AI hasn't replaced Technical SEO; it has raised the stakes and massively improved our productivity. The defining characteristic of a technical SEO in 2026 isn't just diagnosing a problem and carrying out an often time consuming solution, it's knowing how to architect prompts that force LLMs to actually solve it, treating AI as your ultimate Technical Assistant.

In this session, we will look at technical SEO data analysis and advanced AI prompting through a fresh lens: pattern recognition. Following a late-in-life Autism Spectrum Disorder (ASD) diagnosis in 2025, Alex underwent a profound career reflection, and he realised that his natural brain's inclination toward pattern-matching wasn't just a trait, it was a strong advantage in technical execution.

He will break down how to get past generic AI prompts, and instead feed LLMs the structural DNA of a technical issue in a collaborative way to enhance the technical stack (HTML, JSON, Python) to implement better and more efficient solutions for your clients.

Key Takeaways:

- The Pattern First Prompting Framework - You'll learn how to treat AI as a precise technical execution tool, rather than a magical, error-prone fix (which surprise, rarely works). You'll also learn to accurately map data anomalies and technical issues first, as well as how to prompt to truly create a extremely powerful addition to your technical arsenal.

- Live Breakdowns - Real examples of pattern recognition being used to diagnose and resolve basic, intermediate and complex technical issues.

- An Inclusive Blueprint - A framework full of actionable points that attendees can implement on Monday morning. This serves as reinforcement for Neurodivergent SEOs to own their natural strengths, while providing frameworks neurotypical SEOs can adapt to upgrade their own debugging, troubleshooting, and prompting workflows.

Thijs van Beers breaks down a practical framework for isolating traffic from Google AI Overviews, AI Mode, and "People Also Ask" using Google Tag Manager, GA4, and AI without relying on expensive third-party tooling. Thijs reveals how capturing this data originally made it possible to reverse-engineer underlying prompts and measure which content wins quotes in AI search.

However, in true search SEO fashion, Google recently threw a wrench in the gears. Thijs takes attendees through the rise and fall of this methodology, dissecting what changed, what we can still measure, and what the situation reveals about the eternal cat-and-mouse game between SEOs and Google.