I think of the current generation of AI coding tools as being like a developer with a little bit of experience in almost any tech stack and field of application.

If I’m investigating a new field or trying out a new language or library, relative to my own experience, then it’s quite common for an AI code generator to use idioms or libraries I hadn’t yet come across. That alone sometimes saves me a useful amount of time doing research.

However, it’s almost all breadth and very little depth. The quality of the generated code is rarely better than something a junior-to-mid-level developer might have written. It needs to be reviewed and corrected with similar diligence.

Similarly, the quality of a generated review of existing code or of generated supporting assets like test cases or documentation is often superficial and error-prone. I rarely find it an overall win to use current AI-based tools for these things instead of existing tools that can’t do as much but are consistent and reliable at what they do do.

So I wouldn’t necessarily expect current AI tools to help me code better, only sometimes a bit faster, and that mostly in new areas I’m exploring rather than areas where I’m doing professional work that is going to get shipped in the near future.