Automate AEO: 6 Letaido workflows

AI assistants have become a discovery channel in their own right. Where people once typed queries into Google, they now ask ChatGPT, Claude, Gemini, Perplexity, or Copilot—and get back an answer that names a few brands, cites a few sources, and moves on. If you are named, you win visibility. If you are not, you may never know the conversation happened. That is what Answer Engine Optimization (AEO), also known as Generative Engine Optimization (GEO), is for—and it now sits firmly within SEO and marketing.

The problem: AEO is not a one-off project. Answers shift weekly or daily, vary by model, country, and phrasing, and the same question can produce different brand lists. An unknown competitor may suddenly get cited while incorrect pricing about your brand circulates in a Reddit thread—with no alert. Regular checks are necessary, but they do not have to be manual. That is where Letaido comes in: Ahrefs' agentic marketing platform with direct access to the full dataset.

What Letaido delivers for AEO teams

Letaido is not a chatbot but an autonomous marketing agent with unrestricted access to Ahrefs endpoints, native connectors to Slack, HubSpot, WordPress, Notion, and more, plus a library of prebuilt marketing skills. Under the hood: Postgres, Flask UIs, an OpenRouter proxy with 300+ models, and scheduled jobs—so workflows keep running when nobody is at the keyboard. For AEO, that means Brand Radar, Keywords Explorer, and Web Analytics can be bundled into recurring monitoring and reporting processes. Each of the six workflows starts with a starter prompt in plain language that teams paste into a workspace and refine for their brand.

1. Find prompts worth winning

Classic keyword research targets Google searches. AEO targets questions to assistants—and prompt volume cannot be measured directly. Letaido uses Brand Radar to surface real prompts in a niche and Keywords Explorer to estimate underlying search demand as a proxy. Because fewer people use each assistant than Google, the tool scales demand by user base: if ChatGPT has roughly 30% of Google's users, volume is weighted by 0.3. The output is a prioritized prompt map by demand, commercial intent, and thematic clusters—instead of guesswork.

2. Share of voice across every relevant AI platform

"Are we showing up in ChatGPT?" is not enough. Visibility differs between ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, and Copilot. Letaido measures, for defined priority prompts and competitors, how often answers mention or recommend your brand—by platform and by prompt. The result is a scoreboard: share of voice per platform, prompts where you are absent, and competitors taking your share. Weekly logs make trends visible.

3. Identify sources that cite competitors instead of you

When an assistant recommends a competitor, it trusts specific sources—review sites, listicles, documentation, forums. Brand Radar lists cited domains and pages, weighted by frequency and authority, and flags whether your brand already appears. That yields an outreach list: get listed, request corrections, place guest contributions. Much AEO work happens off-site because AI answers mainly reflect external mentions.

4. Sentiment tracking for brand perception

Assistants decide not only whether to mention you but how to frame you—positively, neutrally, or negatively, depending on platform and prompt. Letaido pulls full answer text from Brand Radar, scores sentiment, and logs changes over time. Teams can see whether a perception problem is emerging and which prompts are most affected. For operational follow-up, the article points to Despina's guide on auditing brand mentions.

5. Catch hallucinations about your brand

AI systems invent features, prices, or integrations with convincing confidence. Letaido compares every factual claim in AI answers against your ground truth—pricing pages, feature lists, documentation—and flags false or outdated statements along with the likely source. Teams then know which page to fix, which source to contact, or which signal to strengthen.

6. Monthly AI visibility reports for stakeholders

AEO programs eventually need to translate into metrics non-specialists understand. Letaido can bundle monthly Brand Radar trends, Search Console performance, and AI referral traffic from Web Analytics into a report with KPI tiles, month-over-month comparisons, prompts gained and lost, and a plain-language summary—automatically in Slack or via link.

From single workflows to continuous monitoring

The central lever is scheduling: prompt discovery, share-of-voice tracking, sentiment checks, and hallucination finders run on a recurring basis and alert only on deviations. Ahrefs customers can trial Letaido for one month, paste a starter prompt into a workspace, and launch the first workflow the same day. Teams serious about AEO do not need permanent manual monitoring—they need agents watching in the background when competitors win prompts, prices appear wrong, or sentiment slips.

• Estimate prompt demand via Brand Radar and Keywords Explorer instead of guessing.
• Measure share of voice by platform rather than checking one AI surface only.
• Reverse-engineer cited sources and build targeted off-site influence.
• Log sentiment and factual errors automatically and fix them with priority.