Information architecture
Topics
The whole knowledge base, organised topic-first around the Four Pillars of AI search visibility. One hero hub, four pillars and three cross-cutting tracks. Every service, framework, lab build and article maps to exactly one pillar, ordered by live UK search demand.
The outcome
AI Search Visibility (AEO / GEO / LLMO)
Being the cited, trusted answer inside AI Overviews, ChatGPT, Perplexity and Gemini, not just ranking a blue link.
This is the centre of gravity, and on cleaned commercial-intent demand it is the largest cluster on the site, ahead of technical work and everything else. The goal is not a blue link on page one but being the source an AI answer is built from. Getting there rests on the four pillars below, which is how visibility is actually earned.
AI Search Visibility (AEO / LLMO)
AI Search Visibility work makes your brand and its leadership the cited, trusted source when buyers, investors and journalists ask an AI about your market. SEO competes on keywords; AEO competes on entities, and most organisations are currently invisible or ambiguous to the models.
AEO + LLMO Strategy
A twelve-month AEO and AI-visibility roadmap built around priority topic clusters, keyword targets, content cadence, link priorities and AI-readiness actions, mapped to monthly milestones and your commercial goals.
Instant AEO
An end-to-end programme that runs technical audit, opportunity analysis, competitor benchmark, content strategy, backlink plan and a 12-month roadmap in sequence, then adds a new site build with optimised information architecture and full deployment.
The Four Pillars Framework
The Four Pillars Framework groups the working levers of AI search visibility into four pillars, Technical Foundations, Topical Content, Trust Signals and Authority Network, plus a cross-cutting guardrails layer. It is synthesised from Google’s own primary sources on how generative AI features select what to cite.
Google AI Search Optimisation
Google’s official guidance is blunt: AI features pull from the same standard search index, so there are no AI-specific shortcuts, file formats or markup. Optimising for AI Overviews and AI Mode is optimising for human value, clarity and SEO fundamentals, and explicitly not the fads being sold around it.
The four pillars, how visibility is earned
Technical Foundations
Crawlability, rendering, indexing and structured-data foundations that decide whether you are even in the candidate pool.
None of the visibility work matters if a machine cannot crawl, render and index the page in the first place. This is the foundation layer, codified as a 330-point technical audit across four pillars, every check cross-referenced to a primary source. Second-largest cluster by demand and the strongest bottom-of-funnel intent.
Technical AEO Audit
A 330-point technical and AI-readiness audit. Every check is cross-referenced to a Google primary source and clustered into the Four Pillars of generative search, so you see not only what is wrong but why it matters and how to fix it. It surfaces the crawl, indexing, content, trust and entity issues that quietly suppress rankings and AI citations, with a fix list prioritised by competitive impact.
AEO Graph View
An Obsidian-style visual node graph of a website where each node is a page and each edge an internal link, with toggleable data layers, rankings, backlinks, status codes, on-page scores, analytics, technical issues and proposed information architecture, so structure and performance are visible at a glance.
Internal Linking Intelligence
A feature that auto-generates internal link suggestions from an uploaded site crawl, producing contextually relevant links from real structure rather than generic keyword matches, and flagging the missed opportunity when no crawl is provided.
Topical Content
Non-commodity, people-first content organised for passage-level extraction, the highest-leverage pillar.
Once a page is reachable, the question is whether it answers a real query well enough to be quoted. This pillar covers topical authority, content clusters, query fan-out and semantic structure. Google says useful content influences generative presence more than any other lever, and this is where the article stream lives and compounds authority over time.
Content & Newsroom Strategy
A content strategy and production pipeline that turns raw material into SEO/AEO-optimised articles with structured data, author schema, internal links and People-Also-Ask coverage, designed so authority compounds to named authors, not just pages.
Query Fan-Out
Query fan-out is the pattern where a single user question is silently decomposed into many concurrent sub-searches that run in parallel; the system then assembles the evidence into one synthesised answer. It means a page no longer needs to rank for one head keyword, it needs to be the best-cited page across the cluster of fan-out queries around its intent.
The Auto-Research Loop
An autonomous optimisation loop where an AI agent iterates on a single target, a prompt, module or Skill, to maximise a scalar metric computed by an automated evaluator. Hypothesise, modify, evaluate, keep if better else reset, repeat. The binding constraint is not the loop; it is knowing what to measure.
Seasonal & Trend Validation
A content-pipeline feature that validates a search term against seasonal peak data and trend direction before use, showing the peak month, auto-inserting the highest-volume term into the title and heading, and alerting if the chosen term is currently off-peak.
Search-led information architecture: how we sized our own site by demand
Most sites are organised by their own org chart, not by how people search. The demand-weighted method we use to fix that, first on a client, then on ourselves.
We built a score to catch generic content. Its first casualty was our own spec.
The Non-Commodity Score is a pre-publish gate for generic, commoditised content. Its v0 spec failed its own test. Here is the teardown and the rebuild.
Trust Signals
The E-E-A-T evidence that a real, accountable expert stands behind the page: authorship, sourcing, credentials.
The third pillar is the experience, expertise, authoritativeness and trust that tells Google and AI models a real, accountable person stands behind the page. It is the newest pillar on the site, opened with our own Non-Commodity audit as the first proof, and the priority for the next commissions.
Cross-cutting tracks
Measurement & Attribution
Joining what the team does to what the site does, attribution that survives a CFO conversation.
Search and AI visibility only earns budget when it can be tied to outcomes a CFO will accept. This track is about honest measurement, separating what the team did from what the market and the algorithm did, and building monitoring systems that improve against a defined metric. It anchors the Site Performance Operating System and most of the lab builds.
Competitor & Opportunity Analysis
Two connected analyses: an opportunity gap that sizes the organic prize available to you in revenue terms, and a competitor benchmark across organic, paid and social that shows exactly where you are losing ground and what to fix first.
Site Performance OS
A four-layer operating system that captures every task (input), measures every metric (output) and joins them through an attribution model that survives a CFO conversation, closing the gap that gets agencies fired when the algorithm gives or takes.
The Site Performance Operating System
A four-layer methodology for linking marketing activity to measurable site performance: capture the inputs (every task), measure the outputs (every metric), join them through attribution windows, and surface all three on a cadence, so value is provable rather than asserted.
AI Search Query Capture
A free Chrome extension that reveals the web-search queries ChatGPT and Claude run when they browse, and the source URLs they cite, captured live and on-device. It makes query fan-out visible, the bridge between a natural-language prompt and what actually gets retrieved and cited. Live on the Chrome Web Store.
EventCapture
Event content, keynotes, panels, podcasts, notes, photos, evaporates after the event. EventCapture records it on a phone, offline-first, and turns it into attributed, AEO-optimised content the same day: event reports, articles, social posts, show notes and a quote bank.
Domain Gap Alert
A lightweight hook: enter a seed term, the tool pulls related search terms, checks whether your domain ranks for any, and if it does not, generates an alert, "you are invisible for these terms, here is the cost of that." It quantifies the gap rather than asking a prospect to trust that search matters.
Paid Media & Integration
Integrated paid search and paid social that reinforce one entity story rather than running in a silo.
Paid works best when it reinforces one entity story rather than running in a silo. Strong, stable commercial demand led by ppc, and thin on the current site with a single service, so a clear expansion opportunity. It supports the same authority signals as the organic and AI-visibility work so the channels compound.
Guardrails, Agentic & Future-proofing
Retiring the anti-patterns, plus the forward edge: agentic search, AP2 / UCP, AI integration and enablement.
The cross-cutting hygiene layer that keeps the other pillars honest (no llms.txt, no chunking, no scaled-content abuse) plus the forward edge of agentic search and AI enablement. Low search volume, high differentiation value. This is the home for point-of-view content and the Agentic OS.
AI Integration & Training
A workflow-by-workflow map of where AI saves your team time, ranked by effort versus impact, with recommended tools, an implementation roadmap and a training plan so the capability sticks after the engagement ends.
The Agentic OS
The Agentic OS turns an LLM assistant from a passive question-answerer into an active operating system by codifying work into a four-layer hierarchy: Domains, Tasks, Skills and Automations. Codifying behaviours into repeatable Skills, rather than running them ad hoc, makes the model a reliable team member rather than a slot machine.
The field notes
Frameworks, builds and what is changing in AI search.
Sent occasionally, never noise. The thinking behind the work, and the experiments before they ship.
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