The AI Productivity Gap
This article examines the 'AI productivity gap,' noting that while AI speeds up coding, it does not significantly reduce the time senior engineers spend on non-coding tasks like planning and requirements review. It argues that the productivity boost is more pronounced for junior developers than for seniors.
Why it matters
It challenges the corporate narrative that AI allows companies to replace senior talent with junior developers, highlighting the complexity of engineering workflows.
There’s no doubt that AI has already improved the productivity of engineering teams, and will only get better in the coming years. However, some leaders think fully-baked features should be banged out as fast as prototypes. Sadly, building production features still seems to take almost as long as it used to. Wasn’t AI supposed to turn us all into hyper-productive 10xers?
To understand this AI productivity gap, we need to acknowledge how developers actually break down their days. In reality, coding new features is not where most of their time goes. Senior engineers in particular spend a lot of time figuring out what code they need to write, and AI hasn’t yet made that part any easier.
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