Inside Microsoft’s audacious plan to rebuild itself with AI and Rust
When Microsoft engineer Mark Russinovich famously declared that “the industry should declare C and C++ deprecated,” it sounded radical. When Dave Hunt later set a far more concrete goal, eliminating every line of C and C++ from Microsoft by 2030, it sounded almost implausible.
And yet, for Microsoft, this ambition is not reckless. It is strategic.
Behind the bold headline lies a convergence of three forces reshaping software engineering: memory safety, algorithmic code analysis, and AI-assisted refactoring at unprecedented scale. The story is less about Rust versus C++ and more about who controls complexity in the age of trillion-line codebases.
Why C and C++ Became a Liability
For decades, C and C++ powered the modern computing world. Operating systems, browsers, cloud infrastructure, all were built atop languages that trusted developers to manage memory manually.
That trust has proven costly.
According to Microsoft, Google, and the U.S. Cybersecurity and Infrastructure Security Agency (CISA), over 70% of critical vulnerabilities in major software systems stem from memory-safety bugs. Buffer overflows, use-after-free errors, race conditions — the same classes of flaws recur year after year, despite better tooling and more experienced engineers.
Garbage-collected languages like C# and Java solved many of these problems, but they cannot operate everywhere. Kernels, hypervisors, device drivers, and low-latency systems demand performance and control that managed runtimes cannot reliably deliver.
Rust emerged to fill that gap.
Rust’s Real Advantage: Making Bugs Impossible
Rust does not promise perfect code. What it offers is something more powerful: a compiler that refuses to compile entire categories of bugs.
Memory ownership rules, borrow checking, and thread-safety guarantees are enforced at compile time. Developers are forced to confront ambiguity early, not after deployment, not after an exploit, not after a breach.
This is why Microsoft quietly began introducing Rust into the Windows kernel in 2023. Long before generative AI became a mainstream tool, the company was already experimenting with large-language models to assist in translating legacy C and C++ code into safer Rust equivalents.
The logic was clear: if the most dangerous bugs are structural, the fix must also be structural.
The AI Rewrite Is Not Magic, It’s Infrastructure
Hunt’s “North Star”, one engineer, one month, one million lines of code , understandably raises eyebrows. Even Microsoft struggles to deliver consistent UI theming across Windows releases. Rewriting decades of mission-critical code sounds fanciful.
But this effort is not being approached as a simple code translation problem.
Microsoft has built a code graph infrastructure that maps massive source trees into structured, analyzable representations. Dependencies, call graphs, memory lifetimes, and behavioral patterns are modeled at scale. On top of this, AI agents operate not as free-form code generators, but as algorithmically guided refactoring systems.
In other words, the AI does not “guess.” It is constrained.
This hybrid model, algorithms for structure, AI for transformation, is what makes the goal even remotely plausible.
Why This Matters Beyond Microsoft
If Microsoft succeeds, the implications extend far beyond Redmond.
First, it would prove that legacy technical debt is not permanent. For decades, large organizations accepted insecure code as the cost of longevity. AI-assisted modernization challenges that assumption.
Second, it would reset expectations for software safety. If trillion-dollar companies can systematically eliminate entire vulnerability classes, regulators will begin asking why others cannot.
Third, it changes what it means to be a software engineer. The role shifts from writing raw code to supervising, validating, and reasoning about large-scale automated transformations.
This is not automation replacing engineers. It is engineering moving up a level of abstraction.
The Risks Are Real
None of this is without danger.
AI-generated refactors can introduce subtle logic regressions. Rust’s safety guarantees do not prevent semantic errors. Performance trade-offs can surface in unexpected places. And C++ still enjoys a vast ecosystem, tooling maturity, and decades of optimization knowledge.
Moreover, not all legacy code should be rewritten. Some systems survive precisely because they are well-understood, battle-tested, and stable.
Microsoft knows this. Even Jeffrey Cooperstein, writing for Azure, acknowledged that “we are not able to rewrite everything in Rust overnight.” The shift is incremental, selective, and measured.
The difference now is momentum.
A Bet on the Future of Software
Microsoft’s investment in Rust is not ideological. It is economic.
Security breaches are expensive. Downtime is expensive. Trust erosion is expensive. In an era where cloud infrastructure underpins global commerce, reliability is no longer a technical preference, it is a business requirement.
By combining AI with algorithmic rigor, Microsoft is attempting something rare in tech: a long-term engineering reset.
Whether the 2030 deadline holds matters less than the direction of travel. The real signal is this: the world’s largest software company no longer believes human-scale engineering alone can manage machine-scale complexity.
And it may be right.
