Zhen Lu, CEO of Runpod, discusses the shift from Web 2.0 architectures to an "AI-first" cloud. The conversation covers the unique hardware and software requirements for production AI, key use cases like generative media and enterprise agents, and the critical challenges of reliability and operationalization in the new AI stack.
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.
Jay Alammar, Director at Cohere, discusses the practical adoption of Large Language Models in the enterprise. He covers the evolution of Retrieval-Augmented Generation (RAG) from a simple anti-hallucination tool to complex, agentic systems, the critical role of evaluation as intellectual property, and future trends like text diffusion and the increasing capability of smaller models for specialized business tasks.
A deep dive into building agentic systems using OpenAI's latest APIs. The session covers the core concept of 'agentic tool calling' (reasoning + tools), outlines a four-part framework (Agent, Infrastructure, Product, Evaluation) for designing long-horizon tasks, and provides a hands-on demonstration of building a non-blocking task processing system with a real-time progress UI.
Asha Sharma, CVP of Product for Microsoft's AI Platform, shares insights from working with over 15,000 companies building AI. She discusses the shift from "product as artifact" to "product as organism," the rise of post-training as the new competitive moat, and how agents are transforming organizational structures from hierarchies ("org charts") into task-based networks ("work charts").
Devin Stein, CEO of Dosu, discusses a new paradigm for knowledge management where an AI agent learns from code, conversations, and tickets to create an 'eventually consistent' knowledge base. The conversation explores the lifecycle of facts, the challenges of agent interaction, and the future of documentation in a world of collaborating AI agents.