Writing

In 2026 the SEO industry has three new terms trending at once — AEO, LLMO, GEO — and even Neil Patel, Profound, and emarketer disagree on the definitions. This article proposes the most pragmatic May 2026 ordering: AEO ⊂ GEO ⊃ LLMO. We compare AEO (Google AI Overview/Featured Snippet/Perplexity/ChatGPT Search) vs LLMO (plain chat use of ChatGPT/Claude/Gemini) across eight axes: target platform, main scenario, goal, relationship to SEO, unique techniques, primary metric, time to effect, and industries that benefit. Then we cover the seven shared techniques (E-E-A-T / structured data / first-party data / inverted pyramid / AI-bot allow / Q&A format / llms.txt), the four AEO-only techniques (SERP rich results / Featured Snippet sniping / PAA capture / search-intent matching), the four LLMO-only techniques (training corpus exposure / brand consistency / third-party mentions / prompt recall testing), an industry priority matrix, and three pitfalls (terminology debates / downplaying SEO / vague measurement).

2025 zero-click search hit 69% (up from 56%) and AI Overview now appears on about 55% of Google searches. In an era where "rank #1 no longer guarantees clicks," the new required layer is AEO (Answer Engine Optimization). This article covers the definition (optimization so that search and AI display your content as "the answer itself" or cite it as a source), how AEO differs from SEO, the citation logic of the four Answer Engines (Google AI Overview / ChatGPT Search / Perplexity / Bing Copilot), seven techniques that work (inverted pyramid / Q&A format / FAQ-HowTo Schema / lists & tables / first-party data / author signals / AI-bot allow), new metrics (Snippet appearance / AI-bot hits / branded search / CVR), and three pitfalls (ignoring SEO / blocking AI bots / overdoing it). AEO is not a replacement for SEO but a layer above — implement both in the right order.

The May 2026 Google core update clearly demoted "thin, mass-produced AI-only articles," while hybrid writing — AI drafts, expert edits, first-party data added (as in the Wayfair case) — drove a 24% organic traffic lift. This article covers the three-model split (Claude for long-form voice, ChatGPT for research and tools, Gemini for Workspace and current data), prompts that actually work (persona + sample + constraints, with sample-pasting being the most powerful), the four-step Wayfair-style hybrid workflow, five common "tells" that reveal AI writing and how to kill them, a six-step hands-on workflow, and three pitfalls to avoid (letting AI pick the topic, ignoring hallucinations, failing to kill the good-student tone). The framing has shifted from "AI to take it easy" to "AI as a foundation that raises quality."

Google AI Overviews rewrote the search rules. Seer's 2026 study (53 brands, 5.47M queries) found organic CTR on AIO-present queries dropping 61%, the top-10 citation rate falling from 76% to 38%, yet cited brands earning 120% more clicks — the shift from "rank #1 to win" to "be the page that gets cited" is largely complete. This article maps SEO vs AEO vs LLMO vs GEO in 30 seconds, explains AI Overviews trigger conditions, lays out the seven citation factors (passage completeness, original data, E-E-A-T, structured data, entity density, multimodal content, technical accessibility), separates SEO that still works from SEO that no longer does, defines the new KPI stack (citation × CVR × share of voice), and closes with three risks — hallucinations, citation concentration, channel dependence — all backed by 2026 data.

If robots.txt is a file that tells search engines what they can and cannot crawl, llms.txt is a file that tells AI about your site's content and structure. It helps LLM crawlers (GPTBot, ClaudeBot, etc.) understand your site, increasing the chances of being cited in AI-powered search results. This article covers everything from the llms.txt format specification and what information to include, to whether you should use a static file or dynamic generation, and how to implement it in major frameworks.

With ChatGPT users surpassing 2.8 billion and Google's zero-click rate hitting 83% when AI Overviews appear, simply ranking on search results is no longer enough. LLMO (Large Language Model Optimization) is the new approach to getting your content cited in AI-generated answers. From how it differs from SEO to actionable techniques you can start today.