Frameworks · Agentic AI strategy
BackTier Frameworks
The frameworks behind BackTier's agentic AI strategy work, created by Jason AI Wade. They describe how AI systems find, identify, trust and choose a business, and how that carries through to AI agents acting for buyers.
Core system
From being found to being chosen
AI Visibility Architecture is the parent discipline. The Entity Lock Protocol™ handles identity. The BackTier Visibility Path™ measures progress through it, and the Agentic Visibility Path™ extends it into action.
01 · The parent discipline
AI Visibility Architecture
How a business becomes discoverable, correctly identified, supported by evidence, included and selected by AI systems.
02 · Identity and interpretation
Entity Lock Protocol™
A method for aligning scattered signals around one stable description of who a business or person is, so AI systems recognize and cite them consistently.
03 · Measurement
BackTier Visibility Path™
Citation → Inclusion → Selection
Measures progress from an AI system using your evidence, to including you in an answer, to choosing you.
04 · Action
Agentic Visibility Path™
Citation → Inclusion → Selection → Transaction
Extends the path to the point where an AI agent acts for someone: buying, booking, routing or paying.
Operating standards
How the work stays accurate
One approved source, controlled AI systems and labelled evidence.
05 · One approved source
Authority Canon
One approved, versioned source about the business, a Book or a Story, from which the website, profiles, episodes and audio are built.
06 · Controlled AI systems
Bounded AI Stack
AI systems deployed inside an explicit control boundary, with every output limited to verified, source-labelled material.
07 · Evidence
Provenance & Confidence Standard
Every factual claim in audits, research and case studies is tagged with its source, confidence and date, and causal claims are flagged as unproven.
Layers & research
The detail underneath
08 · Overview
AIV Framework
How the layers of AI visibility fit together.
09 · Layer
Retrieval Pathway Control
The signals that tell AI systems which sources to trust and which businesses to cite.
10 · Layer
Interpretation Correction Loops
Finding what AI systems get wrong about a business and correcting it systematically.
11 · Layer
Decision Layer Insertion
Placing a business inside the AI answers that shape a buyer's choice.
12 · White paper
The Optimization Objective Principle
How optimization disciplines form, with a test that can be failed separating AI visibility from SEO.
Put the frameworks to work
Frameworks are only useful when they change what a business does. We use them to plan your AI strategy, then measure what changes.