Over the past decade, autonomous driving development has undergone a profound transformation – from fragmented ECU-based architectures and smart sensors to centralized, software-defined vehicle platforms powered by AI. Drawing on experience across academia, startups and enterprise environments, the talk will explore how system architectures, sensor data and perception pipelines and development workflows have evolved in production vehicles. It will also examine how these shifts have reshaped R&D practices, tooling and team competencies, both in terms of hard and soft skills, organization structure and modus operandi. As AI continues to expand beyond perception into planning, control and end-to-end systems, an outlook will be offered as to what this means for future hardware/software co-design and engineering organizations.

• The architectural shift: from distributed ECUs to centralized, high-performance SDV platforms
• Evolution of perception pipelines: from modular pipelines to integrated, data-centric systems
• Changing R&D workflows: simulation, CI/CD and data-driven development at scale
• New skill sets and tooling: what modern AD teams need versus a decade ago
• The future: AI beyond perception, end-to-end approaches and HW/SW co-optimization