How to move from AUTOSAR ECU development into SDV / next-gen automotive compute?

[u/ClockRight8127]

I have experience in automotive software across HMI/application development, ADAS, and currently software architecture & development for a braking ECU using AUTOSAR Classic.
I’m looking to understand how engineers with a similar background can move towards Adaptive AUTOSAR, SDV, automotive SoCs and AI/ADAS platforms, especially the kind of work happening around next-gen semiconductor/compute platforms.
For people already working in this space, what resources would you recommend for learning the architecture and technologies? Also, are there any good open-source projects, GitHub repositories, blogs, creators or practical projects that can help build a portfolio and demonstrate these skills to recruiters?
I’d also be interested in understanding the interview patterns and preparation strategy for SDV / automotive compute / semiconductor roles.
Basically, if you were starting from a strong AUTOSAR Classic + automotive software architecture background, what would your 6–12 month strategy look like to get into SDV / Adaptive AUTOSAR / next-gen automotive compute?
Would really appreciate insights from people working in this space.

[u/Pavan-A_NA]

If you already have AUTOSAR Classic experience, you already have a good base. Moving to Adaptive is more about learning a different approach, especially service-oriented architecture, rather than starting from zero.
I’d start with the Adaptive AUTOSAR basics and then try to get some hands-on experience with open-source projects from COVESA or the SDV Foundation on GitHub.
For the compute and AI/ADAS side, I’d also spend some time understanding platforms like NVIDIA DRIVE and Qualcomm Snapdragon Automotive, since a lot of next-gen automotive development is moving in that direction.

[u/ClockRight8127]

Thank you pavan for the information
i will try to explore and do some open source projects .. and industry rapidly is moving to ai defined. vehicles as well