GEO, AEO & SEO, demystified
Comprehensive, no-fluff guides on getting your site discovered, quoted and cited by ChatGPT, Gemini, Claude, Perplexity and Google's AI Overviews.
Google AI Overviews SEO: The Citation Architecture Template
Master Google AI Overviews SEO with our complete page layout template, entity extraction schema, and modular content architecture to win AI citations.
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ChatGPT 2026 Ranking: Expert Strategies for Generative AI Visibility
Master actionable strategies to rank and earn citations in ChatGPT in 2026. Optimize for OpenAI search retrieval, entity salience, RAG, and AEO principles.
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FAQ Schema & AEO: AI Overviews Edge with Structured Data (2026)
Master FAQ schema for AEO in 2026. Learn how structured data feeds Google AI Overviews, boosts Gemini RAG citations, and secures brand attribution.
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Optimizing SaaS Content for GEO: Docs, Changelogs, & Comparison Pages for AI Overviews (2026)
Unlock advanced GEO strategies for SaaS technical documentation, changelogs, and comparison pages to boost visibility in AI Overviews and generative search results.
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Robots.txt for AI: Allow, Block, or Selective? Optimizing for 2026 AEO
Master robots.txt directives for AI: allow, block, or selectively control AI model access to your content for optimal 2026 AEO and SEO strategy.
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Perplexity Citations: An Engineering Teardown & AEO Optimization Guide (2026)
Explore Perplexity AI's advanced citation engine, its impact on SEO and AEO in 2026, and strategies to optimize content for AI visibility and trust.
Read articleWhat Is Generative Engine Optimization (GEO)? The 2026 Field Guide
GEO is the practice of making your content easy for ChatGPT, Gemini, Claude and Perplexity to retrieve, quote and cite. Here is how it works and how to start.
Read articleAnswer Engine Optimization (AEO): The Complete Guide for 2026
AEO is how you win the single answer ChatGPT, Alexa, Siri and Google's AI Overviews read aloud. Learn the schema, structure and content patterns that work.
Read articleSEO in the Age of AI Search: What Still Works, What Is Dead
Classic SEO is not dead, but the rules have shifted. Here is what still drives rankings in 2026 and what to stop wasting time on.
Read articlellms.txt: The Missing File Your Site Needs for AI Search
llms.txt is the robots.txt of the LLM era — a plain-text map that tells AI engines what your site is about and which pages matter most.
Read articleHow to Get Cited by ChatGPT, Perplexity and Gemini
Citations from AI assistants are the new backlinks. Here is the practical playbook to earn them — content patterns, schema, and trust signals that work.
Read articleFour tracks, one archive
Different humans inside the same company care about different things. Pick the track that matches the seat you're sitting in today.
Generative Engine Optimization
llms.txt, AI-crawler permissions, schema combos that win citations in ChatGPT and Perplexity, answer-first content patterns.
Answer Engine Optimization
Single-answer surfaces — AI Overviews, Siri, Alexa, voice mode. FAQ and Speakable schema, answer-first paragraphs.
Classic SEO in 2026
What still moves: core web vitals, internal linking, original research. What's dying: keyword density, link exchanges, AI filler.
Budgets & measurement
Allocating between SEO and GEO, measuring citations without a dashboard, briefing a CMO, planning twelve months out.
How to read this blog
Why this blog exists
Most writing on AI search is either hot-takes that don't survive contact with a real site, or vendor white papers that bury a useful idea inside a twenty-page sales pitch. We started this blog because audits kept surfacing the same fixable mistakes — and nobody was writing them down in a form a busy in-house team could act on in an afternoon. Every post follows the same structure: the symptom, why it happens, the smallest change that fixes it, and the measurement that tells you it worked.
Rules we hold to
No AI-generated filler
We use AI for outlines and fact-checks. We don't publish posts a model wrote and a human skimmed.
No affiliate links in the argument
If we recommend a tool, it's because we've used it in production. Disclosures live at the bottom.
Updates over reposts
When ChatGPT changes a signal, we update the original post with a changelog — not republish to game freshness.
One claim, one source
Every assertion about engine behavior links to a source. If we can't, we label it 'in our experience.'
8–12 minutes per post
We don't pad. We also don't compress so far you lose the "why." Reading time is honest — measured from word count.
RSS & updates
Subscribe to our RSS feed for new articles. When a newsletter launches it'll be a weekly digest, not a separate content stream.
Read articles as practical guidance with a scope
The blog covers AI-search visibility, crawl access, content structure and measurement. Identify the language, publication or revision date, and audience of an article before applying its recommendations. A useful article explains what to do, how to verify it and where the method may not apply; length alone is not evidence of quality.
Check the evidence behind a chart or claim
Distinguish a worked example from a measured result. A chart should name its units, dates and data source; an experiment should identify its prompt set and conditions. Follow source links to see whether they actually support the nearby statement. An automatically updated date does not by itself establish factual freshness.
Keep a record of what changed
Save the original URL, input, date and evidence before editing. Verify the deployed page or file, document the changes and repeat the same checks. Separate technical validity, correct answer representation and qualified visits; none should be used as a substitute for the others.
Evidence and next actions
| Check | Evidence to retain | Action |
|---|---|---|
| Access | Public status and useful response body | Fix barriers before rewriting |
| Accuracy | Visible facts and supporting primary sources | Correct unsupported statements |
| Markup | Valid syntax that matches the page | Remove invented reviews and properties |
| Outcome | Comparable responses and referral activity | Report observations without guarantees |
Implementation checklist
- Use the tool or guide matching the problem.
- Verify important facts against current primary documentation.
- Keep private data out of published files and support requests.
- Check changes on the real domain.
- Retain comparable before-and-after evidence.
A repeatable workflow
- 1Establish a baseline
Save the page URL, date, language, target market and exact questions before editing. Record what the page actually says and what each tested answer cites; a mention without a source link is not a citation.
- 2Make one coherent change
Resolve the clearest failure first, then check the published page rather than only an editor preview. Keep an implementation log so unrelated redesigns, campaigns or product changes are not mistaken for the effect of this work.
- 3Repeat and compare
Repeat the same questions and technical checks after deployment. Keep engines and measurement conditions consistent, report sample size, and inspect answer accuracy alongside citations. A single response is not a stable ranking.
More questions answered
- Does this guarantee an AI citation?
- No. A crawlable, accurate page can still be omitted. Retrieval, source selection and generated answers vary between products and requests; these checks improve the evidence available, not guarantee placement.
- How do I tell whether an improvement worked?
- Compare like-for-like checks and retain the underlying evidence. Track correct brand mentions, source-linked citations and qualified referral visits separately. Do not call a technical score a traffic forecast or attribute every change to one edit.