Comment by siliconc0w
3 hours ago
Good for them to design and publish this - I doubt you'd see anything like this from the other labs.
The loss of competency seems pretty obvious but it's good to have data. What is also interesting to me is that the AI assisted group accomplished the task a bit faster but it wasn't statistically significant. Which seems to align with other findings that AI can make you 'feel' like you're working faster but that perception isn't always matched by the reality. So you're trading learning and eroding competency for a productivity boost which isn't always there.
I wish they had attempted to measure product management skill.
My hypothesis is that the AI users gained less in coding skill, but improved in spec/requirement writing skills.
But there’s no data, so it’s just my speculation. Intuitively, I think AI is shifting entry level programmers to focus on expressing requirements clearly, which may not be all that bad of a thing.
> I wish they had attempted to measure product management skill.
We're definitely getting better at writing specs. The issue is the labor bottleneck is competent senior engineers, not juniors, not PMs, not box-and-arrow staff engineers.
> I think AI is shifting entry level programmers to focus on expressing requirements clearly
This is what the TDD advocates were saying years ago.
What AI development has done for my team is the following:
Dramatically improved Jira usage -- better, more descriptive tickets with actionable user stories and clearly expressed requirements. Dramatically improved github PRs. Dramatically improved test coverage. Dramatically improved documentation, not just in code but in comments.
Basically all _for free_, while at the same time probably doubling or tripling our pace at closing issues, including some issues in our backlog that had lingered for months because they were annoying and nobody felt like working on them, but were easy for claude to knock out.