Robert from Emergent Methods discusses how grounded synthetic news data can solve the publisher revenue crisis in the AI era. He details the process of 'Context Engineering' news into token-optimized, objective data for high-stakes AI agent tasks, covering their open-source models for entity extraction and bias mitigation, and the on-premise infrastructure that protects publisher content.
Simba Khadder explains that the primary bottleneck for LLM agents is not intelligence, but access to structured data. He introduces EnrichMCP, an open-source framework that creates a semantic layer over data models, enabling agents to discover, reason about, and query data sources like SQL databases effectively, moving beyond the limitations of RAG and direct API conversions.
A discussion on the state of technical infrastructure, focusing on how AI and Large Language Models represent a new, fourth foundational pillar alongside compute, network, and storage. The talk covers how AI is disrupting software itself, the investment landscape, and the future of the developer profession.