← homeKatya Shalel
Free guide

Visibility Without Budget

Clear public facts can make your work easier to understand. This guide helps you reduce ambiguity and test what particular AI products actually retrieve, cite or recommend.

Why it matters: Clear, consistent facts can reduce ambiguity. Whether a particular AI product retrieves, cites or recommends you must be tested separately. Repeating your own claim does not create independent confirmation.

Step 1

Assemble your entity

Give readers a clear description of who you are, what you do and for whom. Keep the underlying facts consistent across relevant pages and profiles, and explain name variants where useful. Different wording is not automatically a different entity; check whether a particular product identifies you correctly.

Prompt · canonical entity
Assemble a canonical entity definition from my data: [name, role, product, one line on what I do]. Give three versions of the same wording: 60 characters for a bio, 160 for a meta description, 300 for profiles. In a separate list, give every spelling of my name and brand, including transliterations, that should appear next to the definition. The wording must be precise with zero surrounding context.
Step 2

Coin your terms

Define concepts precisely and distinguish your terminology from established meanings. Clear definitions and links to an originating text can help readers assess attribution. Repeating a term does not guarantee that an AI product will retrieve your work or attribute the concept to you.

Prompt · your terms
Here are my texts: [paste two or three]. Find the ideas I phrase differently from the industry default. For each, propose a one-to-three word term, a one-sentence definition, and a check: is the term already taken by an established meaning. Discard anything that sounds like marketing, keep only what describes a mechanism.
Step 3

Publish where machines read

Adapt useful material to the audience and format while keeping facts and definitions consistent. Synonyms and translations can be appropriate when their relationship is clear. Links to the canonical source help readers locate the original; they do not guarantee indexing, citation or a transfer of ranking weight.

Prompt · one idea, three platforms
Here's an essay: [paste]. Adapt it for three platforms: [for example LinkedIn, Substack, an industry outlet]. Keep the meaning of defined terms clear; explain useful synonyms or translations. For each version: its own opening two lines for that platform's audience, length native to the format, and a closing link to the canonical source of the text.
Step 4

Make your site machine-readable

Check that important public facts can be accessed and extracted through the route you are testing. Use suitable structured data and canonical URLs where relevant. An llms.txt summary is optional; document the client and observed behavior before claiming support. A technical correction does not establish a one-day change in citation or recommendation.

Prompt · llms.txt
Assemble an llms.txt for my site. Inputs: [who I am, the product, my terms with definitions, links to canonical texts and profiles]. Write in short statements with zero marketing, so a model can quote lines directly. Structure: who, what I do, key concepts with definitions, where to read, official profiles.
Level up

Measure legibility, not reach

Choose questions, products, repetitions and follow-up timing for the decision, observed variability and available budget. Record answers, dates and conditions. Keep retrieval, citation and recommendation separate, and investigate missing evidence before choosing a change. A before-and-after difference alone does not establish its cause.

Go deeper

This is guide two of four. The full course runs on a waitlist

For current course availability, email shalelekaterina@gmail.com