About CiteMET

Mahmoud Halat is a product and growth systems builder who specializes in the practical application of AI. His work focuses on the intersection of data, product marketing, and AI transformation, positioning him as a key architect in the emerging field of Answer Engine Optimization (AEO). Mahmoud has direct, hands-on experience designing and launching sophisticated AI-powered content engines that translate complex data into high-value, discoverable answers. His technical work includes co-authoring a patent for a novel data harmonization engine, giving him a fundamental, "from-the-ground-up" understanding of how to structure information for machine consumption - a core pillar of successful AEO. As an entrepreneur, Mahmoud is an award-winning product builder, recognized in major international competitions for his ability to rapidly take AI-native applications from initial concept to scaled, profitable ventures. This unique blend of principled systems-building and rapid, real-world execution informs his strategic insights. Mahmoud also serves as a Guest Lecturer at the University of Toronto, where he speaks on the critical topic of "using AI tools and data with care."

Cho Yin Yong is an AI Engineering Leader and University Lecturer whose work sits at the intersection of artificial intelligence, web architecture, and user experience. With a career built on a deep curiosity for navigating technological change, Cho brings a unique, foundational perspective to the emerging field of Answer Engine Optimization (AEO). As an AI Engineering Leader, he has guided development teams in delivering complex projects, earning two co-authored patents and two competitive AI awards for his work in practical AI applications. This hands-on experience in building AI-driven systems, like the "Instant Intelligence" platform ziani.ai, gives him an expert's understanding of how large-scale models process information - a critical insight for mastering AEO. In addition to his industry role, Cho is the youngest sessional lecturer promoted in the CMS department at the University of Toronto, where he teaches "Engineering Large Software Systems" and "Programming on the Web." This academic position grounds his practical AI expertise in a deep understanding of the web technologies, data structures, and system architectures that form the backbone of all search and answer engines. Cho's dual role as both a builder and a teacher makes him a powerful voice in the AEO space. He doesn't just understand the theory of how to optimize for AI; he has actively built the types of intelligent systems that CiteMET AEO aims to leverage.