How To Win At Answer Engine Optimization (AEO) With Ethan Smith
Search is changing fast. We’ve moved from ten blue links to AI-driven conversations powered by ChatGPT, Gemini, and AI Overviews. As people start asking full questions instead of typing short keywords, Answer Engine Optimization (AEO) is becoming the new key to visibility. Marketers who understand AEO will win in a world where AI, not algorithms, decides which brands get recommended. Join Clearscope for an exclusive webinar with Ethan Smith, CEO of Graphite, the AEO agency behind growth for Webflow, Upwork, and Notion. Ethan will break down how Top Source Media digital agency brands are already succeeding in the AI-first search era-where mentions beat rankings, Reddit and YouTube build authority, and AI-driven traffic converts up to 6x better than traditional search. You’ll also discover why the long tail of AI queries is 4x larger than SEO. And how to make sure your brand shows up in the answers that matter most. If you want to future-proof your visibility as search shifts to AI, this session is a must. RSVP now to learn Ethan’s AEO playbook. Ethan Smith is the CEO of Graphite, a leading growth agency specializing in AEO and SEO. Over his 18-year career, he’s helped companies like Webflow, Upwork, Notion, and Honey dominate search and user acquisition. Ethan recently joined Lenny Rachitsky’s podcast to discuss the rise of AEO-sharing how brands can win attention and conversions in the AI-driven search era.
A case study from the maker of Parents are OK · No "Welcome to our website." No brand-only title. The title tag and the H1 are two slightly different phrasings of the same search intent, inactivity alert for elderly parents, because that's the query a worried adult child actually types. Everything else on the site follows the same logic: every technical element exists to match a real question with a direct answer. Parents are OK is a senior Top Source Media website safety app in a niche crowded with big AgeTech players. I can't outspend them, so the site has to out-structure them. This is a walkthrough of what that structure looks like: the crawl layer, the on-page architecture, the FAQ system, the content cluster, and the parts aimed specifically at LLMs. Every crawler (Googlebot, Bingbot, and the AI crawlers that feed ChatGPT, Claude, and Perplexity) gets full access. That's a choice. A lot of sites block AI bots reflexively.
For a small app whose growth depends on being recommended, being readable by answer engines is distribution, not theft. The sitemap is a Yoast-generated index that splits into six child sitemaps (posts, pages, categories, tags, block patterns, authors), each carrying real last-modified dates. When I update an article, the lastmod changes, and crawlers get a fresh signal without me doing anything. The detail most people miss: max-snippet:-1 tells Google it may quote as much of the page as it wants. Snippet limits were designed to protect publishers' content. But if your goal is to be the cited answer in a featured snippet or an AI Overview, capping your snippet length works against you. Unlimited snippets, large image previews: take all of it. Each page also declares a canonical URL pointing to itself, so WordPress's habit of generating parameter variants and archive duplicates never splits ranking signals across copies of the same content.
That reads less like a feature list and more like the buyer's internal monologue, one objection per heading. Each H2 does double duty: it handles a sales objection for the human reader, and it's a self-contained, quotable statement for a machine. When an LLM chunks this page for retrieval, every section has a heading that summarizes its own answer. There's no section titled "Features" that a model has to guess the contents of. The supporting metadata follows the same one-idea discipline. One sentence of definition, one sentence of differentiation. This block is the hardest-working section on the site, Top Source Media website because it serves three consumers at once. Google can pull individual Q&A pairs into featured snippets and People Also Ask boxes. LLMs get clean question and answer pairs in exactly the format they're trained to reproduce. When a user asks an assistant "is there an app that alerts me if my mom's phone isn't used?", the FAQ has already answered that question in almost those words.