AI Coding

In the AI Era, Choosing a Programming Language Is Harder — Go, Rust, Python, or TypeScript?

Honghao Wang

— 3 min read
In the AI Era, Choosing a Programming Language Is Harder — Go, Rust, Python, or TypeScript?

2025-10-18 — Zhejiang

Programming Languages in the AI-Assisted Coding Era

In today’s world, AI-assisted coding is becoming the new normal. This shift makes the choice of programming language more important than ever.

image
image
image

---

Armin Ronacher’s Perspective: Trade-offs, AI, and Language Choice

Armin Ronacher, author of Flask and entrepreneur, emphasizes that in the AI era:

  • Programming language choice carries complex trade-offs that must be reassessed.
  • The chosen language directly impacts AI-generated code quality.
  • Go fits AI-driven scenarios better — its low abstraction, clear structure, and ease of modification suit AI agents.

From his experiments:

  • Go had higher pass rates from AI-generated code than Python and Rust.
  • Python remains unavoidable for ML and data processing.
  • JavaScript (and thus TypeScript) is equally unavoidable in certain contexts.

Armin foresees next-generation languages tailored for human–AI co-programming becoming a major trend.

Key Takeaways

  • Human energy drives teams; AI cannot replace passion or emotion.
  • Languages encode deep design trade-offs.
  • Unified codebases are not sacred — clear boundaries can be beneficial.
  • Now is the window to invent more perfect languages for human–AI collaboration.
  • Reject “996 culture” — overwork leads to predictable burnout and health crises.

---

1. Language Histories & Comparisons

Python 2 → Python 3 Migration

  • Goal: unify string handling by moving all to Unicode.
  • Reality: far more complex than designers expected.
  • Lesson learned: migrations require pragmatism and coexistence — Python 2 lived alongside Python 3 for over a decade.

Rust later adopted an edition system to let new features coexist with old versions, inspired by Python’s experience.

---

Comparing Python, Rust, Go

Armin’s “Two Personas”:

  • Crafting refined open-source software → Rust is excellent but slow and strict.
  • Building products in startups → Go offers stability, simplicity, and speed.

Rust’s friction points:

  • Slow compilation.
  • Verbose code & heavy type reasoning.
  • Strict borrow checker — great safety but inflexible design constraints.

Go’s advantages:

  • Pragmatic and stable.
  • Easy to maintain.
  • Supported by a strong community.

---

Language Ecosystems

  • Python: mature in automation & ML; suitable for AI inference-heavy workloads.
  • Go: better for high-concurrency services; simpler than Python.
  • Rust: ideal for binary data handling, databases, and high-security modules.
  • TypeScript/JavaScript: essential in browser; backend use hampered by npm’s dependency volume.

---

2. Language Choice in the AI Era

Armin’s Startup with “AI Interns”:

  • 80% AI-generated code; humans focus on creative logic.
  • AI accelerates builds (e.g., visualization tools in minutes instead of weeks).
  • AI assists in debugging and generating reproduction cases.

He concluded:

  • Language matters for AI code quality — Go outperforms Python and Rust in agent pass rates.
  • Potential exists for a new language optimized for human–AI collaboration.

---

Error Handling & Language Design

Armin’s Insights:

  • Different languages crash differently; scope of error impact varies.
  • Type systems reduce known low-level errors but don’t eliminate complexity-driven failures.
  • Observability should be native to languages; context propagation is critical but can conflict with performance.

---

Advice for Startup Engineers

Be ready for chaos:

  • Roles change often.
  • Clear boundaries and processes may not exist early on.
  • Knowing your goals helps navigate uncertainty.

---

Personal Preferences

  • Favorite Language: Python — pragmatic and productive despite flaws.
  • Favorite Tool: A high-quality cordless electric screwdriver — empowers more creativity and willingness to build.

---

Inspirations & Work Philosophy

  • Avoid “996” work slavery — reward should align with equity and personal well-being.
  • Passion + practicality beats perfection obsession in product development.
  • Right tools (whether coding or content creation) open new possibilities.

---

---

---

Event: Geek Time 8th Anniversary — 100% Win Rate

🎁 Prizes include:

  • VIP memberships
  • AI practice handbook
  • AirPods
  • Cash rewards
image

Read the Original Article | Open in WeChat

---

Bottom line: In the AI age, language pragmatism, clear design trade-offs, and human oversight remain critical for building maintainable and innovative systems — whether in coding or AI-powered content creation.

Read more