AEO and GEO, in depth

Two disciplines, one shared foundation, meaningfully different KPIs, and why most practitioners blur them incorrectly

The editorial patterns that survive both AEO extraction and GEO grounding, and the patterns that lose in both

Six acronyms covering overlapping but distinct disciplines: what each one actually means in 2026, where they share work, and where they genuinely diverge

Every era of search created its own optimization discipline. AEO and GEO are the latest rupture, not the first, and the through-line explains what to keep and what to abandon

What llms.txt actually is, what llms-full.txt adds, who's adopting it, and how to ship one that AI engines might actually use

Schema.org has hundreds of types. Only a small subset moves the needle for AI engines, and the priority order is not obvious

Experience, Expertise, Authoritativeness, Trustworthiness: Google's quality framework was built for human raters but maps directly onto the trust signals AI engines weight

Why the traffic fell, how to tell an AI Overviews squeeze from an algorithm hit, and the moves that recover qualified visibility when the click is no longer guaranteed

The training-versus-grounding distinction that should drive the decision, the bots that actually matter, and the pragmatic stance most publishers land on

Citation share, share of voice across engines, attribution rate, and the difference between the metrics that matter and the metrics that flatter

Build vs buy, DIY vs agency, what each pricing tier actually buys, and the five questions that separate a defensible measurement vendor from a dashboard

Buyer journey nuance, product-led content patterns, and what to prioritize when your buyer is a technical decision-maker, not a consumer

Cybersecurity content has its own pacing (CVEs, incidents, vendor announcements) and its own buyer skepticism (sales-pitchy content gets discounted). Here's what changes in the GEO playbook

Ecommerce GEO covers product discovery queries, comparison shopping flows, and the rapidly-emerging AI shopping assistants. The playbook differs from content-first GEO

Product-led growth and Generative Engine Optimization evolved separately but reward the same artifacts. The PLG content stack is, almost by accident, the corpus AI engines most want to ground against

The shift to answer engines is not just a tactic change. It moves budgets, redraws team ownership, and resets the KPIs marketing reports to the board

Six grounded engines, two disciplines, one collapsing distinction between AEO and GEO, and the patterns that have stabilised enough to plan against

Why AI engines weight some publishers heavier than others, what an entity graph actually is, and the practical work to build authority that compounds across engines