Linux and Windows are quietly undergoing one of the biggest rewrites in their history, as artificial intelligence collides with Rust to reshape how low level code is produced and maintained. Instead of relying on decades of hand tuned C and C++, major vendors are starting to feed their legacy code into AI systems that help translate it into safer Rust, then use those same tools to keep the new codebases evolving. The result is a shift in power from individual experts to AI assisted teams, with security and reliability as the main prize.
Why Câs memory problems finally forced a rethink
For years, operating system teams tolerated Câs sharp edges because nothing else seemed to match its mix of performance and control. That bargain has broken down. Security data now shows that about 70% of operating system security holes trace back to memory errors, the kind of buffer overruns and use after free bugs that are baked into Câs design. When the majority of your critical vulnerabilities come from one class of mistake, the language itself becomes a security liability rather than a neutral tool.
Rustâs pitch is that it can deliver the same low level control as C while preventing entire categories of memory bugs at compile time, which is why its strong safety guarantees are now being treated as a frontline defense rather than a nice to have. The shift is not just technical, it is cultural. Teams that once prided themselves on mastering Câs pitfalls are now willing to let the compiler, and increasingly AI systems, shoulder more of the burden. That is where Dec era conversations about Why C is still used and how Easy it once seemed give way to a new focus on Memory safety as a strategic requirement rather than an academic concern.
Rust moves from experiment to fixture in the Linux kernel
Linux has been the bellwether for systems programming practices for decades, so its embrace of Rust carries outsized weight. Kernel maintainers have now made Rust a permanent part of mainstream Linux development, ending its trial status and opening the door for new drivers and subsystems to be written in the safer language. Reports on Rust boosted by permanent adoption describe how this is not a cosmetic change, but a structural one that will influence how contributors approach low level work for years, even as the migration of existing C code is not yet complete.
Inside the kernel community there was early skepticism about mixing languages, yet, Despite the initial fuss, more and more contributors are choosing Rust for new components when they have the option. Coverage of how Despite the controversy Rust is no longer considered experimental highlights that new drivers, helper libraries and other pieces of low level development work are now legitimate Rust targets. That means future hardware support, from network cards to storage controllers, is increasingly likely to arrive with memory safety baked in at the language level.
Microsoftâs billion line Rust ambition
On the Windows side, Microsoft is treating Rust not as a side project but as a core modernization strategy. The company has publicly set a bold goal to replace 1 billion lines of C and C++ with Rust, and it does not intend to do that by hand. Instead, executives have described a plan to combine AI and algorithm driven analysis to rewrite the companyâs largest codebases, using machine assistance to understand sprawling legacy systems and propose safe translations. In one detailed account of How Will They Do It, Hunt explains that Microsoft will lean on algorithm based techniques for code understanding, refactoring and verification, with Our tools acting as copilots rather than autonomous rewriters.
That ambition has led some observers to assume Microsoft is about to rebuild Windows from scratch in Rust, but the reality is more nuanced. Hunt has been explicit that the project is to investigate how AI can assist in translating code from one language to another, not to flip a switch on the entire operating system. Reporting that Microsoft is not rewriting Windows in Rust clarifies that the focus is on targeted components and on building a pipeline that can be reused across products. The distinction matters, because it shows the company is betting on AI assisted migration as an ongoing capability, not a one time heroic rewrite.
Hyper-V and Azure as Rust testbeds
Before touching the heart of Windows, Microsoft has been proving out Rust and AI workflows in its cloud infrastructure. Security critical parts of Hyper-V, the hypervisor that underpins Azure, are being rewritten in Rust, a move that directly ties language safety to the reliability of virtual machines that run everything from internal line of business apps to global consumer services. Community discussions of how They are approaching Hyper components describe a focus on the most exposed and sensitive paths first, and note that Microsoft has Contributed work even for 32-bit architecture support as part of this transition.
This cloud centric experimentation is not happening in isolation. Earlier efforts to modernize Windows itself, including rewriting parts of the Windows kernel in Rust after Azure CTO Mark Russinovich pushed for safer systems code, show a feedback loop between on premises and cloud platforms. One analysis of how Windows kernel components began moving to Rust credits Azure CTO Mark Russinovich with setting the tone that C and C++ should be phased out where practical. Hyper-V and Azure therefore serve as both proving grounds and pressure points, where any gains in safety and maintainability are immediately visible in uptime and incident metrics.
AI as the new systems programmer
What makes this moment different from past language shifts is the role of AI in doing the heavy lifting. Instead of asking human engineers to manually port millions of lines of C, Microsoft wants to develop technology that can analyze, translate and refactor code at industrial scale. Internal targets framed as â1 engineer, 1 month, 1 million lines of codeâ capture the ambition: a single developer, armed with AI tools, should be able to supervise the safe migration of a codebase that would once have taken a large team years. Coverage of how Microsoft is using Rust and AI together notes that a significant share of new code is now written by AI, with humans reviewing and integrating the results rather than typing every line themselves.
At the same time, Microsoft is building infrastructure to make these AI driven changes safe and repeatable. Plans to move to Rust with help from AI include not just translation models but systems that can reason about dependencies, run large scale tests and make code modifications at scale without breaking downstream components. Reporting on those Plans describes a pipeline where AI suggests changes, automated checks validate them, and engineers focus on edge cases and architectural decisions. In that model, AI is less a replacement for systems programmers and more a force multiplier that lets them reshape legacy platforms without losing control.
Linux developers experiment with Rust AI and LLMs
On the Linux side, the AI story is more decentralized but no less significant. Individual maintainers and distributions are starting to use large language models to draft kernel patches, refactor drivers and even explore new subsystems, then rely on Rustâs compiler to catch memory safety issues that might slip past human review. Commentators tracking how Rust AI and optimizations are changing Linux point to a wave of experimentation, from AI assisted kernel code to user space tools like GIMP integrating AI features. The common thread is that developers are comfortable letting AI propose code as long as strong type systems and safety checks stand between those suggestions and production.
This blend of Rust and AI is gradually changing the profile of Linux contributors. Where once the barrier to entry for kernel work was deep C expertise and years of apprenticeship, newer developers can lean on AI to navigate unfamiliar subsystems and on Rust to prevent the most catastrophic mistakes. That does not eliminate the need for seasoned maintainers, but it does shift their role toward reviewing AI generated patches, guiding architectural choices and curating which experiments make it into mainline. In effect, AI is becoming a junior developer that never sleeps, while Rust acts as the strict mentor that refuses to compile unsafe shortcuts.
Windows, Rust and the limits of automation
Even with AI in the loop, Rust is not a magic wand for Windows or any other large codebase. Experts are quick to point out that You can still introduce logic errors, race conditions and other bugs that have nothing to do with memory safety, even in a language designed to prevent Common Vulnerabilities and Exposures. The first Common Vulnerabilities and Exposures entry tied to a Rust component in Windows 11 24H2 underscored that reality. It showed that while Rust can eliminate entire classes of memory related CVE issues, it cannot stop developers from making higher level mistakes or misconfigurations.
That is where AIâs role becomes more complex. The same tools that help translate C to Rust can also introduce subtle behavioral changes if they misunderstand the original intent, and automated refactoring at scale raises the stakes of any oversight. Microsoftâs own messaging, including clarifications that it is not rewriting Windows wholesale in Rust and that Huntâs project is exploratory, reflects an awareness of those limits. The companyâs strategy of starting with well scoped components, such as parts of Hyper-V and specific Windows kernel modules, suggests a recognition that AI assisted migration must be paired with careful human review, staged rollouts and robust telemetry to catch regressions before they reach every desktop.
Security, performance and the new OS bargain
Stepping back, the convergence of AI and Rust is reshaping the basic bargain that operating systems strike with their users. For decades, performance and backward compatibility often trumped security, with vendors accepting a steady stream of memory related exploits as the cost of doing business in C. Now, with 70% of OS security holes tied to memory errors and with credible alternatives available, that tradeoff is no longer defensible. Rustâs adoption in Linux and Windows, backed by AI systems that can tackle the scale of existing codebases, signals a shift toward treating safety as a default expectation rather than an optional hardening pass.
Performance, interestingly, is not being sacrificed in the process. Rustâs low level control allows it to match or exceed C in many hot paths, and AI driven profiling can help identify where hand tuning is still necessary. In cloud environments like Azure, where Hyper-Vâs behavior directly affects customer workloads, early Rust components are being judged not just on security but on latency and throughput. On the Linux side, kernel developers are watching Rust drivers closely for any regressions, but the decision to make Rust a permanent option suggests confidence that the language can meet their standards. As AI tools mature, I expect more of the performance work to shift from manual micro optimizations to AI guided exploration, with humans deciding which tradeoffs align with the platformâs long term goals.
What this means for developers and users
For working developers, the message is clear: AI literacy and Rust proficiency are becoming core skills for anyone who wants to shape the future of Linux, Windows or the cloud platforms built on top of them. The combination of AI copilots, algorithmic code understanding and Rustâs safety model is redefining what it means to be a systems programmer. Instead of memorizing every corner case of Câs pointer arithmetic, engineers are being asked to design robust interfaces, interpret AI generated diffs and reason about how changes ripple through complex systems. Those who can guide AI tools effectively, and who understand Rustâs ownership and borrowing rules deeply, will be in a position to influence some of the most critical software on the planet.
For users, most of this work will remain invisible, surfacing only as fewer catastrophic security incidents and more stable updates. When Microsoft uses AI to help replace C and C++ with Rust in Windows components, or when Linux distributions ship kernels with Rust based drivers, the ideal outcome is that nothing breaks and fewer emergency patches are needed. Yet the stakes are high enough that these behind the scenes changes deserve attention. They represent a rare moment when two major operating system ecosystems are simultaneously retooling their foundations, guided by the same twin forces of AI and Rust. How well they manage that transition will shape not just developer workflows, but the security and reliability of the digital infrastructure that everyone now depends on.
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