Resource Hub: AI Visibility Strategy for Practitioners
Read in sequence
sorilbran.com · Five-Talent Strategy House · 2026
The Mental Models Behind AI Visibility Strategy
Before tactics, there’s architecture. This section covers the foundational concepts you need to understand how machines find, evaluate, and choose who to recommend — and why the sequence matters.
AI visibility strategy isn’t one problem. It’s a stack of problems, each one sitting on top of the last. You can’t optimize for being recommended if you haven’t solved being credible. You can’t optimize for being credible if the machine can’t reliably identify you in the first place.
The pieces in this section are designed to be read in sequence. Each one builds on the last. Together they give you a complete mental model for how AI systems actually work — and where your strategy has to account for behaviors that search engine optimization never had to think about.
How to Build a Canonical Bio That Machines Can Read
The first brick of AI visibility. Your canonical bio is the machine’s primary anchor for connecting your content, your credentials, and your expertise to a single named entity. Everything else builds on top of this.
What to Do When the Fetch Tool Fails
Fetch Tool Failed isn’t an error message. It’s a diagnostic. There are three distinct reasons it happens, and each one has a different fix. Here’s how to tell them apart — and what to do about each one.
3 LLM Behaviors Your AEO Strategy Has to Optimize For
Large language models don’t behave the way search engines do. They recall, retrieve, and infer — three structurally different behaviors with three different optimization requirements. Most AEO strategy is only built for one of them.
The Three Visibility Tiers: Legibility, Eligibility, and Recommendability Explained
Legibility, Eligibility, and Recommendability are sequential gates — not interchangeable priorities. You cannot skip a tier. This piece tells you where you’re trying to land, how to diagnose which tier is your bottleneck, and what the failure mode looks like when you try to skip one.
AI Foundations is a growing resource. New pieces will be added as frameworks develop and as the landscape evolves. The sequence above reflects what’s live now. Check back — or follow along on LinkedIn where new thinking surfaces first.
