Operating Systems and System Programming: How AI is Changing Education in 2026

## Introduction Imagine: you're writing a driver for a new SSD in Rust, and a Linux virtual machine under the control of an AI assistant immediately highlights a potential data race. Or you're delving into the CFS (Completely Fair Scheduler) process scheduler, and a neural network generates an animation of how the execution queues work. In 2026, learning operating systems and system programming has ceased to be a boring reading of manuals — it's now a dialogue with artificial intelligence. The course "Operating Systems and System Programming" on the ASI Biont platform is not just lectures. It's a deep dive into the Linux kernel architecture, memory management, file systems, drivers in C and Rust, where AI acts as a mentor and generator of practical tasks. Let's figure out exactly how the technologies of 2026 help master one of the most complex disciplines in IT. ## Why is System Programming the Foundation? System programming is the circulatory system of any computer. Without understanding how processes, interrupts, virtual memory, and system calls work, you won't be able to write an efficient web server or reliable embedded software. Operating systems are the bridge between hardware and application software. ### Key Topics You Will Master: - **Process and Thread Management**: scheduling, synchronization, deadlock situations. - **Memory Management**: segmentation, paging, swap, malloc under the hood. - **File Systems**: ext4, Btrfs, Virtual File System (VFS), inode, and journaling. - **Device Drivers**: writing kernel modules in C and Rust, working with DMA. - **System Calls**: how read/write, mmap, ioctl work. ## How AI Accelerates Learning on ASI Biont? The main innovation of the course is generative AI, which creates personalized lessons and practical tasks. Unlike static textbooks, the neural network adapts the material to your level. For example, if you confuse the mechanisms of `fork()` and `clone()`, AI will generate 5 additional examples with explanations specifically on this topic. ### Real-World AI Usage Scenarios: 1. **Code Generation for Lab Work.** Need to write a simple task scheduler in C? AI will offer a skeleton and then check your solution for typical errors (e.g., forgot to free memory after `malloc`). 2. **Visualization of Complex Concepts.** Describing how the TLB (Translation Lookaside Buffer) works or the banker's algorithm for avoiding deadlocks — AI can build a diagram in text form or generate pseudocode. 3. **Analysis of Compilation and Linking Errors.** When writing a driver for Linux, you'll get not just a "segmentation fault," but a breakdown of the call stack with recommendations for fixing. 4. **Comparison of C vs Rust Approaches.** AI will show how the same task (e.g., working with shared memory) is solved in C with manual pointer management and in Rust with safe abstractions. > **Important:** AI does not replace the instructor. It generates lessons but does not respond in chat 24/7. All communication happens through structured assignments and tests. ## Practical Example: Writing a Kernel Module with AI Suppose you want to create a simple character driver that outputs "Hello, World!" AI on ASI Biont will suggest the following path: 1. **Generate a template** in C with comments for Linux Kernel 6.x. 2. **Show the structure** of `file_operations` and explain each callback. 3. **Check the build** via Makefile (AI will suggest the necessary flags). 4. **Offer a test** in Rust: implement the same driver using the `kernel` crate and compare memory safety. As a result, you won't just copy the code; you'll understand how `copy_to_user` works, why `kmalloc` can return NULL, and what alternatives Rust provides. ## What Will You Get After the Course? | Skill | Result | |-------|--------| | Understanding Linux Architecture | Confident work with /proc, sysctl, strace, perf | | Writing Drivers | Your own module for a real device (on

Operating Systems and System Programming: How AI is Changing Education in 2026

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