Part Two: Brand Dynamics - Built for the Legible-Lovable Law
Part two: the reader that can't be charmed
In part one I left a brand standing in front of a second audience. Not a human being, but a machine. One that doesn’t feel, extends no charity, and reaches a verdict in milliseconds. This is the half of Marzano's law that keeps our clients up at night, and it is the half almost everyone is getting wrong.
The error is to treat it as a technical problem. The brief goes downstream, to an agency or an in-house team, and comes back as a checklist: optimise the content, fix the schema, chase the citations. I’m not disputing these have their place, it’s just none of them is the actual job.
Because the machine is reading everything, not just your website. The totality of what exists about your brand, compressed into a single recommendation in the time it takes to sip your coffee. Your brands own surfaces, third-party reviews, forum threads, analyst notes, the way a customer described you on Reddit eighteen months ago. It assembles all of it, and decides whether the picture coheres.
And that is the word that matters. Coherence.
A machine can tell when you don't mean it
A human reader forgives incoherence. They meet a brand that says one thing and does another, and they quietly resolve the gap, because people are generous and busy and inclined to give you the benefit of the doubt.
The machine does no such thing. It notices that the claim on your homepage is contradicted by the reviews three clicks away. It registers that the proposition you describe is not the one your customers actually talk about. It reads the gap between what you say and what you deliver, and it grades you on it, without sentiment and without appeal.
The 21st Century Brand and Semrush research makes this visible in the data. Look at how the strongest brands show up. Notion appears across AI systems with the same description again and again; over ninety percent of mentions are simply "Notion," because the product, the proposition and the way people use it all point at the same idea. Rocket Mortgage's turnaround in AI visibility followed a genuine shift in strategy and narrative, not a campaign to game the sources. Shopify's authority is distributed across a whole ecosystem of developers, partners and reviewers, which is exactly why no competitor can fake it.
The pattern underneath all three is the same. The machine rewards coherence. And coherence is not made in the content layer. It is made upstream, in the strategy, long before anyone writes a word of copy.
Legibility is a strategy problem in disguise
This is the point the technical framing misses. Being legible to a machine is not about feeding it the right signals. It is about being a brand that is coherent enough to be read correctly in the first place: a clear position, a proposition that matches the experience, a story that holds together no matter which fragment the machine happens to pick up.
You can’t fake that. You can’t buy it. You can’t bolt it on at the end. Which is precisely why it doesn’t belong with a marketing function downstream. It belongs at the level where the position is set.
So a brand now stands in front of two readers, judging on entirely different terms. One you move by being lovable. One you convince by being legible. Most businesses are strong with the first and still invisible to the second, or clean for the second and inert to the first.
In part three: why you can’t choose between them, and why the brands that win are built for both.
What this means if you are a CEO at an inflection point: if your brand is hard for a machine to read, the cause is almost never technical. It is a strategy that has not been resolved clearly enough to be understood. Fix the coherence at the source, and legibility follows.
This is part two of a three-part series on building brands for humans and machines. Part three brings the two readers together.
* The Legible-Lovable Law is a concept developed by Thomas Marzano in his manifesto Brand Constitutions: The Legible-Lovable Standard for Building Equity in an Agentic Economy (2025).
** AI visibility data and the priming and proving framework are drawn from research by 21st Century Brand and Semrush (2025–26).