The decision to build C++ on C was a pragmatic implementation strategy. Facing over 25 different linkers at Bell Labs, Stroustrup chose to compile C++ to C, using C as a universal low-level target to support all existing toolchains without having to modify them.

Bjarne Stroustrup clarifies that the rivalry between C and C++ is a community fabrication. He and Dennis Ritchie were friends who collaborated, with Ritchie helping design the `const` keyword and even pointing to C++ in his own papers as the language's obvious successor.

Contrary to the belief that abstraction adds overhead, C++ can achieve "negative overhead." High-level constructs give the compiler more information than raw C code, allowing it to perform aggressive optimizations that result in faster executables.

Comma AI's CTO advocates using Python for almost everything in their robotics stack. The benefits of faster development, debugging, and experimentation outweigh the raw performance of C++, which is reserved only for specific, unavoidable cases like safety-critical components or extreme performance bottlenecks.

The creation of the Rust programming language was a direct response to fundamental weaknesses in C++. Mozilla needed a way to eliminate entire classes of security vulnerabilities (memory safety) and safely leverage multi-core processors (concurrency), which were intractable problems in its massive C++ codebase.

Unlike software's daily compilations, hardware development allows only a few "compiles" (builds) in total. This necessitates a more conservative, upfront process focused on reliability and planning, as you can't ship over-the-air updates to fix physical products.

Bjarne Stroustrup advises against being "too clever." Manual optimizations from the 1990s are often "pessimizations" today because they constrain modern compilers, preventing them from applying more sophisticated optimizations tailored to new CPU architectures, caches, and memory access patterns.

While AI coding assistants appear to boost output, they introduce a "rework tax." A Stanford study found AI-generated code leads to significant downstream refactoring. A team might ship 40% more code, but if half of that increase is just fixing last week's AI-generated "slop," the real productivity gain is much lower than headlines suggest.

While static typing aids performance, its primary motivation for Stroustrup was reliability in systems without a human operator. Unlike a developer at a desk, a telephone switch or embedded device can't stop and enter a debugger for a runtime type error, making compile-time checks essential for robustness.