The GenAI Graph Gathering is an event that brought together experts in the field of graph-based artificial intelligence to discuss and share knowledge on GraphRAG, a technique that combines knowledge graphs with retrieval-augmented generation (RAG). The gathering aimed to catch up on recent developments and compare notes on various aspects of GraphRAG. Researchers have found that projects using GraphRAG often start with either unstructured or structured data, but those using mixed data tend to succeed more consistently. The group discussed ways to improve developer experience, including the use of templates and guidance for domain-specific approaches. They also explored knowledge graph construction, GraphRAG techniques, and real-world experience. Key concepts include knowledge graphs as an information architecture that can be simple or comprehensive, and ontologies as a set of concepts and categories that show properties and relations between them. The gathering highlighted the importance of interoperability, explainability, grounding, and balancing ease of use with rigor in ontology development. Advanced graph retrieval techniques continue to explore various methods, including contextual retrieval, query-focused summarization, and GNNs. Ultimately, the goal is for each guest to be successful on their path and for everyone to benefit from GraphRAG, which continues to evolve as a broad spectrum of approaches and technologies.