u/BugBoth

In the tool I use to track AI Citations for my brands I have noticed pretty interesting metrics that really show how ineffective llms.txt and llms-full.txt files are curently

Most visited pages by AI Bots:

1. /
2. robots.txt (25x more visits than llms.txt file)
3. sitemap.xml (17x more visits than llms.txt file)
   ...
4. llms-full.txt
5. llms.tx

So a whole new crop of tools are popping up everywhere. Massive R&D dumping into AI search.

As a marketer, how are you keeping up with it all?

Are you using tools built just for SEO? Are you implementing new ones focused on AEO?

I am really interested to see where all this ends up in 2 years. Like, budget-wise...how do we slice the little spend we have to track all....this?

https://natlawreview.com/press-releases/ai-sightline-launches-complete-platform-ai-search-analytics

I think Reddit is going to kill AI search and ultimately Reddit.

1. Reddit sells access to our posts to major LLMs. AKA...they sell the data
2. Reddit becomes the primary source for a large portion of LLM query fanout and citations
3. Content creators figure this out and flood Reddit with AI generated content and brand spam

Reddit becomes AI slop - AI creates AI slop, the slop is posted to Reddit, AI suggests it's own slop in citations.

The circle of life has been defined and we're all participating in it's decline.

Spent the past couple months testing tools in this space and kept getting asked about it, so figured I'd write up notes.

Quick context: the gap between Google rankings and AI visibility is bigger than most marketing teams realize. Brands crushing SERPs are sometimes ghosts inside ChatGPT and Perplexity. Different signals, different game, and most of us are only measuring one side of it.

Tools I've actually spent real time inside (no particular order):

Otterly AI Prompt-level tracking across six engines. Easy to set up, pricing scales with prompt volume. I quit because the UX sucks...

Peec AI Strong on source attribution and competitor benchmarking. Clean UI. Costs a bagillion dollars and coulndt justfy the spend anymore.

AI Sightline Daily scans, composite visibility score across six engines including Google AI Overviews, and a recommendations engine that flags the specific pages dragging you down. Also has an MCP server if you want to pipe the data into Claude or Cursor. New and the UX is busy, but good for the price.

Profound Citation pattern analytics. Enterprise-leaning, but the depth of analysis is real. Bruh, so expensive!

LLMrefs Narrower focus on LLM citations specifically. Lighter stack if you only care about ChatGPT and Perplexity. Lightweight but kinda meh.

A few things I've noticed regardless of tool:

1. Add an "AI search / ChatGPT / Perplexity" option to your inbound lead source dropdown. The numbers will surprise you.
2. The brands getting cited consistently aren't the loudest publishers. They're the ones with clean structured data, clear topical authority, and steady third-party mentions.
3. Visibility moves week to week. If you're only checking monthly you're missing most of the signal.

The gap is widening between brands that exist in AI answers and the ones that don't. When someone asks an LLM about your category, either you're in the answer or your competitor is.

What are other people using here? Especially curious about anyone running this across multiple brands or pulling the data into a custom dashboard.