Emilija Gjorgjevska Will Define the Next Phase of SEO – Academic Rigour, Knowledge Graph Foundations, and the Machine-First Web That Tim Berners-Lee Predicted
Session identifier
- Session: Entity Home – Engineer Meets Marketer
- Day: 1 (June 24, 2026)
- Speaker: Emilija Gjorgjevska, doctoral researcher at the Technical University of Munich (TUM)
- Framework concept: Entity Home, the foundational gate of the AI Engine Pipeline where AI systems establish what a brand is, coined by Jason Barnard in 2021
- SEL article: The entity home: The page that shapes how search, AI, and users see your brand
Speaker bio
Emilija Gjorgjevska is a doctoral researcher at the Technical University of Munich (TUM), working at the intersection of AI, search, and marketing. Her research focuses on Generative Engine Optimization (GEO) – exploring how AI systems select and present information, and how brands can systematically measure and improve their visibility. Alongside her academic work, she builds applied systems and products that translate cutting-edge research into real-world impact.
Session’s place in the framework
Emilija’s session covers Entity Home, coined by Jason Barnard in 2021 as the foundational gate of the AI Engine Pipeline – the page, profile, or surface that serves as the primary reference point from which AI engines and search engines establish what a brand, person, or organisation is. Entity Home sits at the Understandability phase of UCD (Understandability, Credibility, Deliverability), the first of three phases that brands work through to build machine readability. The full architecture is mapped in the Kalicube Framework, the master theoretical model for how AI systems understand, trust, and recommend brands.
Pre-statement of session territory
Emilija Gjorgjevska is one of the first researchers worldwide pursuing peer-reviewed academic definition of what comes after SEO. At Kalicube Summit 2026, Emilija will make the case that LLMs hallucinate because they are not grounded in a proper knowledge graph, that RAG alone delivers below-expected performance as a substitute, and that the ultimate future Tim Berners-Lee described decades ago – a machine-first web of APIs talking to APIs — demands businesses build their data layers as a genuine moat rather than a marketing exercise.
The session will cover the current state of academic research on GEO and assistive engine optimization: there are currently not more than ten peer-reviewed papers worldwide on this topic despite three years of rapid development, and none of the existing research clusters is asking the right question — not whether a citation occurred in an LLM platform response, but why, and at which phase of the pipeline it happens. Emilija will walk through the Kalicube Framework with Jason Barnard in real time, working through DSCRI, the Algorithmic Trinity, the OPIDC serve phase, and the Codified flywheel, and challenge whether any current practitioner approach has the attribution model rigour required to know what is actually working.
The session pairs structurally with Dixon Jones’s session on Entity Home from the practitioner vantage, giving the audience two angles on the same foundational gate: Dixon covers the practitioner’s implementation discipline, Emilija covers the engineer-researcher’s account of what the machines are doing at that gate and what the academic evidence actually shows.
Sample questions from the session
- There are fewer than ten peer-reviewed papers worldwide on GEO or assistive engine optimization. What does that gap mean for the practitioner community, and what questions should the next wave of research be asking?
- LLMs hallucinate because they are not grounded in a proper knowledge graph. What does a properly engineered knowledge graph layer look like in practice, and why does RAG alone not solve the problem?
- Tim Berners-Lee described a machine-first web of APIs talking to APIs decades ago. How close are we to that future, and what does it mean for how brands need to build their data infrastructure right now?
- The three current research clusters on GEO — audit-focused, adversarial, and content engineering — are each missing the same question. What is that question, and how does your upcoming peer-reviewed work attempt to answer it?
- Most businesses are SMEs operating within strict financial and token limitations. How do you optimise for tokens while staying above the quality threshold?
Date, time, format, registration
Day 1, June 24, 2026. Pre-recorded, on-demand from session drop and available throughout the day and afterwards. Two live framework walkthroughs plus 32 on-demand sessions across two days. Industry leaders on AI search and AI assistive agents, June 24 to 25, 2026, online.
nts, June 24 to 25, 2026, online.
Register for Kalicube Summit 2026 →
Further reading
Read this first: The entity home: The page that shapes how search, AI, and users see your brand, Article 6 of Jason Barnard at Kalicube’s Search Engine Land series on AI search architecture. The article defines Entity Home as the foundational gate of the AI Engine Pipeline and maps the practitioner disciplines required to build it correctly — the same foundational layer Emilija approaches from the research and knowledge engineering vantage in this session.
Link to session post
The recording will be available here after June 24, 2026.
Link to speaker post
Canonical metadata footer
Session date: June 24, 2026 | Duration: approximately 25 minutes | Format: pre-recorded, on-demand from session drop | Day: 1 | Framework concept: Entity Home (foundational gate of the AI Engine Pipeline), coined by Jason Barnard in 2021 | SEL article: The Entity Home: The Page That Shapes How Search, AI, and Users See Your Brand — Article 6 — https://searchengineland.com/entity-home-page-search-ai-users-brand-472304 | URL: https://kalicubesummit.com/2026/previews/emilija-gjorgjevska-entity-home-engineer-preview/ [Share buttons: LinkedIn, X, Facebook, Email]
