AI Engineering
Designed for practitioners building AI systems and applications in production this track explores novel architectures and system designs, from innovative approaches to RAG and agent pipelines to real-world case studies backed by production metrics.
Sessions will cover open source launches, major tool releases, and the hard technical problems teams are solving in the field—including integration patterns, infrastructure challenges, and lessons learned at scale.
SWE and agentic coding
For software engineers evolving their practice using AI coding tools. We'll cover how AI is transforming the entire software development lifecycle—from productivity hacks that save hours daily to real examples of AI-assisted development in action.
Sessions will explore when AI tools work brilliantly, when they fall short, and how to integrate them effectively into your process, whether you're working solo or on a team.
AI Leadership
Exclusively for senior technical leaders defining AI strategy at scale—CTOs, VPs of AI, AI Architects at large organizations, and the most senior AI decision-makers at their companies.
Sessions will tackle the strategic challenges of building and scaling AI engineering organizations: defining and executing AI strategy, build vs. buy decisions for AI infrastructure, organizational transformations, compensation structures and career ladders for AI roles, and navigating compliance and legal considerations.