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The minute you automate the most mundane thing and think you have it all squared away, whole new things appear — productivity drives new scenarios.

Sinofsky explains that productivity gains from automation don't shrink the long tail of work — they create new scenarios and analysis layers that didn't previously exist. ✦ AI generated

Steven Sinofsky · a16z Podcast · 2026-07-07 · original ↗

starts at this moment · 37:07

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it sounds like you're both saying that automating the long tail is still kind of the hardest thing about about all of this. Is is that true or would you say that there are other hard things uh that that developers and founders also need to think about?

the minute that you can get something easier with automation and you can actually automate it, which I do think is happening right now with agents and with with language models, well then we're going to dream up a whole bunch of new stuff to do. Like I I just mentioned this this loop that Amazon must be in on customer service. Well, they got rid of all the phone people... they've fixed that level of productivity, but now there's this backend that's just out there constantly figuring out how to have it not happen again. And that now they need a new level of analysis, a new set of tools. And the long tail got no shorter. It just got longer in a different way.

verbatim transcript · starts at 37:07

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37:07models, well then we're going to dream up a whole bunch of new stuff to do. Like I I just mentioned this this loop that Amazon must be in on customer service. Well, they got rid of all the phone people and the phone experience that would be miserable to do a return and the the challenge response and the fighting and like, can I return this and do I have to package it up or will you

37:28just ignore like toothpaste? They don't want it back. Like that's an a pioneering invention by Amazon is like, you know, if somebody gets the wrong consumable, we just don't want it. Like they're poisoning it, they used part of it, it's cheaper to just have them throw it away. Well, that never happened before. Like, you used to have to actually bring spoiled food to the supermarket and show it to them. And so,

37:50they've fixed that level of productivity, but now there's this backend that's just out there constantly figuring out how to have it not happen again. And that now they need a new level of analysis, a new set of tools. And the long tail got no shorter. It just got longer in a different way. >> Yes. And and I I think people forget that that's how innovation is this

38:12constant reinvention and it's it's a growing pie, not a static pie. And and all the negativity around AI comes from just thinking that the work to be done is this fixed thing that takes n people and m amount of software and we're just going to replace n people with m plus five and then we don't we're done. There's no jobs anymore. There's just an agent running. And that's just never

38:38going to happen. Like legal is a great example of this, like where people do contracts and they think that the law is going to help contracts get get done quicker without lawyers. Except I can assure you contracts will get longer and more sophisticated and encompass way more sets of scenarios than a person ever could. And that's going to create a whole >> more litigation around it. And that

39:00creates a whole ecos. Look, there's the the now apocryphal, semi-apocalypical famous example of radiology, which is a correlation, not a causation, but radiologists all love AI, and now we are having a radiology shortage. It it's not it's there's a lot of reasons. It's complicated, but it it it it just shows that the innovation wasn't static and and the market for the demand wasn't static. And and so I think

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