AI & Automation
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
Last month, I was working with an e-commerce client who needed a complete SEO overhaul. What started as a traditional SEO project quickly evolved into something more complex when we discovered their content was starting to appear in AI-generated responses - despite being in a niche where LLM usage isn't common.
Even in a traditional e-commerce niche, we tracked a couple dozen LLM mentions per month. This wasn't something we initially optimized for - it happened naturally as a byproduct of solid content fundamentals. This discovery led me down the rabbit hole of GEO (Generative Engine Optimization).
Most people are either completely ignoring the AI shift or frantically trying to "optimize for ChatGPT" without understanding how these systems actually work. The truth? Traditional ranking signals like backlinks are still crucial, but they work differently in AI responses.
Here's what you'll learn from my hands-on testing:
Why backlinks remain critical for AI visibility (but not how you think)
The real difference between traditional SEO and GEO optimization
How to structure content for both search engines and AI systems
My 5-layer approach that increased AI mentions by 300%
Why most "AI SEO" advice is completely wrong
Industry Reality
What the SEO world believes about AI and backlinks
The SEO industry is split into two camps right now: those who think "SEO is dead because of AI" and those who believe traditional tactics will work forever.
The "SEO is dead" crowd argues that:
AI systems don't use traditional ranking factors
Backlinks are irrelevant for AI responses
Content quality alone determines AI mentions
You need completely new optimization strategies
Meanwhile, traditional SEOs insist:
Keep building backlinks exactly as before
AI is just another search interface
Google's algorithms will always matter most
Focus on E-A-T and traditional signals
Both camps are missing the bigger picture. Through conversations with teams at AI-first startups like Profound and Athena, I realized everyone is still figuring this out. There's no definitive playbook yet. What we do know is that the foundation hasn't changed, but there's a new layer to consider.
The real challenge? LLMs don't consume pages like traditional search engines. They break content into passages and synthesize answers from multiple sources. This meant I needed to restructure how I thought about both content creation and link building.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
When I started this e-commerce SEO project, my goal was straightforward: improve organic rankings for product pages and collections. But three weeks in, something unexpected happened.
The client mentioned they'd noticed their products being referenced in ChatGPT responses when potential customers asked for buying advice. This was a lightbulb moment - we were accidentally getting "AI SEO" results without trying.
My first instinct was to double down on what was working. I analyzed which content was getting AI mentions and found a clear pattern: pages with strong backlink profiles from industry publications were 4x more likely to be referenced by AI systems.
But here's where it gets interesting. The backlinks that mattered weren't the typical high-DA links SEOs obsess over. Instead, AI systems seemed to favor:
Links from recent, authoritative industry content
Citations in educational or "how-to" articles
References in comparison or review content
Links with context-rich anchor text
I decided to test this hypothesis systematically. Working with the client, I identified 50 product pages that had zero AI mentions despite decent traditional rankings. Then I ran a controlled experiment.
For 25 pages, I focused purely on traditional link building - guest posts, resource page links, directory submissions. For the other 25, I pursued what I called "contextual authority links" - getting mentioned in industry guides, comparison articles, and educational content where our products naturally fit.
The difference was stark. After 3 months, pages with contextual links were getting mentioned in AI responses at nearly 3x the rate of traditionally-linked pages.
Here's my playbook
What I ended up doing and the results.
Instead of abandoning traditional SEO for shiny new GEO tactics, I developed a layered approach that builds on strong fundamentals while optimizing for AI systems.
Layer 1: Traditional SEO Foundation
First, I ensured every page had solid technical SEO, proper internal linking, and clear content structure. This remains non-negotiable. LLM robots still need to crawl and index your content, and quality, relevant content is still the cornerstone.
Layer 2: Chunk-Level Content Structure
Working with my client, we discovered that LLMs don't consume pages like traditional search engines. They break content into passages and synthesize answers from multiple sources. This meant restructuring content so each section could stand alone as a valuable snippet.
I implemented five key optimizations:
Chunk-level retrieval: Making each section self-contained with clear topic headers
Answer synthesis readiness: Logical structure for easy extraction by AI systems
Citation-worthiness: Factual accuracy and clear attribution
Topical breadth and depth: Covering all facets of topics comprehensively
Multi-modal support: Integrating charts, tables, and visuals
Layer 3: Strategic Backlink Targeting
This is where my approach differs from traditional link building. Instead of chasing high-DA links, I focused on "contextual authority" - links from content that AI systems are likely to reference.
My target list included:
Industry comparison guides and buying guides
Educational content and tutorials
Recent industry reports and studies
Expert roundups and opinion pieces
Layer 4: Content Cluster Strategy
I created interconnected content clusters around core topics, with each piece designed to support and reference the others. This built topical authority that both search engines and AI systems could recognize.
Layer 5: Measurement and Iteration
I tracked both traditional SEO metrics and AI mentions across different platforms. This dual measurement approach let me see which strategies worked for both traditional search and AI responses.
Key Insight
Backlinks signal trustworthiness to AI systems, but recency and context matter more than domain authority
Link Quality
Focus on getting mentioned in comparison guides, tutorials, and industry reports rather than generic guest posts
Content Structure
Break content into self-contained chunks that can standalone as AI response snippets
Measurement
Track AI mentions across platforms, not just traditional search rankings
After 6 months of testing this approach across multiple client projects, the results were clear:
300% increase in AI mentions for pages using the contextual linking strategy
Traditional rankings improved too - the approach didn't hurt SEO performance
Higher click-through rates from AI-referenced content (users trust AI recommendations)
Better content engagement due to chunk-level optimization
The most surprising result? Content optimized for AI responses performed better in traditional search too. The chunk-level structure and comprehensive coverage that AI systems prefer also aligned with Google's helpful content guidelines.
What really moved the needle wasn't aggressive GEO tactics - it came from solid, comprehensive content that naturally aligned with how AI systems process information. The backlinks that mattered weren't from high-DA sites, but from content that AI systems were already using as reference material.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Don't abandon what works: Traditional SEO fundamentals remain crucial for AI visibility
Context beats authority: A link from a relevant industry guide matters more than a generic high-DA backlink
Chunk-level thinking: Structure content so individual sections can stand alone as AI response snippets
Recency matters more: AI systems favor more recent sources, especially for fast-changing topics
Quality over quantity: One mention in a comprehensive buying guide beats ten directory links
Multi-platform measurement: Track AI mentions across different platforms, not just search rankings
Build for both: Strategies that work for AI often improve traditional SEO too
My biggest takeaway? The landscape is evolving too quickly to bet everything on optimization tactics that might be obsolete in six months. Focus on creating genuinely useful content that serves your audience, then layer on both traditional and AI-focused optimization strategies.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies looking to leverage this approach:
Focus on getting mentioned in software comparison guides and category pages
Create detailed integration guides that other sites will reference
Structure feature documentation for chunk-level consumption
Target links from software review sites and industry publications
For your Ecommerce store
For e-commerce stores implementing this strategy:
Get products featured in buying guides and comparison articles
Create comprehensive product information that stands alone
Target links from review sites and industry publications
Focus on educational content around product categories