我用 AI 智能體建立約 2,200 個頁面，最難的是辨別網站分析中的真實流量

I run a small Korean information site (guides on labor rules, taxes, game-store sales) and I let AI agents generate most of the pages. As of 2026-10-20 the sitemap has about 2,180 unique URLs. That same day, at 17:35 KST, the site had 161 visitors.

Building pages got cheap. Getting people to read them did not. That part is not news, but one thing I got wrong along the way might save you some time.

The mistake: counting my own checks as traffic

My workflow after publishing a YouTube Short is to open the link in the description to confirm it works. Over a few days those checks piled up in my analytics as a clean-looking "YouTube referral" bucket. It looked like 59% of that day's visits. It was mostly me.

How it showed up in the data, in case you want to look for the same pattern:

100% desktop, no mobile at all
almost all from one city
arrival pages hit a near-equal number of times each (4, 4, 4, 3, 3), not a long-tail shape
visit times matched my upload times

Once I excluded those, the day dropped from 207 to 87 visits. The trustworthy sources were smaller and weirder: developer communities (one batch, deep reads), direct visits, a Naver blog, and a handful from Q&A answers.

What I changed

A per-browser opt-out flag. Opening /?nohit=1 once in a browser stores a flag, and later visits from that browser are not counted.
UTM tags on every outbound link. About 95% of visits had no campaign tag, which made every channel comparison guesswork.
A rule that I do not use daily visitor counts alone to decide which channel to invest in.

Where I am stuck

Writing pages was the easy 90%. If you have built a content site mostly with agents: how did you separate your own QA traffic from real readers, and did you find a channel where a new, small site gets read at all?

Notes: I used AI tools to draft and structure this post and checked the numbers against my own dashboard. The site is in Korean: https://sungprofile.cloud/?utm_source=devto&utm_medium=referral&utm_campaign=dev_2610