What is Generative Engine Optimization (GEO), and does it replace SEO? In this episode of Root Cause we get to the root cause of what happens to being findable when people stop Googling and start asking ChatGPT, Gemini or Perplexity. With search engines, a human picks from a list of results. With AI search, the model gives one answer and one recommendation, and if you are not in it, you are not in the consideration set. That shift is what GEO (also called AI search optimization or AI visibility) is trying to address.
We cover GEO vs SEO and why good SEO is only a subset of AI visibility; the what, where and how of AI-readable content (which topics, which sites like Reddit, G2 and Capterra AI trusts, which formats); whether GEO feeds the AI slop machine (AI-generated content is no more readable to LLMs than human writing, and three purposeful articles beat ten); how fast-changing models affect what you optimize; why millennials using ChatGPT as a search engine and Gen Z using it as a companion are two different problems for a brand; B2B vs B2C vs creator use cases; and the fairness question of manufacturing a persona that ranks above the better product. Then the technical part: how you get a deterministic, credit-score-style AI visibility score out of non-deterministic LLMs, why the LLM should be a data extractor and never a grader, and practical GEO advice for content creators (know your proposition, get cited where AI trusts, transcribe your videos, and yes, bring back the blog).
My guest is Tamanna Haque, mathematician, lead data scientist with a decade of production AI on real customer data, and co-founder of GenSight.AI, a GEO platform she built in her personal time with her husband Jonas. This is her first public conversation about it, and I came in openly skeptical.
Chapters and Topics
00:00 Introduction of the Episode and the Guest
02:56 Why Build a GEO Product in the Evenings: Eating Your Own Dog Food
06:08 What Is Generative Engine Optimization?
07:21 GEO vs SEO: Being an Option vs Being the Answer
10:48 The What, the Where and the How of Being Visible to AI
11:51 Does GEO Feed the AI Slop Machine?
15:05 Models Change Fast: Optimize Once or Forever?
17:02 Millennials Search, Gen Z Chats: Two Different Problems
20:46 B2B vs B2C vs Creators: Who Benefits Most?
22:35 Manufacturing a Persona: Who Deserves the Top Spot?
26:58 Deterministic Scores from Non-Deterministic Models
29:39 The LLM as Data Extractor, Never a Grader
31:44 Free Advice for Creators: Know Your Proposition, Bring Back the Blog
36:09 Book Recommendation: Harry Potter
38:05 Question from Fraser Merrifield: Top Movies
39:46 Question for the Next Guest: Which Pet Would You Have?
40:38 Closing
Find Tamanna at:
Find me (Nune) at:
LinkedIn: https://www.linkedin.com/in/nisabek/
Substack: https://www.thoughtfultechnologist.com/
References
References mentioned during the talk (in order they appeared):
01:34 - GenSight.AI, the GEO platform Tamanna co-founded with her husband Jonas
11:26 - Review sites Tamanna names as inherently trusted by AI: Reddit, Capterra, G2
26:58 - GenSight.AI methodology: deterministic scoring, the LLM as data extractor, never a grader
https://gensight.ai/methodology
36:38 - Harry Potter, Tamanna’s book recommendation
https://en.wikipedia.org/wiki/Harry_Potter
37:23 - Harry Potter and the Methods of Rationality, the alternative universe I mentioned from my episode with Evan Marshall
38:05 - Question from Fraser Merrifield (”top five movies”), his Root Cause episode
38:46 - Casino Royale (2006)
https://en.wikipedia.org/wiki/Casino_Royale_(2006_film))
39:08 - The Mission: Impossible films
https://en.wikipedia.org/wiki/Mission:*Impossible*(film_series)
