AI-assisted development is all the rage nowadays. I'm sceptical, but really want to give these tools a fair shot. But then I look at what these tools actually manage to do, and am disillusioned: these tools can be worse than useless, making us net-negative productive.

Let's pick one of the best possible examples of AI-generated code changes. An example so good, that the Cursor Editor uses it to advertise on their front page.

Tox is a neat tool for helping test Python projects. It automatically creates “virtual environments” that include the necessary dependencies, and can then run user-defined tools for testing. Multiple environments can be created in a declarative manner to test different combinations of Python versions + dependencies. Tox will also build packages in an isolated environment.

This has been an absolutely fantastic tool in its 15 years of existence. But since then, tooling in the Python ecosystem has moved on, and doing it the Tox way will probably slow you down.

You can get 90% of the value of Tox by wrapping Poetry or uv, and will end up with simpler, faster, and more flexible QA tooling. My preferred way to do that is to define tasks with Just, which enables something quite close to the npm run style development experience.