Rust is the Language of AGI
Why the compiler that frustrated you is the reward function that will enable AGI. How Rust's strictness makes it perfect for AI-generated code.
The Paradox of Rust
Most loved language, hardest to learn—perfect for AI
Most Beloved Language
10 Years
Stack Overflow's most beloved programming language, every single year
Admiration Score
82%
Developer admiration rate in Stack Overflow surveys
"Rust has a very steep learning curve because it has a very powerful compiler that forces you to do the right thing. You can do a lot of things that are not only wrong, not only not optimal but also very bug prone in languages like C++ or in languages like Python, JavaScript, they're not even a compiler, right? So it's just anything goes right in no strong type system."
— Michael Yuan, Founder, Second State
Why AI Prefers Rust
The compiler as reward function
The Compiler as Reward Function
Rust's strict compiler creates an optimal feedback loop for AI learning. In reinforcement learning terms, the compiler provides immediate, unambiguous rewards: code either compiles or it doesn't.
"The compiler of the rust language provide a very good feedback loop for the AI so it forces AI to generate what we call a very good reward function. For any question or any request you have, a correct answer in the world of rust is what's the compiler accepts. It provides a very strong feedback to the large language model so it can get really good at those things."
— Michael Yuan, Founder, Second State
"Rust is better suited for machines not only because it's more efficient but because it's more structurally oriented for the strong compiler checking the strong type system and all that. It's just more rigorous."
— Brett Taylor, Chairman, OpenAI Board (via Latent Space Podcast)
Once it compiles, it works
One of the experiences that a lot of Rust developers have is that there's little debugging—once your Rust project compiles, there's a high likelihood it's going to run correctly.
Rust Coder: AI That Passes Exams
Real-world validation with 1,000+ developers
Active Users
1,000+
Developers using Rust Coder in university bootcamps
Knowledge Base
Hundreds
Programming tasks with verified solutions
Demo: University Exam Question
The demo shows a complex exam question: converting numbers to different bases. The AI running on Gaia network generates complete Rust code, explains its approach, and the code compiles and runs correctly on the first attempt.
$ cargo test
running 3 tests
test convert_binary ... ok
test convert_hex ... ok
test convert_octal ... ok
test result: ok. 3 passed; 0 failed
MCP Server That Fixes Its Own Bugs
Automated compile-and-fix loop
LLM Agent
Cursor IDE
AI-powered IDE
Claude
Anthropic AI assistant
GPT-4
OpenAI language model
Qwen2.5-Coder
Alibaba coding model
MCP Protocol
Open MCP Proxy
Proxy server for MCP
Generate Tool
Code generation tool
Compile & Fix Tool
Auto-compile and fix errors
Rust Coder
Vector Database
Embeddings storage
Knowledge Base
Verified solutions
Error Patterns
Common error database
Infrastructure
Llama Edge
Edge runtime
Gaia Network
Decentralized compute
Rust Compiler
Compiler as reward function
Developer introduces bug
Missing semicolon, unclosed brace, or type error
MCP server compiles code
Rust compiler detects and reports errors
AI analyzes error messages
LLM parses compiler output and identifies fixes
AI generates fix
Applies correction to source code
Repeat until success
Cycle continues until compilation succeeds
"It's a fully integrated solution with Rust Coder's knowledge base of all the Rust compiler error messages and how to fix those error messages. And as you use it, the knowledge base also grows. Sometimes it can't fix it, but cursor would give a different answer. So it would learn as it goes how to fix this type of issues."
— Michael Yuan, Founder, Second State
The Tech Stack
From edge deployment to autonomous agents
Llama Edge
Open-source runtime for edge AI deployment. Tens of megabytes instead of gigabytes for PyTorch. Supports LLMs, YOLO, Whisper, TTS, Stable Diffusion.
Gaia Network
Decentralized compute network for running open-source AI models. Packaging of Llama Edge + vector database + knowledge base.
Vector Search
Multiple backends: Elasticsearch, TiDB, Qdrant. Embeddings-based retrieval for Rust examples and patterns.
MCP Protocol
Model Context Protocol for integrating LLMs with tools. Not just for humans—fundamentally for machine-to-machine communication.
The Vision: Autonomous Code Generation
MCP for machines, not humans
"The path to AGI may come from code generators. If the large language model planned for something and it wants to execute on it, it could call a core API or it could generate code to perform this task for it."
— Michael Yuan, Founder, Second State
The Drone Scenario
You can envision a future where we build a system that controls a drone. The Rust code generated is to direct where the drone going to fly and how would they behave in certain circumstances. It would just generate that code using the SDK that is specified and then automatically compile and debug until it works and get uploaded to the drone and then the drone fly out and do whatever the AI wants it to do, entirely without human intervention but with reasonable guarantees of the correctness of the code that been generated.
Generated Code vs APIs
When AI generates Rust code instead of calling APIs: Flexibility (not limited by API surface), Safety (compiler verifies correctness), Performance (native execution), Autonomy (AI can implement novel solutions).
Getting Started with Rust Coder
Installation and usage
Installation
# Clone Rust Coder
git clone https://github.com/second-state/rust-coder
# Install MCP server
npm install -g @rust-coder/mcp-server
# Start Cursor integration
rust-coder-mcp start
Two Interfaces
REST APIs
For workflow engines, deterministic software, autonomous agents
MCP Tools
For LLM agents (Cursor, Claude Desktop, and other MCP clients)
Key Takeaways
Actionable insights
Compiler as Reward Function
Rust's strict compiler is a feature, not a bug. For AI, immediate feedback from compiler errors creates an optimal learning loop.
AI-First Language Design
Languages designed for human ergonomics (Python, JavaScript) prioritize easy syntax. Languages designed for AI (Rust) prioritize verifiable correctness.
Beyond Human Assistance
The vision isn't just AI helping humans write code—it's AI generating verified code for autonomous execution.
Integrated Knowledge Growth
Rust Coder's vector database expands with every error-fix interaction, creating a self-improving system.
Production-Ready Today
Over 1,000 developers are already using Rust Coder in university bootcamps. It's not research—it's deployed.
MCP for Machines
MCP is not really for humans, although we're using it for humans at this moment. It's really for machines.
"If we see a future where most of the code is written by AI, to have AI write human-incomprehensible Python or JavaScript is not the way to go. Rust would be the way to go because it's friendly to the AI and reasonably friendly to humans."
— Michael Yuan, Founder, Second State
Research Notes
Methodology: This analysis is based on the full transcript of Michael Yuan's talk at the AI Engineer Conference. All quotes are verified with exact YouTube timestamps.
Speaker: Michael Yuan is founder at Second State, the company behind Llama Edge and Gaia Network. The Rust Coder project is sponsored by the Linux Foundation through LFX internship grants.
Related Content: This talk complements discussions on AI engineering patterns, MCP tool integration, and the future of autonomous code generation. See Ship Agents that Ship, Why Bolt.new Won for related insights.