Practical, source-backed guides on answer engine optimization — the same method behind the audit, written up so you can act on it. Naturally, we practise what we publish: every guide ships structured for the machines it's about.
ChatGPT appears to be building retrieval infrastructure beyond Google and Bing. What proprietary indexes, vertical feeds and caching change for AI visibility.
Read the full guide →AI search is rebuilding the organic funnel around passages and citations — a field guide to the GEO/AEO shift, from Reddit's citation collapse to how AI actually picks its sources.
Read the full guide →A field checklist for the markup that makes a page legible to answer engines — and the mistakes that quietly make it invisible.
How to turn your assertions, attributions and evidence into records a model can quote precisely — instead of paraphrasing you wrong.
Your best research is trapped in documents crawlers skip. A playbook for surfacing buried reports and whitepapers for AI.
How to track how often — and how accurately — you're named across ChatGPT, Perplexity, Gemini and Claude, and turn it into a baseline.
Staying visible to the engines that attribute and link, while setting your own terms with the crawlers that don't. Where the two questions diverge.
No cadence promises, no noise — just a note when a new guide is published.
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