Nikesh Arora, CEO of Palo Alto Networks, discusses the transformative impact of AI on search, enterprise business models, and cybersecurity. He explores the shift from search to agentic AI, the challenges and opportunities for enterprise adoption, and how AI is fundamentally compressing cyberattack timelines while enabling new, data-centric defense strategies.
Jesse Zhang, co-founder and CEO of Decagon, discusses how their AI agents are revolutionizing customer service for large enterprises by replacing mundane human labor. He covers their go-to-market strategy, the importance of a hardworking in-office culture, his journey as a second-time founder, and the future of an agentic world where AIs interact on behalf of companies and consumers.
Hudson Buzby from JFrog discusses the critical security, governance, and legal challenges enterprises face when adopting open-source AI models. He highlights the risks lurking in repositories like Hugging Face and argues for a centralized, curated AI gateway as the essential framework for enabling safe, scalable, and cost-effective AI development.
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.
Bob McGrew, an early executive at Palantir and former Chief Research Officer at OpenAI, explains the Forward Deployed Engineer (FDE) model he helped pioneer. He details its origins, operational structure, and why it has become the dominant strategy for AI agent startups navigating a new market with immense product discovery needs.
Ben Lorica and Evangelos Simoudis explore the nuanced landscape of AI regulation, contrasting foundation model oversight with domain-specific rules and highlighting the critical issue of IP rights in training data. They also analyze China's engineering-led AI strategy and the challenges of enterprise AI adoption.