SEO and GEO/AEO: Getting Recommended by Google AND by AI

Summary

For twenty years, getting found meant ranking on Google. Now half your future customers will discover you through an AI assistant that reads the web, picks a few sources, and recommends them. You have to win both channels, and the good news is they reward the same thing: clear, well-structured, trustworthy content that a machine can read and cite. This lesson covers the SEO fundamentals and the new GEO/AEO layer - llms.txt, structured data, citability - plus two tactics that punch above their weight: the favicon trick and the system of websites.

What you will learn

You will learn the SEO fundamentals that still matter - titles, meta descriptions, sitemaps and Search Console - the SERP details like favicons that lift click-through, how GEO/AEO and llms.txt make your content citable by AI assistants, the role of clean markdown and structured data, and the system-of-websites strategy of running many focused sites instead of one sprawling one.

Prerequisites

A live, indexed site and the Search Console basics from Course 3, since discovery builds on being indexable in the first place. You should also remember the agentic surface concepts from Course 4 - llms.txt and clean machine-readable content are where SEO and agentic design meet.

The problem

Two failure modes are common. The first is building something good that nobody can find because the basics are missing - no descriptive titles, no sitemap, never verified in Search Console. The second is newer and more dangerous: a site optimised only for Google that is invisible to AI assistants, so when someone asks Claude or ChatGPT for a recommendation in your space, you are never mentioned. Winning one channel and ignoring the other leaves half your discovery on the table.

SEO fundamentals that still matter

The foundation has not changed: help both humans and crawlers understand each page, and earn trust. Get these right before chasing anything clever.

• Title tag: unique per page, around 50 to 60 characters, leading with the words people actually search. This is your headline in the results and your single biggest lever on click-through.
• Meta description: roughly 140 to 158 characters, written to earn the click, not to stuff keywords. It is your advert under the title.
• Clean structure: one H1, logical headings, fast pages, mobile-friendly, descriptive URLs. Crawlers reward clarity.
• Sitemap and Search Console: submit an XML sitemap and verify the site in Google Search Console so you can see impressions, clicks and which queries you rank for.
• Trust: real content, no thin pages, internal links, and inbound links from sites that matter.

The favicon-in-SERP trick

Here is a small, underused edge. On mobile and increasingly on desktop, Google shows your site's favicon next to your search result. A crisp, distinctive, recognisable favicon makes your listing stand out in a wall of text and measurably lifts click-through, which in turn signals relevance and can help your ranking. Most people ship a default or blurry icon and leave this on the table. Make a clean favicon at the sizes Google expects, reference it correctly in your head tags, and confirm it actually shows. It is ten minutes of work for a permanent advantage on every result you ever rank for.

GEO/AEO: making AI recommend you

GEO (Generative Engine Optimisation) and AEO (Answer Engine Optimisation) are about being the source an AI assistant chooses to read and cite. The mechanics are different from Google but the spirit is the same: be readable, be structured, be trustworthy, be unambiguous. AI assistants favour content that directly answers the question, states facts plainly, and is easy to parse. The single most useful new artefact is llms.txt - a plain-markdown map of your site that points assistants at your best, cleanest content, the same way robots.txt and sitemap.xml guide search crawlers.

# Your Company

> One clear sentence on what you do and who it is for.

## Core pages
- [Pricing](https://example.com/pricing.md): plans and what each includes
- [How it works](https://example.com/how-it-works.md): the product in plain steps

## Guides
- [Getting started](https://example.com/guides/start.md): first 10 minutes
- [API reference](https://example.com/api.md): endpoints and examples

## About
- [Founder](https://example.com/about.md): who is behind this and why

• Serve a clean .md version of each important page so assistants get content without wading through your layout.
• Add structured data (JSON-LD) for articles, products, FAQs and your organisation, so both Google and AI parse facts unambiguously.
• Write answer-first: lead with the direct answer, then the detail. Assistants quote the clear sentence, not the buried one.
• State concrete facts - prices, specs, dates - plainly, because that is what gets cited.

The system-of-websites strategy

Here is a strategy the founder of this school uses deliberately: instead of cramming everything into one broad site, run a system of focused niche sites. Thirteen tightly themed sites, each owning one specific topic or audience, beat one site trying to rank for everything. Each site can be the clearest, most authoritative answer in its narrow niche, which is exactly what both Google and AI assistants reward. The sites cross-link where it genuinely helps the reader, so authority compounds across the system instead of every property starting from zero. With agents, spinning up and maintaining a new focused site is cheap, which makes this strategy far more practical than it was when every site meant a team.

• One site, one clear niche: easier to become the definitive answer than a generalist site ever can.
• Specificity wins citations: AI assistants prefer the focused source that obviously matches the question.
• Cross-link with intent: connect sites where it helps the reader, so authority and discovery compound.
• Agents make it cheap: scaffolding and maintaining many small sites is now an afternoon, not a hire.

Typical mistakes

The recurring ones: duplicate or missing title tags so every page looks the same in results; keyword-stuffed descriptions that read like spam and kill click-through; never verifying in Search Console so you are flying blind; shipping no llms.txt and no clean markdown, so AI assistants skip you; and burying your answer three paragraphs down where no assistant will ever quote it. Lead with the answer, keep pages clean, and feed both crawlers and assistants.

Business ROI

Discovery is compounding and nearly free once it works. A page that ranks or gets cited brings visitors every day with no ongoing cost, which is the cheapest acquisition channel there is. The shift to AI discovery is the opportunity: most competitors are still optimising only for Google, so the builders who make their content citable now will own the AI-recommendation channel before it gets crowded. Getting recommended by an assistant that millions of people trust is worth more than a page-two Google ranking, and right now it is wide open.

Checklist

Confirm these for any site you want discovered through both channels.

• Every page has a unique, search-led title and a click-worthy meta description.
• A sitemap is submitted and the site is verified in Search Console.
• A crisp favicon shows next to your result, and structured data is in place.
• An llms.txt maps your best content and clean .md versions are served.
• Your most important answers lead with the answer, not the backstory.

Resources

Google Search Central and the Search Console documentation are the timeless SEO references; the llms.txt proposal and schema.org are the GEO/AEO ones. The Going Live lesson in Course 3 covers the Search Console setup if yours is not done. Watch your Search Console impressions and click-through over weeks - it is the only feedback loop that tells you what is actually working.

Your task

Pick one real page and rewrite its title and meta description to lead with what people search and earn the click. Ship a clean favicon and confirm it appears in a search result. Then write a first llms.txt for the site mapping your best pages. You now feed both channels - check Search Console in two weeks to see the effect.

Next lesson

Being discoverable by AI leads straight to the next idea: designing products that AI itself loves to use, where the API is the product and the UI is almost beside the point.