Graph analytics expert Amy Hodler explores the power of graph data structures, covering fundamental concepts, graph algorithms like PageRank, and their application in fraud detection and supply chain optimization. She delves into the emergence of Graph RAG for enhancing AI systems and discusses the future of graphs as memory for AI agents and in causal inference.
OpenAI's Greg Brockman and Thibault Sottiaux explore the evolution of AI-powered software development, from the first coding sparks in GPT-3 to today's GPT-5 Codex. They detail the concept of the "harness," the rise of agentic coding, breakthroughs in automated code review, and how AI agents capable of running for hours on complex refactoring will reshape the future of engineering.
Co-founder Sam Ross discusses Numeral's journey from a personal e-commerce pain point to a venture-backed global tax platform. He covers the market opportunity created by outdated incumbents, the 'do things that don't scale' approach to finding product-market fit, lessons from fundraising, and how Numeral leverages AI to automate complex compliance workflows, shifting from a tool to a full-service solution.
MeshAgent introduces a multiplayer AI paradigm, shifting from single-user systems to collaborative 'Rooms' where teams of humans and agents can work together with shared context. This talk explores the platform's architecture, developer tools, and its approach to solving real-world collaborative tasks.
A deep dive into the architectural and economic foundations of memory for AI agents. The talk explores the core tradeoffs between classical data storage and dynamic agent behavior, introduces a human-inspired framework for memory, and discusses practical strategies and future directions for building reliable, evolving AI systems.
Jerry from LlamaIndex explains why naive Retrieval-Augmented Generation (RAG) fails in production and dives deep into advanced data quality techniques—from parsing complex documents and hierarchical indexing to chunking best practices—required to build robust, high-quality LLM applications.