Grant Miller uses a surfing analogy to explore the challenges and strategies of AI adoption. He discusses the historical waves of technological innovation, the current surge in AI—from generative models to agentic systems—and offers practical lessons on navigating this rapid change by being prepared, patient, and adaptable.
A deep dive into the OpenAI Responses API, covering its architecture, advantages over Chat Completions, and practical applications for building persistent, multimodal agents with GPT-5, including live demos on migration and multi-tool workflows.
A deep dive into how AI agents connect to external tools, comparing the AI-native Model Context Protocol (MCP) with the high-performance gRPC framework. The summary explores their respective architectures, discovery mechanisms, and performance trade-offs, concluding with a vision for their complementary roles in future AI systems.
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.
Nick Coult from AWS explains that the future of serverless is not a replacement but an essential foundation for the rise of AI agents. This talk explores the core benefits of serverless, its synergy with event-driven architectures, and how agentic AI and agentic workflows will rely on serverless principles to scale and operate effectively.
A talk on designing a dependable AI execution layer that handles thousands of operations without constant supervision. The system is built to be precise, responsible, and action-oriented, avoiding common LLM pitfalls like burnout, memory bloat, and overthinking.