Summary

Wes McKinney reflects on how coding agents are changing which programming languages are most productive. While Python excels at human ergonomics—readability, simplicity, and a vast ecosystem—agentic engineering favors languages like Go and Rust that offer fast compile-test cycles, easy distribution, and static binaries. He argues that human ergonomics in programming languages matters much less now that agents do most of the coding, though Python will remain essential for data science and ML due to ecosystem inertia. The durable value in the stack increasingly resides in compute kernels and data access layers, not the language bindings on top.

Key Insight

As coding agents become the primary authors of code, the human ergonomics that made Python dominant matter far less than the compile-test speed and distribution simplicity that favor Go and Rust.

Spicy Quotes (click to share)

• 7

  Human ergonomics in programming languages matters much less now.

• 8

  Dragging around a Python interpreter has started to feel like the Java Virtual Machine from which we tried so desperately to unburden ourselves.

• 6

  The reasons that Python has gotten so popular are that it is productive and pleasant for humans to write and use. As the hours and days pass by, this benefit feels increasingly moot compared with the evident downsides.

• 4

  Quicker iterations translate to net improved productivity even factoring in the 'overhead' of generating code in a more verbose or more syntactically complex language.

• 3

  Agents have made these languages much more accessible beyond their prior core user base of heavy duty systems engineering.

• 5

  Most of the long term value clearly resides in the first two layers (compute and data access), not the last two.

• 2

  I'm working harder and having more fun building than I have in years.

Tone

reflective, pragmatic, forward-looking