The Directed Grid: How AI Should Work Inside a B2B Company
AI in a B2B company should run as a directed loop: a human sets the question, Radar measures, Vector qualifies, Hive builds, and a human decides. Full model.
Read the field noteResearch, methods, failures, and build notes for teams earning AI visibility and shipping AI products. No recycled playbooks. No unexplained scores.
Decision-stage visibility and evidence architecture.
Methods, experiments, and corrections.
See the evidence behind every number.
What broke, why it broke, and what changed.
AI in a B2B company should run as a directed loop: a human sets the question, Radar measures, Vector qualifies, Hive builds, and a human decides. Full model.
Read the field noteThree ways in
The library is organized around decisions, not content categories invented for search engines.
Start with decision-stage visibility, evidence architecture, and what an AEO score can and cannot tell you.
Read foundationsInspect how Radar scores, how entity resolution works, and how we test our own audit architecture.
Read the methodsFollow experiments across engines, referrals, citations, and volatile recommendations.
Read field notesLatest notes
The most recent field notes, newest first.
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Read articleMost AI visibility scores are opaque grades you cannot defend. Here is how Radar scores AI visibility in three separated layers, with a trail behind every number.
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