The methodology
The work, mapped.
Nine load-bearing pieces, in the order they actually need to be done. Most engagements don't start at stage one — they start where the gap is.
Request a Diagnostic →Foundation
01
The Brief
The prompt library that defines what the brand is competing to be cited for. 100–200 buyer-vocabulary prompts, tagged by funnel stage, persona, and priority — the denominator every downstream metric runs against.
Most enterprises measure citation rate against the prompts they think buyers ask. The Brief measures against the prompts buyers actually ask.
Read the playbook on The Brief →
Foundation
02
The Verification Stack
The entity foundation AI uses to decide whether the brand is real. Organization schema, Wikidata entry, Knowledge Panel resolution, consistent identity across the third-party surfaces AI grounds its answers in.
Brands AI can't verify get weighted lower than brands AI has never heard of. Verification is the gate every other layer waits behind.
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Foundation
03
The Access Layer
The crawlability infrastructure that determines whether AI systems can read the brand at all. Robots.txt, sitemap hygiene, llms.txt where it applies, the technical permissions that decide whether content gets ingested.
Most enterprises block half the AI crawlers by accident, then wonder why pillar content isn't being cited.
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Authority
04
The Mention Graph
The third-party citation surface AI uses to build category consensus. Reddit, G2, Wikipedia, podcast transcripts, industry trade publications — the distributed conversation that determines who AI cites for category-level prompts.
The brands AI cites are not the brands publishing the most. They're the brands the rest of the internet is already talking about.
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Authority
05
The Trust Chain
The author entity and E-E-A-T infrastructure that makes content count for full credit. Real bylines, Person schema, sameAs verification to LinkedIn and Wikidata, credentials displayed, knowsAbout declarations.
Content published under "Team" or no byline starts from zero credibility, no matter how good the writing is. The Trust Chain is the highest-leverage single fix in the methodology.
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Distribution
06
The Citation Surface
The publishing layer beyond the owned domain. Substack, Medium, GitHub, dev.to, industry trades, contributor programmes — the platforms AI is structurally trained to weight more heavily than the company blog.
Owned content is one node in a graph that has many. Most enterprise content programmes optimise the one node and ignore the rest.
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Distribution
07
The Indexing Layer
The plumbing that connects published content to the indexes AI retrieves from. Bing Webmaster Tools and the AI Performance dashboard, IndexNow protocol, Google Search Console configured for AI Mode.
Microsoft owns most of the AI ecosystem's retrieval surface. Almost no enterprise team has logged into the dashboard that proves it.
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Distribution
08
The Agent Layer
The agent-readable surface buyers increasingly research from. AI tool directories where AI grounds its shortlists, Custom GPTs where they earn their place, MCP servers for SaaS, agent-readable documentation.
The buyer's first stop is increasingly AI, not the website. The brands building the agent layer now will be the ones agents already know how to talk to by 2027.
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Measurement
09
The Proof Layer
The framework that makes the work defensible at the line-item level. Five metrics tracked against documented baselines, rolling 12-week averages, written targets at 90 days / 6 months / 12 months, partial-attribution model that names its own limits.
A dashboard isn't measurement. The Proof Layer is what stands between a programme that survives the third quarterly review and one that doesn't.
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Where to start
The diagnostic is the work, before it's the conversation.
We don't pretend to know which of the nine stages applies to your brand without running the diagnostic. Some engagements are six months of foundation work alone because the entity layer was never built. Some are pure distribution and measurement because the foundation work was done well by a previous team and the brand needs to be moved into the AI ecosystem at scale. Some are full-stack from stage one to nine.
The diagnostic is a structured audit against the nine stages — typically a two-week engagement that produces a baseline visibility report, a stage-by-stage assessment of where the gaps are, a recommended sequence for the next ninety days, and an honest answer about which stages don't apply to your business at all.
It's a paid engagement. Roughly two weeks. Produces a document the leadership team can read and act on regardless of whether the next conversation is with us, with an internal team, or with another firm. We've handed clients the diagnostic and told them they don't need ongoing support because their gap was a single stage they could solve in-house. That's part of the work.
If the diagnostic surfaces ongoing work that we're the right firm for, that conversation comes after — not before.
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