Is Python Becoming the "Hat of Rust" in the Era of AI Writing Code?

#Rust #Go #Software Development

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Is Python Becoming the Hat of Rust in the Era of AI Writing Code?

📰 News Overview

Explosive Performance of AI Models: As of April 2026, major models like Claude Opus 4.7, GPT-5.5, Gemini 3.1, and DeepSeek V4 have scored over 80% on SWE-bench Verified, dramatically enhancing system development capabilities.
Language Transition of Key Tools: Microsoft has rewritten its TypeScript compiler in Go, achieving speeds ten times faster than before. Anthropic’s AI agents have successfully created a Rust-based C compiler with 100,000 lines of code for just $20,000.
Transformation of the Python Ecosystem: Popular libraries like Pydantic and Polars are transitioning to Rust, prioritizing “execution speed” over “ease of writing,” with AI facilitating this shift.

💡 Key Points

AI and Rust’s Synergy: Rust’s strict compiler checks serve as a “free training signal” for AI, allowing models to self-correct in real time, making it easier for AI to generate code compared to C++.
Infrastructure Acquisitions: OpenAI has acquired Astral, which develops the Rust-based development tool “uv.” Anthropic has also acquired the high-speed runtime “Bun,” indicating that AI companies are beginning to directly control “fast infrastructure.”

🦈 Shark’s Eye (Curator’s Perspective)

The old belief that “Python is easy for humans to write” has been completely overturned by the rise of AI! While Rust and Go may be complex for humans, they provide an incredible “learning environment” for AI, where compilers directly teach models about errors. If AI can churn out code at lightning speed, humans should simply choose the fastest languages for execution! Python is increasingly becoming just a “stylish hat” to run a speedy Rust core. This reversal marks a significant turning point in the history of software engineering!

🚀 What’s Next?

In new projects, languages like Python and TypeScript, previously chosen for “development speed,” are likely to fade into the background, making way for Rust and Go as standard choices from the get-go. The trend of AI agents automatically replacing existing Python assets with Rust will accelerate, dramatically speeding up backends for web and apps!

💬 A Word from HaruShark

If AI can easily write complex languages, humans no longer need to stress over it! Let’s push forward in pursuit of ultimate speed! 🦈🔥

📚 Terminology

SWE-bench Verified: A reliable metric that measures how effectively AI models can solve real-world software problems.
System Languages: Languages that operate close to computer hardware (like Rust, Go, C++). They are known for their very fast execution speeds.
Compiler Feedback Loop: The process of checking for errors before executing code. AI can use these error messages as hints to immediately correct code.
Source: If AI writes your code, why use Python?