If AI writes your code, why use Python?
medium.com
May 11, 2026
8 min read
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45/100
Summary
The shift in software development priorities has moved from speed of deployment to performance efficiency. As AI tools increasingly write code, languages like Rust, Go, and C++ are gaining traction due to their superior performance, despite longer ramp-up times and smaller talent pools compared to Python and TypeScript.
Key Takeaways
- AI advancements have made it easier to write code in traditionally difficult languages like Rust, Go, and C++, shifting the performance calculus for software development.
- Major companies, such as Microsoft, are transitioning to faster programming languages like Go for critical projects, citing significant performance improvements and reduced engineering costs.
- A C compiler was developed in Rust using AI assistance, demonstrating that complex software projects can now be completed much faster and at a lower cost than before.
- The reliance on ecosystems for languages like Python and JavaScript is diminishing as AI tools enhance productivity in systems programming.
Community Sentiment
Positives
- Python's mature ecosystem for AI/ML provides quick turnaround and extensive training data, making it a preferred choice for many developers.
- Using AI tools with Python allows for rapid prototyping, as it enables developers to create throwaway versions quickly, enhancing the development process.
- The simplicity and readability of Go, combined with AI assistance, leads to efficient coding and deployment, showcasing the potential of AI in streamlining development.
Concerns
- Reliance on Python and other dynamically typed languages raises concerns about code correctness, as AI-generated code may introduce subtle bugs that are hard to detect.
- The lack of strict typing in languages like Python can lead to confidence issues when AI writes code, as it may break functionality in specific production scenarios.
