Meta Knowledge Graph: A Self Learning Agentic System

Session track: Data Intelligence

Session time: 02:00 pm - 02:30 pm UTC November 12

Session description:

This talk presents a practical architecture for building harness-agnostic intelligent agent systems that can persist context, retrieve knowledge, and improve across sessions. Rather than treating memory as a standalone database, it frames agent intelligence as a loop: tools provide on-demand access to enterprise data and memory, hooks passively capture execution traces, metadata layers help agents discover and reason over available knowledge, and background consolidation turns raw activity into durable learnings and prompt improvements. The session will cover the core design patterns, tradeoffs between agent-driven and harness-driven orchestration, and how a knowledge graph can act as the shared substrate for provenance, retrieval, memory, and self-improvement.

Speaker

Firat Tekiner

Director AI Product Management

Firat Tekiner, PhD, MBA, is Senior Director of AI Product Management at Neo4j. Previously Senior Staff Product Manager for Data Analytics and AI at Google Cloud, he led Data Agents work in BigQuery. He has over 25 years’ experience building products and information systems for major research, education, telecommunications, finance and retail organisations. Earlier roles include National Supercomputing Services, the National Centre for Text Mining and Ab Initio Software. He has over 50 publications across parallel computing, big data, AI and computer communications, and co-authored Architecting Data and Machine Learning Platforms (O’Reilly, 2023) and Architecting Data Systems for AI (O’Reilly, exp 2026).