A panel of experts from AWS, G-P, and AntStack discuss the practical impact of Generative AI on software development. They explore how AI is used as an accelerant for productivity, the challenges of applying it to large-scale system design, its role in modernization, and the future implications for developer careers and safety-critical systems.
David Anderson explains his "Value Flywheel Effect" framework, a model for continuous cloud modernization that joins business and technology strategy. He details how creating psychological safety, a robust serverless-first technology strategy, and a focus on system design over code builds the necessary momentum and shared context to harness future technologies like AI effectively.
Uma Ramadoss from AWS explains the core concepts of Agentic AI, differentiating it from standard AI workflows. The session covers how to build agentic systems on AWS using services like Bedrock and Step Functions, and open-source frameworks like Strands SDK, emphasizing practical architecture, context enrichment, and the importance of verification.
Prashanth HN explores the powerful synergy between event-driven Agentic AI and Serverless architecture. Learn how AWS services like Lambda, Step Functions, and Bedrock provide the essential building blocks for creating sophisticated, scalable, and cost-effective AI agents, with practical examples of Agentic RAG, swarms, and orchestration patterns.
Learn how Vercel's open-source Workflows platform simplifies deploying durable, observable, and long-running AI agents by abstracting away the infrastructure complexities of queues, databases, and error handling.
Ben Smith and James Beswick explore the evolution of modern software architecture, discussing the critical role of workflow services in managing distributed systems, the trade-offs between microservices and monoliths, and the power of plugin architectures.