Apparently "AI is speeding up the onboarding process", they say. But isn't that because the onboarding process is about learning, and by having an AI regurgitate the answers you can complete the process without learning anything, which might speed it up but completely defeats the purpose?
I think there's definite scope for that being true; not because you can start doing stuff before you understand it (you can), but because you can ask questions of a codebase your unfamiliar with to learn about it faster.
id guess the time til forst being able to make useful changes has dropped to near zero, but the time to get mastery of the code base has gone towards infinity.
is that mastery still useful as time goes on though? its always felt a bit like its unhealthy for code to have people with mastery on it. its a sign of a bad bus factor. every effort ive ever seen around code quality and documentation improvement has been to make that code mastery and full understanding irrelevant.
Correct. Reading code is important. The details are in the minutia, and the way code works is that the minutia are important.
Summarizing this with AI makes you lose that context.
Yes, that's how I'd interpret it, too.
According to the article, onboarding speed is measured as “time to the 10th Pull Request (PR).”
As we have seen on public GitHub projects, LLMs have made it really easy to submit a large number of low-effort pull requests without having any understanding of a project.
Obviously, such a kind of higher onboarding speed is not necessarily good for an organization.