The 10x productivity number is (as you say) only for specific tasks - and even for core tasks, anything that can be sped up by a factor of 10 is unlikely to be more than 50% of the job—and probably much less. This is because pretty much nobody does the core thing they do more than about 70% of the time. And 10% time savings across ten tasks does not add up to 100% saving.
But I think you underestimate how useful “vibecoding” has become for many people with agent tools. So, instead you’re getting expansion and not replacement. People with existing codebases are getting small productivity increases, people who could barely code are going things they would never even attempt. And those tools are new—months to weeks, so they will take a while to show up in our lived lives. And they may never show up in existing software because the code is too complex and getting it into a feature takes too much effort. The bottle neck is not the ability of programmers to produce the code but the coordination of getting multiple code changes into productoin. This is not just AI. Any start up going from MVP to product seems to be shipping features daily but eventually this slows down as the software gets bigger.
Two thoughts.
The 10x productivity number is (as you say) only for specific tasks - and even for core tasks, anything that can be sped up by a factor of 10 is unlikely to be more than 50% of the job—and probably much less. This is because pretty much nobody does the core thing they do more than about 70% of the time. And 10% time savings across ten tasks does not add up to 100% saving.
But I think you underestimate how useful “vibecoding” has become for many people with agent tools. So, instead you’re getting expansion and not replacement. People with existing codebases are getting small productivity increases, people who could barely code are going things they would never even attempt. And those tools are new—months to weeks, so they will take a while to show up in our lived lives. And they may never show up in existing software because the code is too complex and getting it into a feature takes too much effort. The bottle neck is not the ability of programmers to produce the code but the coordination of getting multiple code changes into productoin. This is not just AI. Any start up going from MVP to product seems to be shipping features daily but eventually this slows down as the software gets bigger.