AI Evaluators Are Your New PM Audience

You have spent your career writing for two audiences: the customer and the internal stakeholder. There is a third audience now, and most product teams have not noticed it exists.

The short version

AI evaluators are your new PM audience. AI systems increasingly decide whether your product gets recommended, compared, or dismissed before a human ever sees it, so product legibility to a model is now part of your funnel. This is not SEO with a new coat of paint: SEO optimized for ranking, this optimizes for being correctly understood and correctly recommended by a system reasoning about your product on someone else's behalf. Get it wrong and the AI does not rank you lower, it describes you inaccurately or leaves you out of the comparison. The new deliverable is a structured, machine-readable statement of what the product does, who it is for, and how it differs, kept accurate as the product evolves. Fold it into downside exposure: ask what an outside AI needs to know to evaluate your product correctly.

AI systems are increasingly the thing that decides whether your product gets recommended, compared, or dismissed before a human ever sees it. Someone asks an AI assistant to compare project management tools, or to evaluate whether a vendor fits their compliance requirements, and the AI's answer is now a meaningful part of your funnel. That answer depends on how legible your product is to a model: how well your positioning, your docs, your feature descriptions, and your differentiation are structured as something a model can parse and reason about, not just something a human can skim.

This is not SEO with a new coat of paint. SEO optimized for ranking. This is optimizing for being correctly understood and correctly recommended by a system that is reasoning about your product on someone else's behalf. Get it wrong and the AI does not rank you lower, it describes you inaccurately, or worse, it leaves you out of the comparison entirely because it could not tell what you actually do. This is the discipline I called writing for machines(coming Jul 16), pushed from your content to your product itself.

Practically, this means product marketing and product management need a new deliverable: a structured, machine-readable statement of what the product does, who it is for, and how it differs from adjacent categories, kept accurate as the product evolves. Not a blog post. Not a one-pager buried in a deck. Something closer to a schema than a narrative.

I would fold this directly into downside exposure. When you prioritize an AI feature, you already ask what happens when it is wrong. Now ask a second question: if an AI system outside your walls is evaluating this feature to decide whether to recommend your product, what does it need to know to get that evaluation right? If you cannot answer that in a sentence, you have a discoverability problem you do not know you have yet.

Pick your single most important product line. Ask a general model, cold, to describe it and say who it competes with. The gap between that answer and the truth is your first ticket.