To succeed with AI-assisted coding, the author suggests setting realistic expectations, making code quality a key performance indicator, conducting continuous code inspections, emphasizing the importance of understanding code over merely writing it, and allocating time for ongoing learning. The author stresses the need to keep skilled humans in the loop and to focus on code quality and continuous learning to navigate this new frontier effectively.
Key takeaways:
- AI-assisted coding has the potential to increase developer productivity, but it's still in its early stages and needs to be adopted with caution.
- While AI can speed up coding, it's important to remember that understanding existing code is a critical part of a developer's job. AI-assisted coding could potentially complicate this process.
- AI-assisted coding can be error-prone, and the code it generates needs to be inspected and understood by human developers. This means that code quality and familiarity are key considerations.
- To succeed with AI-assisted coding, organizations need to set realistic expectations, make code quality a key performance indicator, conduct continuous code inspections, and allocate time for ongoing learning.