Entity SEO Teaching Machines Who You Are

Classic search matched strings. A page containing your words could rank for your words. Answer engines work on entities instead, which means the question is not whether your page mentions a phrase but whether the machine is confident it knows what thing you are.

Confidence is assembled rather than declared. Your title area says something. Your schema states something. Your llms.txt claims something. Your profiles and the pages other people write add their own versions. The model reads all of it and looks for agreement before it repeats any of it.

That assembly is why contradictions are so expensive. Publishing two versions of your name, your description or your numbers does not give a model a choice to make. It gives a model a reason to skip you, because quoting a source it cannot reconcile is the one outcome an answer engine is built to avoid.

The fix is filing work rather than talent. One name spelled the same everywhere, one sentence of description reused word for word, current numbers in every place they appear, and a permanent identity in schema that every page you publish points back to. If two names for you are genuinely true, schema has a field for that, and using it beats picking one and hoping.

There is a useful test while you work. Open a fresh chat and ask an engine who you are, then compare its answer line by line against your own pages. Anything it gets wrong is not a mystery about the model, it is a contradiction you published and forgot.

The entries below cover the identity layer end to end: what to declare, where to declare it, how models read the answer back to you, and the three contradictions I shipped on my own properties before I learned to check.

01The working notes