside an Agent OS. A second method scales the same idea via Hermes Kanban boards with multiple agent roles and a judge gate before “done,” with logs saved to shared memory.
00:00 Self Improving SEO Engine
01:03 Proof It Ranks
02:15 Loop Setup Walkthrough
03:07 Judging Models And Rounds
04:10 Scoring And Iteration
04:52 Beyond SEO Video Loops
06:38 Method One Quick Loop
07:55 Method Two Kanban Team
09:31 Five Part Framework
10:37 Memory Logs And Costs
11:24 Offer And Objections
12:54 Wrap Up And Next Steps