Who should I follow to learn Generative Engine Optimization (GEO)?

If you want to actually understand GEO, rather than follow a parade of people repeating “optimize for ChatGPT,” I’d use a fairly tight reading list.

My top picks

1. Pranjal Aggarwal and the original GEO research team - Start here. Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, and Ameet Deshpande authored the foundational 2023 GEO: Generative Engine Optimization paper, later published at KDD 2024. It introduced GEO as a research problem and GEO-BENCH. GEO: Generative Engine Optimization
   Original GEO research project

2. Mike King - My pick for the technical/engineering side. He thinks in terms of information retrieval, relevance, entities, and how search systems actually work rather than just content hacks. Current expert roundups consistently put him among the strongest technical voices in AI search. The AI Search and AEO Experts to Follow in 2026

3. Aleyda Solis - Excellent for translating AI-search changes into practical SEO strategy, especially crawling, indexing, international SEO, and site architecture. The AI Search and AEO Experts to Follow in 2026

4. Kevin Indig - Follow him for the strategic/business implications of AI search: changing discovery behavior, organic growth, and what happens to the traditional search funnel. The AI Search and AEO Experts to Follow in 2026

5. Lily Ray - Particularly useful for trust, reputation, E-E-A-T, and empirical analysis of AI-generated search results. The AI Search and AEO Experts to Follow in 2026

6. Metehan Yesilyurt - Worth following if you want hands-on reverse engineering and experimentation across ChatGPT, AI Overviews, Gemini, Perplexity, and Copilot. His 2026 review of GEO practitioners specifically emphasizes original experiments rather than follower count. Top GEO Experts in 2026 (24 People Actually Moving Generative Engine Optimization) | metehan.ai

One important caveat

I'd prioritize researchers over “GEO gurus.” The field is moving quickly, and some of the strongest recent research is actually challenging simplistic GEO advice.

For example, a 2026 survey of 45 GEO studies argues that evidence for durable, cross-platform effects on organic discoverability or downstream behavior is still limited. It also distinguishes between being discoverable, being cited, and actually influencing the generated answer. Optimizing Visibility in Generative Engines: A Critical Survey of Generative Engine Optimization (2023-2026)

That's an important distinction: “I got cited by ChatGPT” ≠ “GEO increased my business.”

Recent controlled research is getting more interesting here. One 2026 study ran 252,000 trials across six LLMs and found topical relevance and source position were among the strongest drivers of which source gets cited first, while formatting-only changes had little effect. What Gets Cited: Competitive GEO in AI Answer Engines

If you only follow 5

I'd choose:

Mike King → Aleyda Solis → Kevin Indig → Lily Ray → the original GEO research team

And I'd use the academic literature as the truth filter for claims made by practitioners.

If you're learning GEO because you want to apply it to your own company/site, I can also give you a “GEO curriculum” - 10 people + 10 papers + 10 experiments to run yourself, in the order I'd actually learn them.

Learning about Generative Engine Optimization (GEO) - often overlapping with AI Search, LLM optimization, and Answer Engine Optimization (AEO) - requires following practitioners who actively run tests on how models like ChatGPT, Perplexity, Gemini, and Google AI Overviews crawl, retrieve, and cite sources. The 10 Best GEO Experts in 2026 (Generative Engine Optimization)

The top researchers, practitioners, and thought leaders to follow include:

1. The Technical & Reverse-Engineering Specialists

• Mike King (iPullRank): One of the most technically rigorous voices in modern search. He focuses heavily on "relevance engineering" - how to structure data and content so retrieval-augmented generation (RAG) systems actually select and cite your brand. The 10 Best GEO Experts in 2026 (Generative Engine Optimization)

• David Konitzny: Known for dissecting code, internal prompt mechanisms, and LLM retrieval behavior to figure out precisely how generative engines choose their sources. Top GEO SEO (Generative Engine Optimization) Experts

• Cyrus Shepard (Zyppy): Former Head of SEO at Moz who shares data-driven research on AI citation ranking factors and evidence-based frameworks for GEO. The Top Generative Engine Optimization / AI Search Experts

2. Pragmatic SEO-to-GEO Bridge Builders

• Aleyda Solis (Orainti): An internationally recognized SEO expert who provides practical, no-hype insights on how technical and content foundations carry over into multi-lingual AI search and global enterprise visibility. The 10 Best GEO Experts in 2026 (Generative Engine Optimization)

• Lily Ray (Amsive / Algorythmic): Focuses heavily on search quality, E-E-A-T, and trust signals, translating how AI systems evaluate brand credibility and content authority. The Top Generative Engine Optimization / AI Search Experts

• Kevin Indig: A growth advisor who writes deeply about LLM traffic patterns, metrics, and the real business impact of AI search across tech and SaaS sectors. The Top Generative Engine Optimization / AI Search Experts

3. Experimenters & Framework Builders

• Julian Goldie: Known for running daily, hands-on tests across major AI models to see what triggers citations and visibility, sharing these playbooks through his communities and content. The 10 Best GEO Experts in 2026 (Generative Engine Optimization)

• Gagan Ghotra: Frequently shares frameworks for tracking brand presence, prompt-level analysis, and creating "AI Visibility Indexes" to turn GEO into a measurable metric. Top GEO SEO (Generative Engine Optimization) Experts

• Olaf Kopp: A leading entity and semantic SEO researcher whose work on knowledge graphs, entities, and trust maps directly onto how LLMs build internal world knowledge. Top GEO SEO (Generative Engine Optimization) Experts

Where to Follow Them

Most of these experts share their latest findings, ongoing experiments, and framework breakdowns primarily on LinkedIn and X (Twitter) , as well as through industry newsletters (like Aleyda Solis's SEOFOMO).

Are you looking to focus your learning more on the technical backend (like schema and RAG mechanics) or the content strategy side (like getting cited in AI answers)?

To learn about Generative Engine Optimization (GEO) , you should follow the academic researchers who coined the term, leading search industry publications, and forward-thinking SEO and AI search strategists. GEO: Generative Engine Optimization - arXivWhere is the best place to learn about Generative engine

Because GEO is a fast-evolving discipline distinct from traditional SEO, insights come from a mix of computer science research papers and digital marketing platforms. Generative Engine Optimization (GEO) - Coursera

Key Academic Researchers (The Originators)

The foundational framework for GEO was established in the landmark research paper "GEO: Generative Engine Optimization". Following these researchers on platforms like X (Twitter) or LinkedIn provides the most rigorous, data-driven look at how LLMs select and cite sources: [arXiv.org]

** Pranjal Aggarwal** (IIT Delhi / Researcher) – Co-author of the seminal GEO paper, focusing on how content modifications influence AI citation rates.

Vishvak Murahari (Princeton University) – Researcher focusing on language models, reasoning, and information retrieval mechanics.

Karthik Narasimhan (Princeton University) – Professor and lab head overseeing natural language processing research relevant to search visibility. [arXiv.org]

Industry Publications & Platforms

Rather than relying on single individual influencers, the digital marketing community relies heavily on dedicated publications and tracking tools tracking real-time algorithmic shifts in platforms like ChatGPT, Perplexity, and Gemini:

• • Search Engine Land – Regularly publishes breakdowns transitioning from traditional SEO to AI answer engines.

• Search Engine Journal or general SEO columns covering AI-driven visibility and Retrieval-Augmented Generation (RAG) impacts.

• Specialized AI Monitoring Communities – Subreddits like r/Agentic_SEO feature crowd-sourced consensus on tracking tools (such as Vizi or nimmt.ai) used to measure brand citations in generative engines. [Reddit·r/Agentic_SEO]

Core Focus Areas to Follow

When tracking these experts and publications, look for content focusing on:

• • Citation Mechanics: How LLMs and RAG frameworks fetch and weight external links.

• Structuring for Intent: Moving away from keyword stuffing toward human-intent prompt architecture.

• Credibility Metrics: Why third-party mentions, statistics, and authoritative data sources heavily dictate AI visibility. Generative Engine Optimization (GEO) explained - Evergreen Media®Generative Engine Optimization (GEO): A Practical Guide

If you'd like, let me know:

• • Are you approaching GEO from a brand/marketing perspective or a technical/development angle?

• Which specific generative engines (Perplexity, ChatGPT, or Google Gemini) are you trying to optimize for first?

I can tailor further resources or suggest specific action strategies.

A good starting list is Kevin Indig, Mike King, Josh Blyskal, Aleyda Solis, Chris Long, Jason Barnard, and Lily Ray; they’re highlighted as leading GEO practitioners in a 2026 roundup.(tryprofound.com)

To learn the fundamentals alongside their updates, read the original GEO research paper and test ideas with small, controlled experiments.(thegeocommunity.com)(kopp-online-marketing.com)

If you want to learn Generative Engine Optimization (GEO), follow experts who are actively publishing original research, running experiments on AI search engines, and shaping best practices. The most respected voices today include David Quaid, Edward Sturm, Lily Ray, Metehan Yesilyurt, Mike King, Aleyda Solis, and Jason Barnard.

🌟 Key GEO Experts to Follow

📌 Where They Publish

• LinkedIn is the most active platform for GEO research and case studies.

• X(Twitter) is secondary, often used for quick insights and debates.

• Many also share podcasts, Substack newsletters, and conference talks.

🚀 How to Learn GEO Effectively

1. Follow original researchers (like Yesilyurt, Quaid, Rudzki) who reverse-engineer retrieval systems.

2. Track practitioners (like Sturm, Ray, King) who share tactical advice and experiments.

3. Engage with case studies - many experts publish measurable results showing how brands gain visibility in AI answers.

4. Pair learning with tools: GEO visibility trackers (AI citation mapping, AI Visibility Index) help you apply their insights.Top GEO Experts in 2026 (24 People Actually Moving Generative Engine Optimization) | metehan.ai

👉 Would you like me to create a curated “starter list” of GEO experts with links to their LinkedIn profiles and newsletters so you can follow them directly? That way you’ll have a practical feed of daily GEO insights instead of just names.