1. Find the code you want to change

2. Run the tests to confirm that test coverage is good for the starting point

3. Track down everywhere else that might call or interact with that code

4. Update the tests (red/green TDD)

5. Alter the code

6. Update the things that call the code

7. Run the tests again

8. Apply linters/formatters

9. Address any feedback from linters

10. Check to see if any documentation needs updating and do that

11. Land a commit with a descriptive commit message

I can get all of that done with a coding agent with a single sentence prompt - especially if it's already in a session where it knows that I do "red/green TDD".

... and then I can work on something else while the agent is churning through those steps.

Mature workflows for those kinds of tasks have been mostly ubiquitous across professional-grade engineering tools like those from JetBrains or Visual Studio itself for longee than many people here have even been working in the trade.

It's clearly not the case for simonw, but much of what many people task AI tools to do foe them are only a novelty for the "VS Code"-type users who stubbornly refused to explore more professional-grade paid tools in the past.

Yet for many tasks, those mature paid tools provided reliable and efficient features that make the AI approach look like an expensive, slow, and dangerously nondeterministic regression.