SE Radio: C Remains Foundational in 2026
On a recent Software Engineering Radio podcast, INRIA senior scientist Jens Gustedt argued for the continued relevance of the C programming language. Gustedt stated that C remains critical for systems programming and performance-sensitive workloads that underpin large-scale ML systems. He noted that understanding C is a differentiator for engineers working on core data pipelines or ML serving frameworks.
- The latest C standard, C23 (published in 2024 as ISO/IEC 9899:2024), modernizes the language by adding features for better C++ compatibility, such as C++11-style attributes, and removes obsolete features like K&R function definitions. The standards committee has also begun preliminary planning for a future revision, tentatively named "C2Y". - In performance benchmarks for CPU-intensive tasks, C and C++ consistently rank as the fastest, outperforming languages like Rust, Go, and Python. This raw performance is why C remains foundational for operating systems, hardware drivers, and embedded systems. - Many high-performance machine learning libraries popular in Python, such as TensorFlow and NumPy, are built with C++ and C on the backend to execute computationally expensive operations efficiently. This allows data scientists to work in a high-productivity language like Python while leveraging the speed of C for performance-critical calculations. - At major tech companies, a common engineering philosophy is "Python where we can, C++ where we must." C++ is frequently used for performance-critical backend services, such as Meta's video processing and Amazon's recommendation engines. - Job descriptions for ML Infrastructure Engineer roles at FAANG companies often list C++ as a required or beneficial skill alongside Python. This is because these roles involve building and maintaining the high-performance infrastructure for model training and deployment. - While C remains a top 5 language in 2026 popularity rankings, Rust has emerged as its main competitor for systems programming, offering comparable performance with stronger memory safety guarantees, though with a steeper learning curve.
