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The talk explores how Rust’s type system and memory safety can be leveraged to enforce mandatory guardrails at the infrastructure level, where traditional frameworks often fall short.
As autonomous AI agents move from prototypes to production, the gap between Python’s flexibility and the need for rigorous safety becomes a critical liability. This session introduces the "Iron Cage" architecture - a hybrid approach that utilizes Rust as a secure, high-performance runtime boundary for AI agents.
The talk explores how Rust’s type system and memory safety can be leveraged to enforce mandatory guardrails at the infrastructure level, where traditional frameworks often fall short. Through a real-world case study, the speaker demonstrates design patterns for wrapping unpredictable AI logic in a secure Rust environment. Attendees will learn how to transition from optional application-level validators to a system where safety and resource constraints are enforced by the runtime itself. The session provides a blueprint for building AI-native infrastructure that ensures production-grade reliability without sacrificing development velocity.
I'll share a few tricks to help you write cleaner, more powerful declarative macros. You'll also get a sneak peek at the nightly features to see what's coming next macro_rules! world.
In this talk, we’ll explore battle-tested best practices for integrating Claude Code into a professional Axum development workflow without compromising on Rust’s core values: correctness, clarity, and maintainability.
In 2024, I added the `Option::as_slice` and `Option::as_mut_slice` methods to libcore. This talk is about what motivated the addition, and looks into the no less than 4 different implementations that made up the methods. It also shows that even without a deep understanding of all compiler internals, it is possible to add changes both to the compiler and standard library.
This talk explains how Rust debugging actually works: how compiler-generated debuginfo (DWARF/PDB) maps binaries back to source, and how LLDB/GDB interpret that data in practice.
