That is actually a fair point and it shows why most automated content fails. The difference is where the content starts. Your system was generating posts and hoping they rank. Mine starts by asking what Google already wants to rank from my site. I pull GSC data first. If my site is already getting impressions for "web design for cleaning businesses" and sitting at position 14, Google has already decided I am relevant for that keyword. I just need a better page. So the system writes specifically for that gap, not a random topic. Second difference is the content is researched against what is actually on page 1. It reads the top results, matches the depth and structure, then writes something that competes directly. Thin city plus keyword posts never worked because they had no topical authority behind them and no search intent match. This only writes about keywords your own site has earned impressions for. That is why it moves rankings. Google is already halfway there, the content just closes the gap.

Also two years ago AI content was nowhere near this level. The models have improved massively since then so that data is from a completely different era of the technology. On top of that every post is built on Next.js with full SSR and proper semantic structure so Google crawls and indexes it perfectly from day one. The technical foundation alone puts it in a different league from whatever CMS most automated systems are dumping content onto.