A technical reference on AI search visibility. This site sells nothing, takes no engagements and endorses no products. Consulting enquiries are handled separately at hartzer.com.

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Three silos

Guides

Twelve guides on AI search visibility, grouped under three pillar guides: what AI search is and how it works, how to write and build for it, and how to measure it without fooling yourself.

The pillars

Start with a pillar guide

Each pillar guide covers its silo end to end and links to the four guides underneath it.

Abstract contour line illustration representing Understanding AI search
Pillar guide

Understanding AI search

Observed

What AI search is, how a generated answer is assembled, and how to read the studies that claim to measure it.

Read the guide →
Abstract funnel form illustration representing Optimizing for AI search
Pillar guide

Optimizing for AI search

Documented

The documented requirements for appearing in AI answers, and the widely sold tactics that failed replication.

Read the guide →
Abstract gauge dial illustration representing Measuring AI search visibility
Pillar guide

Measuring AI search visibility

Observed

What the platform reports contain, why one measurement is one draw from a distribution, and what a defensible AI visibility report discloses.

Read the guide →

Understanding AI Search

3 guides

Start with the pillar guide: Understanding AI search →

What AI search is, how a generated answer is assembled, and how to read the studies that claim to measure it.

Abstract crossing beam illustration representing How AI search engines choose what to cite
Understanding AI Search

How AI search engines choose what to cite

Observed

The retrieve, use and cite decisions pulled apart, with what each platform documents and what four contradictory overlap studies actually measured.

Read the guide →
Abstract stepped block illustration representing What changed when AI Overviews launched
Understanding AI Search

What changed when AI Overviews launched

Documented

The rollout dated from SGE onward, each publisher click study named with its sample and funder, and the numbers that get confused with each other.

Read the guide →
Abstract layered wave illustration representing Why AI search traffic behaves differently
Understanding AI Search

Why AI search traffic behaves differently

Observed

The three things called AI traffic, what the large panels agree and disagree on, and why the direct-traffic gap is a mechanism without a magnitude.

Read the guide →

Optimizing for AI Search

4 guides

Start with the pillar guide: Optimizing for AI search →

The documented requirements for appearing in AI answers, and the widely sold tactics that failed replication.

Abstract concentric arc illustration representing How to Rank in AI Overviews
Optimizing for AI Search

How to Rank in AI Overviews

Observed

The honest answer to the most-asked question in AI search: there is no separate ranking system, and what genuinely follows from that is narrower than most advice admits.

Read the guide →
Abstract offset block illustration representing Structuring Content for Answer Extraction
Optimizing for AI Search

Structuring Content for Answer Extraction

Observed

The markup died in May 2026 with no blog post. The editorial pattern it was confused with was never the same thing and never depended on schema.

Read the guide →
Abstract ladder rung illustration representing Technical Requirements for AI Crawlers
Optimizing for AI Search

Technical Requirements for AI Crawlers

Documented

Which user-agent token does what, which ones cost you visibility if you block them, and the one Google token that does not do what its name suggests.

Read the guide →
Abstract angled shard illustration representing AI Search Visibility for Law Firms
Optimizing for AI Search

AI Search Visibility for Law Firms

Unsupported

Almost nothing legal-specific about AI search has been independently measured. What the evidence supports, and what the advertising rules already cover.

Read the guide →

Measuring AI Search Visibility

4 guides

Start with the pillar guide: Measuring AI search visibility →

What the platform reports contain, why one measurement is one draw from a distribution, and what a defensible AI visibility report discloses.

Abstract pulse line illustration representing How to track AI Overview visibility
Measuring AI Search Visibility

How to track AI Overview visibility

Observed

What can honestly be measured about an AI Overview citation, what Google has reported since June 2026, and how many samples a number needs before it means anything.

Read the guide →
Abstract tapered column illustration representing How to evaluate an AI visibility tracking tool
Measuring AI Search Visibility

How to evaluate an AI visibility tracking tool

Unsupported

What a tool in this category can and cannot answer, why two honest tools disagree about the same brand, and the disclosures a number needs before it belongs in a report.

Read the guide →
Abstract scattered dot illustration representing What AI search analytics can and cannot tell you
Measuring AI Search Visibility

What AI search analytics can and cannot tell you

Documented

A dated ledger of what Google Search Console, Bing Webmaster Tools, analytics and server logs each report about AI search, and the questions none of them answer.

Read the guide →
Abstract horizontal band illustration representing Building an AI visibility report that survives scrutiny
Measuring AI Search Visibility

Building an AI visibility report that survives scrutiny

Observed

What belongs in an AI visibility report, how to sample so that a change can be told apart from noise, and the comparisons to keep off the page.

Read the guide →
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