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Wednesday September 9, 2026 11:05 - 11:45 EDT
AI-assisted Rust code writing is increasing in prevalence in both open-source and production environments. Recent LLM models can write Rust that compiles, passes tests and may look idiomatic, yet there can be underlying issues. Crate maintainers may frequently encounter "vibe-coded" contributions: code that is syntactically correct but architecturally un-idiomatic.
Get ready to contribute! This talk will mix maintainer experience with a small live snapshot of how the room is encountering AI in Rust today.
Drawing from lessons learned while maintaining an open-source Rust crate and managing a contributor community, the speaker will examine where AI genuinely accelerates development and where it consistently struggles. Rather than focusing on tools or prompts, the talk explores how LLM generated patterns work with Rust’s ownership borrow checker, type system, and particularly with Rust’s crate design.
We will look at patterns in “vibe-coded” Rust: code that may work but lack clear invariants and code fighting lifetimes and borrow checker issues. We’ll see where AI genuinely helps Rust developers, where it can actually struggle, and what it could mean for learning, reviewing, and maintaining Rust code.
Speakers
avatar for Lisa Crossman

Lisa Crossman

Bioinformatics Consultant, SequenceAnalysis.co.uk
Lisa Crossman is originally a Lab Biologist with a wealth of experience in scientific research and programming. She has a degree in Microbiology from University of Bristol, UK, MSc in Molecular Genetics from the University of Leicester and a PhD in Bacterial Genetics and Molecular... Read More →
Wednesday September 9, 2026 11:05 - 11:45 EDT
Palais des Congrès de Montréal

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