Context engineering

Multi-Agent Personalization with Shared Memory: From Email to Website to Proposal // Hamed Taheri

Multi-Agent Personalization with Shared Memory: From Email to Website to Proposal // Hamed Taheri

This talk explores the challenges of using multi-agent systems for mass personalization, highlighting the inconsistencies and inaccuracies that arise from traditional methods like RAG and function calling. The speaker introduces Cortex UCM, a unified customer memory system that proactively infers and standardizes customer insights. This shared, structured memory layer enables agents to achieve a deep, consistent understanding of customers, leading to high-quality, scalable generative personalization for emails, websites, and product pages.

Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase

Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase

Harrison Chase, co-founder of LangChain, explains the evolution of AI agents from early, rigid scaffolding to modern, flexible "harnesses." He argues that "context engineering"—managing what an LLM sees—is the key to building effective long-horizon agents. Chase also explores how agent development differs from traditional software, highlighting the critical role of traces as the new source of truth and memory systems that enable agents to improve themselves over time.

Real-Time Voice Agents in Production

Real-Time Voice Agents in Production

Panos Stravopodis, CTO of Elyos AI, shares the infrastructure and orchestration challenges of building production-ready voice AI agents. He details the four pillars for success—latency, consistency, context, and recovery—and provides engineering patterns for error handling, context management, and achieving conversational coherence in real-time systems.

The Infinite Software Crisis – Jake Nations, Netflix

The Infinite Software Crisis – Jake Nations, Netflix

In an era of the "Infinite Software Crisis" where AI-generated code outpaces human understanding, this talk argues for choosing "simple" design over "easy" generation. The speaker presents a three-phase methodology—Research, Planning, and Implementation—that forces developers to think critically before generating code. This approach leverages AI for mechanical tasks while ensuring that human judgment, context, and a deep understanding of the system remain the core of the software development process, turning human insight into the ultimate competitive advantage.

Architecting AI Security & Trust Layers | Sumeet Jeswani | AI/Cloud Specialist | Google #ai

Architecting AI Security & Trust Layers | Sumeet Jeswani | AI/Cloud Specialist | Google #ai

Sumeet Jeswani of Google discusses the critical shift from AI-powered to AI-orchestrated cyber attacks, where autonomous agents now lead complex security breaches. The summary explores new manipulation techniques like prompt and data injection, and outlines a multi-layered defense strategy rooted in the principles of least agency, defense-in-depth, and building security into AI systems from the ground up.

Context Engineering 2.0

Context Engineering 2.0

Simba Khadder explains the evolution of feature stores and MLOps, detailing why they remain crucial in the age of LLMs for high-scale use cases. He discusses the acquisition of his company, Featureform, by Redis and outlines their new vision: building a "Context Engine" for AI. This engine aims to unify structured data, unstructured data, and memory into a single pane of glass, moving beyond simple RAG to a more sophisticated "Context Engineering 2.0" that empowers agents with rich, queryable context.