This presentation explores chiplet-based SoC design as a practical solution to the growing complexity of ADAS and autonomous vehicle systems. As platforms demand high-performance computing, real-time AI, and sensor fusion, traditional monolithic SoCs face performance, memory bandwidth, and flexibility limits. We introduce a modular approach that enables application-specific integration through collaboration with OEMs, Tier1s, and ecosystem partners. Topics include design flexibility, heterogeneous integration, and managing chiplet challenges such as high-bandwidth interconnects, power delivery, thermal constraints, packaging, and automotive-grade quality. A real-world use case shows how multiple SoC and HBM dies integrated on a silicon interposer overcome performance bottlenecks and support scalable architectures delivering hundreds of teraflops—essential for Level 4/5 autonomy. We’ll also touch on verification challenges and modern methodologies needed to manage such complexity. Finally, we highlight the role of open standards (e.g., UCIe) and ecosystem collaboration to ensure long-term interoperability and reduce development risk in next-generation automotive compute platforms.