Back to Blog
Engineering

Why We're Betting on Rust: Safety, Speed, and Sanity

After years of debugging memory leaks, we made a choice. Here's why Rust has become our go-to language for performance-critical systems—and why it might be yours too.

P
Prism Labs Team
AI Engineering Studio
January 1, 2026
10 min read
Why We're Betting on Rust: Safety, Speed, and Sanity

Production was on fire, and a use-after-free bug was causing cascading failures. That was the night I started seriously looking at Rust.

Fast forward to 2026, and Rust has become a key part of our toolkit for performance-critical systems. Here's what we've learned.

70% of security vulnerabilities are memory safety bugs
Click to zoom
70% of severe security vulnerabilities are memory safety bugs (Microsoft/Google data)

The Librarian Who Never Forgets

Imagine a library with a very strict librarian who tracks every single book at all times. That's Rust's "borrow checker".

Rust's ownership model visualized
Click to zoom
Rust's Ownership Model: 1) Every piece of data has exactly ONE owner, 2) Owner can lend data to others (borrowing), 3) Many readers OR one writer, never both

The magic: all this checking happens at compile time, not runtime. If your code could cause a memory bug, it won't compile. Period.

"The borrow checker isn't your enemy—it's your future self, sent back in time to stop you from making mistakes."

Rust Community Wisdom

Fearless Concurrency

Data races happen when two threads access the same data simultaneously. They're nightmarish to debug—often invisible in testing.

Rust makes data races literally impossible. The ownership rules that prevent memory bugs also prevent data races. If it compiles, it won't have data races.

How Rust prevents data races
Click to zoom
Traditional languages: two threads pointing to shared data with explosion. Rust: compiler blocking second thread with shield icon.

The Economics: Real Numbers

Real-world performance improvements from Rust
Click to zoom
Discord: GC pauses eliminated. Tenable: 75% less CPU, 95% less memory. Lambda cold starts: Rust 18ms vs Node 150ms vs Python 200ms

Discord's Story

Their "Read States" service in Go stuttered every 2 minutes from garbage collection. Rewritten in Rust, the spikes vanished entirely—plus lower memory and fewer servers.

Energy Efficiency

Programming language energy consumption comparison
Click to zoom
C: 1.00x (baseline), Rust: 1.03x, Java: 1.98x, Python: 75.88x

Python uses roughly 76x the energy of equivalent Rust code. At scale, that's thousands of tons of CO2 annually.

The Hybrid Approach

You don't have to rewrite everything. The most pragmatic approach:

Python + Rust hybrid architecture
Click to zoom
Top: Python/TypeScript interface. Middle: PyO3/FFI bridge. Bottom: Rust core. Examples: Pydantic V2 (5-50x faster), Ruff (100x faster linting)

The Honest Trade-offs

ChallengeRealityMitigation
Learning curve4-6 weeks to productivityDon't rush first projects; pair with mentors
Compile timesMinutes for large projectsModularize code; use fast linkers like mold
Talent scarcity£90k-140k+ for senior rolesTrain strong C++/Go devs; Rust attracts talent

When to Use Rust

When to use Rust decision matrix
Click to zoom
YES: High-performance services, Concurrent/parallel code, Security-critical, CLI tools, WebAssembly. PROBABLY NOT: Quick prototypes, Simple CRUD APIs, Data science scripts, Throw-away code

The Bottom Line

Rust isn't just faster Python or safer C++. It's a fundamental rethinking of how we build reliable software.

We've been burned too many times by production fires caused by memory bugs. Rust doesn't make us perfect programmers, but it catches us when we fall. For systems where reliability matters, the peace of mind is worth it.


Questions about adopting Rust? Get in touch—we love talking about this stuff.

Share this article
P
Written by
Prism Labs Team
AI Engineering Studio

A collective of AI engineers, data scientists, and software architects building the next generation of intelligent systems.