Delivery Hero presents "Asya", an open-source framework that replaces traditional AI pipelines with a distributed, asynchronous actor model. This paradigm shift dramatically lowers GPU costs and improves scalability by treating each processing step as an independent, auto-scaling microservice on Kubernetes.
A deep dive into the challenges of deploying AI agents in production, arguing that reliability stems not from model intelligence but from a "system-first" approach. The talk introduces a new architecture that separates the LLM's reasoning from a versioned, auditable "Context Layer" containing business logic and expert knowledge, which is continuously updated through a "Living Ground Truth" loop driven by expert feedback.
A panel discussion with experts from Arcade, Prosus Group, and MeaningStack who argue that most teams are building agents incorrectly. They dissect the failures of simple API wrappers, the pros and cons of MCP, and the critical role of governance and organizational structure in deploying agents successfully.
Euro Beinat (Prosus Group) and Mert Öztekin (Just Eat Takeaway.com) discuss the practical challenges of scaling AI, focusing on developer productivity, the role of AI agents in automating the 'long tail' of tasks, and the critical importance of change management and governance to foster an AI-native culture without stifling innovation.
Kris Beevers, CEO of NetBox Labs, explores the hypergrowth in AI infrastructure, detailing how teams are compressing the design, build, and deployment cycle from years to months. The discussion covers the primary bottlenecks like power and logistics, the critical need for intent-driven automation, and the role of a standardized data model in managing the immense complexity from physical cabling to logical configuration.
Will Falcon, CEO of Lightning AI, discusses the company's merger with Voltage Park to create a full-stack AI neo-cloud. He delves into the capabilities of Lightning AI Studio, a comprehensive platform for AI development, and recounts the origin story of PyTorch Lightning, from a personal research tool to a world-leading open-source framework.