The blog · Research & practice

Search keeps changing.
So do the questions.

Guides, investigations and experiments on technical SEO, AI discoverability and content intelligence. Written by a practitioner, organised by idea rather than by date, and honest about which pieces are current and which are history.

01 / Start here

Start with something useful.

Three pieces that show how I work: open the evidence first, then decide.

02 / Guided reading

Follow an idea. Not just an article.

One route through the technical evidence trail: how pages get rendered, how bots actually behave, and how to pull the data to check both.

03 / Knowledge map

Explore the ideas that connect.

Four areas I keep investigating. Three have published writing today; one is still being built.

Topic 01 · Published

Technical & enterprise SEO

Crawling, indexing, rendering, site speed, audits and the infrastructure underneath search.

Browse technical SEO →
Topic 02 · Published

Tools, measurement & workflows

Search Console, analytics, audit tools and the hands-on workflows that turn data into decisions.

Browse tools & measurement →
Topic 03 · In progress

AI search & discoverability

AEO, GEO, citation behaviour and how brands are found inside AI answers. First pieces are being researched, not yet published.

See what’s next →
Topic 04 · Published

Content intelligence

Content gaps, entities and semantic relevance, explored through my Content Quality Intelligence experiment.

See the experiment ↗

04 / Complete library

Browse all posts.

05 / The research queue

Questions I’m exploring next.

Research · Planned

How AI assistants discover, select and cite web content

AI visibility · Citation research

Playbook · Planned

Using Screaming Frog and AI for richer content investigations

Auditing · Automation · Evidence

06 / The philosophy

Less recycled advice.
More useful thinking.

I write to connect what search data shows, what the technology makes possible and what readers actually need. Some answers come from experience. Others begin as experiments worth testing, and I label which is which.

01
Evidence before opinionOpen the crawl, the logs and the data first.
02
Findings must shipA recommendation needs impact, scope and a place in the queue.
03
Observed is not hypothesisedWhat I have seen stays separate from what I suspect.
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