AI makes Rust easier - but should you switch?

With AI assistants like GitHub Copilot, Claude, and ChatGPT, it's suddenly possible to write code in languages you don't master. But is that a good idea?

AI changes the calculus

Before AI:

• Rust = 6-12 months of learning
• Borrow checker = frustration
• Many give up

After AI:

• AI explains lifetime errors
• Generates boilerplate
• Suggests idiomatic solutions

Rust is now realistic for non-experts.

But there's a catch.

The problem: Maintenance

AI helps you write code. But who maintains it?

// AI generated this
fn process_data<'a, T: AsRef<str>>(data: &'a [T]) -> impl Iterator<Item = &'a str> {
    data.iter()
        .map(|s| s.as_ref())
        .filter(|s| !s.is_empty())
}

Questions:

• Do you understand what 'a means?
• Can you debug this in 6 months?
• Can your colleague?

If the answer is no, you have a problem.

The real risk

We've seen this pattern:

1. Developer uses AI to write Rust
2. It works! Ships to production
3. 6 months later: bug appears
4. No one understands the code
5. Rewrite in Go/Java

Result: Wasted time and money.

When AI + hard language makes sense

✅ Do it when:

• At least one team member truly understands the language
• You have time to learn along the way
• The performance gain is measurable and worth it
• You plan to invest in the competency

❌ Avoid when:

• The entire team is new to the language
• It's a critical system with no backup plan
• You have a tight deadline
• "AI can just write it"

Our recommendation

Use AI as a learning tool, not a crutch.

The best way to use AI to learn Rust:

1. Have AI explain code line by line
2. Ask for alternative implementations
3. Ask "why" for each decision
4. Write tests yourself - it forces understanding

What we do ourselves

We advise teams on technology choices, and see the consequences of both good and bad decisions.

We use AI daily:

• For boilerplate and repetitive code
• To explain unfamiliar libraries
• To suggest optimizations

But we always choose technologies we understand. Because we have to maintain them.

The most important thing AI gives us isn't code - it's faster learning.