Field notes from the AI search era

Why we publish this blog

Search is splitting into two systems. The first is the one everyone knows: Google's ranked list of links, governed by crawlability, relevance, backlinks, and page experience. The second is newer and moves faster — generative engines like ChatGPT, Perplexity, Gemini, and Google AI Overviews that read the web, synthesise an answer, and cite a small handful of sources. Ranking in the first system no longer guarantees you appear in the second, and most brands have no visibility into whether they are being cited at all.

This blog is where we write down what we learn running Generative Engine Optimization engagements for B2B SaaS, fintech, healthtech, and DTC brands. Every article is written to be useful on its own: no gated PDFs, no vague "it depends" advice. If we recommend a schema pattern, we show the markup. If we recommend an audit, we give you the prompts to run and the thresholds to judge the results against.

What you'll find here

• Foundations — plain-language explanations of what GEO is, how generative engines choose sources, and how that differs from classical SEO ranking factors.
• Implementation guides — structured data, entity configuration, llms.txt, content formatting for answer extraction, and the technical hygiene that determines whether a crawler can use your page at all.
• Measurement — how to establish a citation baseline, which prompts to track, how to read month-over-month movement, and how to separate real gains from model noise.
• Strategy — where to invest first when budget is limited, and how GEO and SEO work compounds together rather than competing.

New articles are added as our own testing produces results worth sharing. If there's a question you want answered, tell us and we'll write it up.