Building in public means sharing the real stuff so here it is.

For the first several months of my SaaS organic SEO felt like a tax I was paying on my time without getting much back. Content was going out, traffic was trickling in, revenue from organic was negligible. I kept hearing that SEO was a long game and I kept telling myself that patience was the issue.

Patience wasn't the issue. The system was broken in three specific places and I just hadn't found them yet.

The first broken place was content format. I was writing for Google in the way guides from five years ago told you to. Long posts, keyword frequency, structure designed for crawlers. That content ranked for things occasionally and converted rarely because it wasn't actually a great reading experience. Nobody stays on a page that feels like it was written by someone following a checklist. The format I switched to through this SEO tool was simpler and better. One question per article, direct answer first, plain clear language throughout. Readers stay because they get value immediately. And this format is exactly what AI tools like ChatGPT and Perplexity look for when generating answers. My content started getting cited in AI responses for relevant queries and that traffic converts better than almost anything else because the person already has context before they land on the page.

The second broken place was indexing. I was naive about this for longer than I want to admit. Publishing content does not mean Google has seen it. For a site without massive authority Google crawls when it wants to and that can mean weeks between visits. This indexing tool automated the process of telling Google and Bing about every new page the moment it went live. Submissions go directly to Google's Indexing API and Bing's IndexNow automatically. The backlog of unindexed content cleared, new content started ranking fast, and the compound effect of that over a few months of consistent publishing was significant.

The third broken place was measurement. I was tracking traffic and making content decisions based on what got visits. That is a reasonable starting point but it is not the right metric to optimize for long term. This analytics tool connected my content performance directly to my Stripe data so I could see which pages were driving paid conversions not just sessions. That visibility changed everything. The content that looked good in analytics and the content that actually made money were different sets of pages and I had been investing effort in the wrong one.

Three broken places, all fixed. Organic is now the channel I'm most confident in.

I built a micro SaaS marketplace for AI agent skills. Think app store but for SKILL.md files that make Claude Code, Cursor, and Codex CLI better at specific tasks. I'm a non-technical solo founder. Built the whole thing with Lovable and Claude.

This post isn't about the product. It's about the distribution strategy that got it to 15K active monthly users with zero ad spend. Most of this is AEO stuff that I think this sub will find useful.

The numbers first

15,000+ active users in the last 30 days. 219% growth over the previous period. 300K+ Google search impressions per month. 4,000+ organic clicks per month. 878+ page-1 Google rankings, up from about 15 at launch. Cited as a source by ChatGPT, Gemini, Claude, Perplexity, Doubao, and Kagi. 350+ AI-referred sessions per month from 9 different AI engines. Total marketing spend: $0.

The AEO strategy that drives most of my growth now

This is the part I want to focus on because I don't see many people talking about it with real numbers.

AI Overviews are eating Google clicks. I have 121 queries where I rank positions 1 through 3 on Google with zero clicks. The AI answers the question before anyone scrolls down. That insight changed my entire strategy. I stopped chasing rankings and started optimizing to become the source AI engines cite.

Here's what I did specifically:

Every article has a Quick Answer block at the top. 40 to 60 words that directly answer the main question. This is what AI Overviews and LLMs extract. If you bury the answer halfway down your page, the AI will pull from someone who doesn't.

All H2 headings are phrased as questions. Not "Claude Code Skill Locations" but "Where Does Claude Code Store Skills?" AI engines prefer extracting from question-format sections. I tested this across 96 articles and the ones with question headings get cited significantly more.

Every page has FAQ schema. Google's AI picks up our Q&As directly. This is one of the highest leverage things I did and it took maybe 2 hours total with Claude generating the schema.

I built an entity anchor page (/about) with Organization, Person, and AboutPage schema. This tells AI engines who we are and establishes the entity relationship. Without this, you're just another anonymous source.

I created an llms.txt file that explicitly tells LLM crawlers what the site is and where to find key content. Also made sure robots.txt allows all AI crawlers. Most people block them. I want them to read everything.

The result: when someone asks ChatGPT "where can I find SKILL.md skills" or asks Perplexity "what is the best skill marketplace for AI agents," they get pointed to us. That didn't happen by accident. Claude helped me engineer every piece of it.

The content engine behind it

I don't ask Claude to "write me a blog post about X." That produces generic stuff that Google doesn't rank and AI engines don't cite.

Instead I feed Claude my Google Search Console exports (queries, impressions, click-through rates, average positions) and ask it to find keyword gaps. Claude identifies queries where I have high impressions but zero clicks, finds topics where competitors have content but I don't, and spots cannibalization where multiple pages compete for the same query.

Then we write articles together targeting those specific gaps. Every article has the Quick Answer block at the top, question-based H2s, comparison tables where relevant, and internal links to related articles.

96 articles later, we went from 5 clicks per week to 1,000+ clicks per week. 878+ page-1 rankings. All organic.

The technical SEO layer most people skip

I built the app with Lovable (React SPA). Out of the box it was an SEO disaster. Google's crawler saw an empty div and a JavaScript bundle. The JS was 460KB. The logo was a 179KB PNG rendered at 112 pixels. LCP was 4+ seconds on mobile.

Claude diagnosed all of this. It wrote the SSR layer, found the bundle bloat, identified the oversized images, and rewrote the performance bottlenecks. Desktop LCP went from 2.5 seconds to 0.9 seconds. PageSpeed performance score went from 70 to 97. Logo went from 179KB to 7KB.

If you're building with Lovable, Bolt, or any React framework and expecting organic traffic, you need to fix this layer. Google will not reliably index a client-side rendered SPA.

The structured data architecture

Claude built the entire structured data layer:

Homepage: Organization, WebSite with SearchAction, FAQPage with 15 Q&As. Individual skill pages: SoftwareApplication with pricing, BreadcrumbList, conditional FAQPage. Article pages: Article, FAQPage, HowTo, BreadcrumbList, Organization. About page: Organization, AboutPage, Person schema for entity anchoring.

PageSpeed Insights shows "Structured data is valid" on every page with a 100 SEO score. I didn't know any of this before Claude explained it. Now every page is machine-readable for both Google and AI engines.

The weekly growth loop

Every Monday I do the same thing:

1. Export Google Search Console data (queries, pages, clicks, impressions, positions)
2. Upload the CSVs to Claude and ask: find keyword gaps, cannibalization, and CTR problems
3. Claude identifies 3 to 5 specific opportunities with exact numbers
4. I write 2 to 3 articles targeting those gaps, rewrite titles on underperforming pages, and add internal links from high-authority pages to weak ones
5. Ping IndexNow to get new pages crawled within 24 hours
6. Manually request indexing on GSC for the new articles

Takes about 2 to 3 hours per week. Highest ROI activity in the business.

What I'd tell someone starting AEO today

Set up Google Search Console before you launch. Even with zero traffic it starts collecting data on what queries your site appears for. That data becomes your content strategy within 2 to 3 weeks.

Write articles targeting specific questions, not broad topics. "How to install skills in Claude Code" beats "The Ultimate Guide to AI Agent Skills" every time.

Set up structured data from day one. Organization schema on your homepage, Product schema on your product pages, FAQ schema on your content pages. This is what AI engines read to decide whether to cite you.

Create an llms.txt file. It's like robots.txt but for AI crawlers. Takes 10 minutes and it tells every LLM exactly what your site offers.

Don't fight AI Overviews. Become the source they pull from.

Happy to answer questions about any of this. The site is agensi.io if you want to see how this looks in practice. If you want to support a bootstrapped one-person startup, making a free account genuinely helps more than you'd think 😄

I am the founder of IndexerHub which helps sites get indexed on Google, Bing and AI search engines. This post is not a pitch for it though.

I want to share what actually happened when I tried to grow a brand new domain from scratch because I made enough mistakes along the way that the lessons feel worth writing down.

The biggest mindset shift for me was realising that writing for Google and writing for AI search are genuinely two different things. I had been treating them the same and wondering why my content was not showing up in ChatGPT or Perplexity answers even when it was ranking okay on Google.

Google cares about authority, backlinks, technical signals, keyword relevance. AI tools care about one thing. Does this content directly answer the question someone just asked. That is it. They are scanning for content that leads with the answer, uses plain language, and does not make the reader hunt through paragraphs to find what they came for. Once I understood that I rewrote everything. Every article became one question with the answer in the first paragraph and everything else supporting it. Within a few weeks content started showing up in AI-generated responses and that traffic converted better than anything else I was getting.

The other thing that tripped me up early was indexing. I kept publishing and nothing was moving and I eventually realised half my content was not even in Google's index yet. For a new domain Google crawls when it feels like it and that can mean weeks of your content just sitting there invisible. Once I started actively submitting every page to Google's Indexing API and Bing's IndexNow the moment I published, things started moving much faster.

From mid-March to the first week of May traffic grew from basically zero to 560 visitors a week and revenue crossed $1,195. The growth compounded once the content format was right and the indexing was fast. Those two things together made the difference.

Tools I used: 

EarlySEO for content, it handles keyword research and structures everything for AI citations. 

Faurya for analytics, completely free with no card needed, connects to Stripe and shows you revenue per visitor not just sessions.

Happy to answer questions on any of this.

SEO used to be mostly about ranking pages on Google.

Now the game is changing:

• SEO → Rank on search engines
• AEO → Become the direct answer
• GEO → Get cited by AI systems like ChatGPT & Gemini
• AIO → Use AI to optimize content and marketing automatically

Feels like modern SEO is no longer just about keywords and backlinks.
Visibility now depends on whether AI systems can understand, trust, and use your content.

Curious how many people here are already optimizing for AI visibility instead of just SERP rankings?

Source: What Is SEO vs GEO vs AEO Explained

Tool: Canva