Why I am Betting on Directories against Google AI
Google AI Overviews answer many questions without a click. If you search for "best AI tools," Google gives you a list right there.
This is the main threat to my new projects. I am building three directory sites: Top AI Tools, Find Games Like, and Open Alternative To.
I am testing a specific bet. By October 2026, at least one site must get 200 organic clicks per month from specific comparison or filter pages. If this fails, I will publish my data and admit I was wrong.
Google AI is good at listing what exists. It is bad at three things:
Attribute filtering: You cannot easily ask an AI for "open source tools that work offline and have a mobile app." My sites use structured databases to let you filter by these exact needs.
Negative space: Most AI answers stay positive. My game site uses AI to find reasons to avoid a game. It tells you who should skip a title.
Freshness: AI relies on web mentions which can be old. My directory pulls GitHub data weekly to show if a tool is actually being maintained.
I am also targeting the "second stage" of research.
People use AI to find a list. Then, they search for a specific comparison like "Appflowy vs Anytype." That second search has high intent. They want a verdict, not just a paragraph of text. Structured data wins this battle.
My setup is cheap. It costs about $25 per month. This allows me to run the experiment for a year without pressure.
I am watching for three signs of failure:
- High impressions but zero clicks on comparison pages.
- Google rejecting my sites for low quality even after improvements.
- People moving all research from search engines to LLM chats.
I am testing three narrow sites instead of one big site. This lets me see which intent type works fastest. If one works and two fail, that is still a win. I will learn what people actually want.