Former Microsoft Executive Explains Where We Are in the AI Cycle w/ Anish Acharya & Steven Sinofsky

Steven Sinofsky 0:00 We're at the sixty-four K IBM PC era of the microcomputer. People are still trying to figure out how everything works.

Anish Acharya 0:08 We have to relearn how to use this type of tool before we know how to be productive with it.

Steven Sinofsky 0:12 Vibe writing is absolutely a thing.

Anish Acharya 0:15 It's a place in which full autonomy can be fulfilled today.

Steven Sinofsky 0:18 We've changed our view of excellent because we wanted more access.

Anish Acharya 0:22 Is the bar for success what people can do today, or is the bar for success just something that's better than the alternative? Of course, this is dramatically better.

Erik Torenberg 0:35 Anish, Steven, we were having such a good conversation offline that I wanted to, to, to get this on the podcast. There are a few c- uh, topics we wanted to, to discuss. First, we were all fascinated by Andrej Karpathy's talk at, at, at Startup School. Steven, what did you find so interesting or what were your takeaways or, or reactions from it?

Steven Sinofsky 0:53 Well, I totally love the, the talk. He did an unbelievable... Like, a philosopher king version of, of where we are, and I just found his, his metaphors really compelling. In fact, what, what I might do is even take it further back and just say, since he used an analogy of, like, where we are in computing, and lots of people are talking about the Windows 3 era and stuff like that, and having lived through all of them, I tend to think we're at the sixty-four K IBM PC era of the microcomputer. And the reason I think that is, is, is actually a technical one, which is that we're at the point where people are still trying to figure out how everything works, and all the coding and all of the energy is working around, like, these very basic working problems. Like, with the PC, it was like, okay, we have sixty-four K of memory, and our programs are all too big, and we have no display, and all these problems. And with AI, you know, people are like, "It's gonna replace Search, it's gonna replace Excel, and it's gonna replace all these things," but it, it doesn't add very well. It gives you a lot of errors. Like, the thing that you say it's gonna do, it just doesn't even do yet. So I feel like we're at a point that is just so, so early, and he did a fantastic job of sort of making that arc.

Anish Acharya 2:17 You know, the thing that struck me the most was he talked a lot about our relationship with this new tool. You know, and in a sense, we, we wanna use it, like, in the same way that we've used all the other computing tools and technologies we've used in the past. But he really talked about this kind of inversion of the relationship of LLMs as people spirits, the fact that they have jagged intelligence. So to me, that sort of meta point he made was one of the most interesting. We have to relearn how to use this type of tool before we know how to be productive with it.

Steven Sinofsky 2:45 A- and I, I think tools is a super interesting point because it... the talk is anchored in tools, but the world is, itself is anchored in tools, and the early stages of a platform are always about tools. And, and so you kinda could get, get a little confused. Like right now, of course, for- he was talking about vibe coding, clearly 'cause he, he pioneered the term, invented the concept, and is living it. And it, it's very interesting 'cause I actually think, um, coding is one domain that always works best early in a platform because, well, all the customers of the platform are developers, and they're gonna make their tooling kinda work and, and come along. But, but I really

Steven Sinofsky 3:23 think that the most interesting thing for me, what's being underestimated in the near term is sort of vibe writing. And I j- and I, I mean, it seems weird to say anything with AI is underestimated 'cause-

Anish Acharya 3:34 [laughs]

Steven Sinofsky 3:34 ... Lord knows that's not where we are.

Anish Acharya 3:36 Mm-hmm.

Steven Sinofsky 3:36 But the thing is is that vibe writing is, is so here. Like, if you're in college, you're already vibe writing, and, you know, businesses are still working through the, "Well, can we use this? This doesn't seem appropriate." And that's a thing I've definitely lived through with word processors, with the micro- I, you know... I had to get permission from the dean in college to use a computer to write papers. And so, so, but this vibe writing is absolutely a thing, and it is really, really no different than when calculators showed up and all of a sudden just doing math homework involved using a calculator. And people were like, "Well, you're not gonna know how to do math in the future." And it's like, "I won't have to know how to do math." That's, like, the whole point-

Anish Acharya 4:17 [laughs]

Steven Sinofsky 4:17 ... of a tool. Like, I have a power drill, so I do not know how to use, like, one of those Amish drill things.

Anish Acharya 4:23 [laughs]

Steven Sinofsky 4:23 Like, I, you know, and the world moves up the stack. And so that's where we are, and it's just super exciting.

Anish Acharya 4:29 What I love about the vibe writing concept actually is it's a place in which full autonomy can be fulfilled today. So you can ask the model to vibe write something, you know, really detailed and compelling, and it'll do a great job. Whereas with vibe coding, I think there's a ton of constraints as to what the model can actually do versus what it can conceptually do, and understanding those boundaries and constraints is gonna define a lot of the text to code stuff for the next two years.

Steven Sinofsky 4:54 Well, I'd push back a, a little bit on that because I, of course, I agree on the coding side-

Anish Acharya 4:58 Yeah

Steven Sinofsky 4:58 ... and I think there's a lot of develop- One of the things developers do early in a platform is they, they love to tell you that they're doing something every day and it's working, but it, it actually just isn't, and that's just what happens early in a platform. They tell you all these things that they say are easy, and-

Anish Acharya 5:14 [laughs]

Steven Sinofsky 5:14 ... they're actually not, and they, they spent 86, 18 hours struggling with something that didn't work. But on the vibe writing side, it also hits a point that I just think is so, so important which is, yeah, you can prompt it to spew out a bunch of stuff, but, like, if you have a job and your salary depends on you submitting that or you're a student and your grade depends on you submitting that, it, it actually better be right, and you can't just, like, say, "Look, I vibe wrote this, and here you go." And, and, and I think people don't get confused when it comes to, like, math. Like, everybody knows you have to go check the math if you ask it-

Anish Acharya 5:49 Mm-hmm

Steven Sinofsky 5:49 ... to do a table and then add a column that does math. But we're gonna just see endless, endless human wasn't in the loop vibe writing things, and it's just that with programs you can't really see that right away because in order to actually distribute it or get someone to use it, you have to at least fix the initial bugs.We'll only see them later when there are security bugs, authentication bugs, passwords stored in plain text, or a zillion other problems that are gonna happen from vibe coding.

Anish Acharya 6:17 I mean, in w- in a sense, we've seen this already, right? We saw a bunch of lawsuits that were citing case precedent from cases that don't exist. So maybe this is actually the operative point, which is there's full autonomy, there's partial autonomy. Maybe partial autonomy in writing is moving us from writer to editor, but you still have to be the editor.

Steven Sinofsky 6:33 Yeah. We should also give him credit. I mean, he... Many people have talked about this, but he did a fantastic job using the Iron Man analogy of, of how we're gonna have, you know, a s- a, a autonomy, partial autonomy, and a slider to control what you want. I actually think that's a fantastic a- analogy and a way of thinking it that gives you a very clear picture from the movies if y- you live through the movies. And but it... at the same time, it, it's still, uh, people are very, very aggressive on their timeline of agents.

Anish Acharya 7:04 Yes.

Steven Sinofsky 7:04 And there's a very, very long history in trying to automate things that turn out to be very, very difficult to automate. And so I, I think that one, it, he... And he did a fantastic job. He, he said, "People are talking about, like, the year of agents." Yeah, that's a good consultant phrase. We're a, just like he said, we're in the decade of agents, and it's gonna take a decade for things to be anywhere near living up to agentification as a meme.

Anish Acharya 7:31 You know, it, it's an interesting point.

Anish Acharya 7:33 I think a lot about agents as applied to financial services, and I think there's a set of problems in financial services that are high friction, low judgment. So for example, when I wanna go refinance my personal loan, I don't really feel attached to any sp- specific brand of a personal loan provider. I just want the cheapest rate. So it's actually a very low judgment decision. But going and researching and applying for a personal loan is a high friction process. That's something I would love to delegate to an agent. I think it can do a nice job. Whereas doing my taxes, wow, like, Steven, how much risk do you wanna take on your taxes? How many things do you wanna report or not report? That requires an enormous amount of judgment, and of course, it also is high friction. So when I think of the two by two of where is automation gonna come first, I think a lot about high friction, low judgment.

Steven Sinofsky 8:16 I, I wanna build on that 'cause I, I actually think it's super important to also consider that for anyone to offer the alternatives to, to the market, there has to be an ability to differentiate, to explain. And, and so you end up with this kinda thing where, like, I just want the cheapest flight. And of course, for 20 years, all the flight ch- searches and stuff has worked on the cheap... But it turns out that's not actually what you want.

Anish Acharya 8:40 That's right. [laughs]

Steven Sinofsky 8:40 Plus, a lot of people wanna intervene in presenting your choices to you.

Anish Acharya 8:45 Yes.

Steven Sinofsky 8:45 And so I don't... Like, this idea that all choice in life is gonna be reduced to some headless API-

Anish Acharya 8:52 Right

Steven Sinofsky 8:52 ... I don't understand. People have to go build that and make a living building those things. So to your, to your example of, like, refinancing a home-

Anish Acharya 9:00 Yes

Steven Sinofsky 9:00 ... like, the only reason that it, it can exist as a search problem today-

Anish Acharya 9:04 Yeah

Steven Sinofsky 9:04 ... is because the different people who wanna refinance you can target you with an ad and attract you as a customer and differentiate themselves on that offering.

Anish Acharya 9:13 Right.

Steven Sinofsky 9:13 And if you can't do that, then your ability to actually automate that task isn't gonna exist 'cause there's no economic incentive to just be, "Hi, I'm the headless, faceless, nameless, low price mortgage leader."

Anish Acharya 9:26 That's right. [laughs]

Steven Sinofsky 9:26 It's not really a business.

Anish Acharya 9:27 That's right.

Steven Sinofsky 9:28 Like, there's no, nothing there. Just like, you know, headless, faceless, nameless food isn't a thing. It doesn't show up in a white can labeled food.

Anish Acharya 9:36 [laughs]

Steven Sinofsky 9:37 And then you consume it, and you're, "Okay, all good. I have food now."

Anish Acharya 9:40 Well, maybe Soylent, but yes. [laughs]

Steven Sinofsky 9:42 Now, in the future, in the dystopian future of Repo Man, that's where we end up. But that's not gonna happen.

Anish Acharya 9:46 I want the cheapest flight as long as it's not on Spirit Airlines.

Steven Sinofsky 9:49 Right. I want the cheapest flight, but I'm traveling with a family of three. I don't wanna leave at 5:00 AM.

Anish Acharya 9:53 No red-eye. [laughs]

Steven Sinofsky 9:54 I... Yeah, like, it's just, I want miles on this airline.

Anish Acharya 9:57 Yes. Yes. Yes.

Steven Sinofsky 9:57 You know? A lot of things don't add up to that. And I, I have a s- this is a real thing in business. It's a thing on the producer and the consumer side. Consumers really, really want much more choice than they often think they do, and anyone who's bought anything on Amazon knows they complain about the choice, but they really don't want just, you know, like, phone case to show up as the thing 'cause it was $6.

Anish Acharya 10:21 I think this is a real through line t- through the talk, um, you know, which is partial autonomy, jagged intelligence. Karpathy is just talking a ton about the constraints of the technology, which I think is the right thing for us to be thinking through trade-offs around as builders.

Steven Sinofsky 10:36 And he does a great job, very much as this philosopher that I love. His delivery, his tone, e- he really, really... Don't just go read the summaries. Don't read a post. Go just watch the video-

Anish Acharya 10:47 Mm-hmm

Steven Sinofsky 10:47 ... immersively.

Anish Acharya 10:48 Totally. Well, I wanna get to automation and, and sort of employment, um, particularly on the, on the entry-level side. But, but first I want, just wanna ask the broader question of, you know, there was this idea of, you know, like, AI plus human, uh, at... So I think it, I think it was chess could beat AI at, for some period of time, and that was kinda the co-pilot view of the world, that human plus AI will, will be, will be, have a better product. And then it turned out, I think it was chess, maybe it was Go, or maybe it was both, that actually, that was, that was a temporary thing, and AIs are just, just better. And so then there's the, the question as to how much of the world is like chess, where, um, where a human plus AI is only better for a certain period of time, and then the sort of the models get, get better, or, or how much, uh, you know, the world is, is like something else that is always, we're always gonna want that human plus AI is just better, or we're just always gonna want humans to hu- humans to do it.

Steven Sinofsky 11:39 Look, my view is that in a domain in which you have a formal definition of correctness, the path will be no autonomy, partial autonomy, full autonomy. In domains where you don't have a formal definition of correctness or where a ton of human judgment is necessary and human choice and sort of human direction, we're just w- w- the right product design is not to go all the way to full autonomy. I would argue that chess and Go do have a formal definition for correctness, so it makes sense that those were fully automated over time. We're back to the early stages of, of where, where things are, which means that a bunch of programmers are sort of defining what success looks like. And programmers are very good at either works or it doesn't work, or I just wanna automate this, or I'm going to reduce your job to a tiny shell script kind of mentality. And, and I just look at the world asEverything is gray, and everything is much harder than it looks when you don't actually have to do it. Ages and ages ago, I visited a really giant hospital in Minnesota to, to help them figure out how to use Excel within the medical profession. And the doctor just looked at me and he's like, "I don't think you understand." And he, he, he, he was like, "My job is all uncertain. Every aspect of what I do is uncertain. So adding something that pretends to be certain, like a spreadsheet, to my uncertainty doesn't actually help me."

Anish Acharya 13:04 Mm-hmm.

Steven Sinofsky 13:04 And so fast-forward, first I've spent 25 years as a doctor, but that's a different... But-

Anish Acharya 13:09 [laughs]

Steven Sinofsky 13:09 But if, there was a story this week about radiologists. And so very early in, in... Actually, if you go to ImageNet, everybody was immediately, "Radiology is doomed."

Anish Acharya 13:18 Mm-hmm.

Steven Sinofsky 13:18 Like, there was, "Oh," like, "you never need to get a skin cancer biopsy. You'll just take pictures of your, of your mole, and it will just tell you..." And then you find out, wow, there's judgment there, and there's even judgment in doing the biops- in how to do the biopsy, and then what to biopsy, and all this. And so the... But it turns out the radiologists have, like, fully embraced AI.

Anish Acharya 13:38 Uh-huh.

Steven Sinofsky 13:38 But they embraced it as no different than they embraced the latest MRI technology or the latest software update from GE for a CT scan.

Anish Acharya 13:47 Mm-hmm.

Steven Sinofsky 13:48 And I, like, I just think there are so many things like that, and, and s- so many jobs are either very, very uncertain, or most of the job is, is basically exception handling.

Anish Acharya 14:01 Right.

Steven Sinofsky 14:01 And-

Anish Acharya 14:02 Right

Steven Sinofsky 14:02 ... and, like, like, people are like, "Oh, we're gonna automate our taxes." Okay, taxes are literally a giant cascading if and switch statements of exceptions.

Anish Acharya 14:10 Yes.

Steven Sinofsky 14:11 And, and so the idea that you will just automate that, well, you have to know the answer to all the exceptions, and if you're gonna prompt it with the answer to all the exceptions, then you're doing your taxes manually. So, like, [laughs] it's a very strange... I mean, you know, it's sort of like everybody, once you reach a certain income, you have to get help from an accountant to do your taxes, and the first thing the accountant does is ask you for your tax planner. And, uh, as a software person, I look at him like, "The tax planner really, really looks like the input fields of the software you're using."

Anish Acharya 14:43 [laughs]

Steven Sinofsky 14:43 "So if maybe I could just buy that software and then type it in." And I said that, and he's like, "Well, you're welcome to, but you will go to jail."

Anish Acharya 14:51 [laughs]

Steven Sinofsky 14:52 And he explains, like, because every time I give him a number is a whole decision about where to apply it, does it work? And I'm like, "Well, you're not really a farmer, so don't fill anything in on that form," and stuff like that. So it's... People get... It, automation is extremely difficult, and it's ex- it's exception bound, it's judgment bound, and it's all uncertain.

Anish Acharya 15:13 You know, a field in which this question comes up a ton is product management. I've had so many conversations with product managers over the last two years about the death of product management, it's the end of the field, why do we need PMs? And I think, you know, our sort of developer generation has developed a real resentment towards product managers, which is a different conversation. With that said, I think that the product management job is the job of addressing ambiguity, and it's ambiguity that prevents progress from being made. Sometimes it's execution, decision-making, product design. That will not change. The nature of business and human interaction in companies is these complex adaptive systems where there will always be ambiguity. I think you'll always need judgment, and you'll always need somebody who looks like a product manager.

Steven Sinofsky 15:55 Yeah, I think that really gets to the sort of the vibe coding sort of challenge we're dealing with, which is, like, how fast can we go text to app? Uh, and I think, you know, here what's so interesting in, in the long arc of platform transitions is that we're also having this platform transition happen not just on the, on, out in the open. We, you know, we've had that before, like back when in the earliest days of computing, these platform transitions happened in user group meetings, like at the Cubberley Community Center down the street-

Anish Acharya 16:24 Mm-hmm

Steven Sinofsky 16:24 ... or in magazines or in newsletters, and then with news groups, then the internet, and so on. You know, the whole internet was all ICQ, and it was all in the open. But now it's, like, happening on CNN, on the nightly news. You're, you know, everyone knows about the platform transition that, that's happening, in particular on social and on, in Discord. And so what's happening is you're getting a lot of, like, vibe coding for clout.

Anish Acharya 16:48 Mm-hmm.

Steven Sinofsky 16:48 And so you're getting a lot of this, like, "I had an idea, I prompted it, and it worked, and here I am."

Anish Acharya 16:55 [laughs]

Steven Sinofsky 16:56 "And, and, and I..." You know, at some point, I just go, like, "I, I'm calling BS on that. That's, like, not a thing." And then I sound like an old person-

Anish Acharya 17:02 [laughs]

Steven Sinofsky 17:02 ... and because some people think I am, it... I don't, but some people think I am.

Anish Acharya 17:06 I don't either.

Steven Sinofsky 17:07 You know, it looks like, hey, you know, you're just being old.

Anish Acharya 17:11 Yes.

Steven Sinofsky 17:11 But then you, you dig in and you find out, like, wow, you're prompting. Although it's English-like, it turns out you're just programming.

Anish Acharya 17:21 Yes.

Steven Sinofsky 17:21 And you're just programming in prompts.

Anish Acharya 17:23 Yes.

Steven Sinofsky 17:23 And people are like, "Oh, this is... What we're gonna do is we're just gonna get the model to require a little bit more structure." And I'm like, "You're writing a new programming language."

Anish Acharya 17:32 Yes.

Steven Sinofsky 17:32 And we're just... Like, this path of text app and vibe coding is just developing a new language, which is super cool.

Anish Acharya 17:39 Yes.

Steven Sinofsky 17:40 Like, Lord knows, like, the world is built on programming languages. In the '80s, if you drove slowly past a computer science department trying to get a PhD, they would just invent a new programming language right then and there-

Anish Acharya 17:51 [laughs]

Steven Sinofsky 17:51 ... if you stood outside the building for too short a time.

Steven Sinofsky 17:54 But we, we can't lose sight of the fact that the arc of programming has been one of, of basically overpromise and underdeliver. You know, when I was in college, like, the theory was the market was gonna need so many programmers that the whole employment force would be, the whole workforce would just be software people.

Anish Acharya 18:12 Mm-hmm.

Steven Sinofsky 18:12 And, and that never happened. And now here we are, we're not gonna need any. They're all just gonna go away. And I think it was extreme in 1990, and it's extreme today.

Anish Acharya 18:21 Yes.

Steven Sinofsky 18:22 And, and I think that the, the, the big thing is this overpromising at each transition. You know, even just most recently, low code.Who, like, who does any- who even says that word anymore? Like, it's a... Like, we're not allowed to even mention it. And it's because, like, it's always the same thing, which is, yes, if all you're doing is a very straightforward app that looks like all the other straightforward apps, but with, like, a domain spin-

Anish Acharya 18:46 Mm-hmm

Steven Sinofsky 18:46 ... or a branding logo-

Anish Acharya 18:46 Mm-hmm

Steven Sinofsky 18:46 ... or something, you know, we see this with, with Wix and with website templates.

Anish Acharya 18:50 Mm-hmm.

Steven Sinofsky 18:51 Like, it's possible. But you're not gonna run a company on any of those.

Anish Acharya 18:56 I totally agree. Where I disagree, actually, is I think that the, the language, the language model in this case, but the language in your metaphor is improving at a dramatic rate underneath these things. So while I think almost all these products today, they sort of... They're good at prototyping, they're trying to push into refinement. They're not really usable as things that you can actually deploy to production at all. In fact, most of the cool demos you see on Twitter don't work three days later. So they're very much in the prototyping phase, but the programming language and the metaphor is improving dramatically. I think we'll, we'll get there, or at least make more progress than we think, uh, versus a traditional programming language like object-oriented that didn't feel like it 100x the number of programmers or 1/100 the amount of time to ship something to production. We just got, you know, new tools, uh, and, and sort of new problems to solve.

Steven Sinofsky 19:44 Well, of course, you- you're benefiting from hindsight.

Anish Acharya 19:47 Yes. Yes.

Steven Sinofsky 19:47 And that's a key, a key thing. First, I obvio- I agree. Like, y- we're in an exponential improvement cycle-

Anish Acharya 19:55 Yes

Steven Sinofsky 19:55 ... with the models.

Anish Acharya 19:56 Yes.

Steven Sinofsky 19:56 So any predictive power goes out the window.

Anish Acharya 19:58 Correct.

Steven Sinofsky 19:59 And anyone who says, like, something negative is just gonna be, like-

Anish Acharya 20:03 [laughs]

Steven Sinofsky 20:03 ... you're gonna be the next person who says the internet is gonna be-

Anish Acharya 20:05 Fax machine

Steven Sinofsky 20:05 ... a passing fad like a fax machine.

Anish Acharya 20:07 [laughs]

Steven Sinofsky 20:07 And that's a bad... You just don't wanna be there. And it turns out also, that's a case where having lived through them, you get very shy about, like, making predictions because you see how foolish people look for a long time.

Anish Acharya 20:19 [laughs]

Steven Sinofsky 20:19 But, like, like, take something like object-oriented. I mean, this thing was hyped to the moon-

Anish Acharya 20:25 Mm-hmm

Steven Sinofsky 20:25 ... for how to, how to solve... This is a wave of programming languages. Just to give you an idea, again, how time, how the speed of things move. They started in 1980, and by 1990, they finally reached, like, peak hype.

Anish Acharya 20:39 Right.

Steven Sinofsky 20:39 So it was like 10 years of incremental improvement, and by then they were also over. Like, any programmer would've kind of said, "Eh, it's not really... It's sort of just changing the old programming mo- model- paradigms of abstraction and polymorphism and stuff like that." But meanwhile, the, the magazines, which was the key measure of success at the time-

Anish Acharya 20:58 [laughs]

Steven Sinofsky 20:59 Like, like, there was one magazine that had a picture of a baby in diapers, not a picture, a drawing, on the cover, uh, programming, how programming will get made easy. A- and it was like, I'm go- And I'm like, I remember seeing it at the newsstand, and I was working on the C++ compiler at the time, which hadn't... C++ was a brand-new language in 1990, and, and it didn't work yet.

Anish Acharya 21:20 Right.

Steven Sinofsky 21:21 And here was a baby who was gonna make programming possible-

Anish Acharya 21:23 [laughs]

Steven Sinofsky 21:24 ... for other babies at, at baby care or something. And that, and whether it was v- you know, that or all the database programming languages like, um, Delphi or PowerBuilder, you know, these are all, in algorithmic sense, they were all constant improvement. Like, just they added a constant factor, like plus seven, onto programming. None of them changed the mathematical-

Anish Acharya 21:46 Order of magnitude, right

Steven Sinofsky 21:47 ... order of magnitude. And I think the... Like, what, what I believe is with writing right now, it's changing order of magnitude.

Anish Acharya 21:55 Right.

Steven Sinofsky 21:55 And so we're here... It's here. It's happening. Accuracy isn't there, but one of the things about writing is, like, actually when you read it, most of it in business is not really accurate already. So we're, w- It's very much like autocorrect. Like, autocorrect fixed all the common typos, like T-E-H to T-E-H in English, and just replaced them with these wild new autocorrects that just replaced what you typed with a word that has no meaning in the context of the sentence.

Anish Acharya 22:21 Yes.

Steven Sinofsky 22:22 Which is what we face on phones all the time. So what we're gonna see is a whole different set of errors in business writing or in academic writing in schools that just replace other errors that have always creeped in.

Anish Acharya 22:33 Totally. I remember Smalltalk was the hot language, right?

Steven Sinofsky 22:36 Well, Smalltalk was the start of it, and it was called-

Anish Acharya 22:37 Yes

Steven Sinofsky 22:37 ... Smalltalk 80.

Anish Acharya 22:39 Yes.

Steven Sinofsky 22:39 And then it, it really didn't ever achieve any momentum outside of Palo Alto.

Anish Acharya 22:43 Yes. [laughs]

Steven Sinofsky 22:44 But, but then, um, C++ came along.

Anish Acharya 22:47 Yes.

Steven Sinofsky 22:47 And there were 50 languages in the middle-

Anish Acharya 22:49 Yes

Steven Sinofsky 22:49 ... that people don't talk about.

Anish Acharya 22:50 Yes.

Steven Sinofsky 22:50 Like, Objective-C being one of them. That was the, the, the, the iPhone language-

Anish Acharya 22:54 Uh-huh

Steven Sinofsky 22:54 ... which was really one Steve Jobs-

Anish Acharya 22:55 Pascal.

Steven Sinofsky 22:56 Uh, d- There was Object Pascal and Pascal, Pascal with the relational database attached, but I, uh, this was my master's degree. Then I quit grad school. I could go on about this one for far too long, so I'll just stop

Steven Sinofsky 23:07 now.

Anish Acharya 23:07 Do you think there will be best-selling novels that are, you know, entirely AI-generated or nearly entirely g- in, in the next few years?

Steven Sinofsky 23:13 Abs- 100%. 100... And, and I think, I don't think Stephen King is gonna do that, and, but I think there'll be some new writer who will probably write it under a pseudonym, and a year after the novel is written and has been made into a movie, they'll say, "Oh, by the way, I got the plot idea from a prompt, and then I just started having writing, and I was editing it along the way." Uh, absolutely. And the copyright suit that follows from training models and stuff, that's a different issue.

Anish Acharya 23:39 [laughs] I, I think there's two things on this actually that are really interesting. So one is, you know, these language models are these averaging machines, and you don't... Uh, with art, you almost definitionally don't want the average of all the novels or all the writing or all the authors. You want something that's at the edge. So how do we actually point them in a direction such that they can be at the edge of culture, which I think is important for making great art? I think the other thing is a lot of the artists don't yet know how to use the new tools, and we're gonna see artists that are native in the technology. Instead, what we're seeing a lot, you know, out there, what's called the slop, has just been a lot of this low barrier to entry art that's being created, which is great because it gives people the sort of fulfillment of creative generation. I think what we're talking less about is, "Hey, how is the ceiling being raised for artists because they have access to these technologies?"

Steven Sinofsky 24:27 You know, without going all Duchamp on what is art-

Anish Acharya 24:30 Yes

Steven Sinofsky 24:30 ... I mean, you know, we all, like, b- bad sitcoms are part of society too, but I, I think it's important. We tend to focus on, like, the very, very best of things, but most everything isn't only the very best. In business writing-It's all slop.

Erik Torenberg 24:46 [laughs]

Anish Acharya 24:46 Yeah.

Steven Sinofsky 24:46 I mean, this is why-

Erik Torenberg 24:47 [laughs]

Steven Sinofsky 24:48 I-- look, I've written a lot of business writing, so I can say this confidently a-about what I've written and what gets written. But like, like take something completely mundane that a lot of people in Silicon Valley spend a lot of time working on, like the enterprise software case study.

Erik Torenberg 25:04 Mm-hmm.

Steven Sinofsky 25:05 Uh, like I'm telling you, GPT generates a better enterprise-

Erik Torenberg 25:10 [laughs]

Steven Sinofsky 25:10 ... case studies faster than the typical marketing associate does at a company in like one-millionth the effort. And it... Uh, do you need the... Does the content need to exist? It actually does. Like there... Like, it's just an important part of the selling process.

Anish Acharya 25:25 Yes.

Steven Sinofsky 25:25 And, and so we... Yeah, just like with, with so- at the extreme, like with something like medical diagnosis. The-- We, we tend to think about the most obscure diseases, the most difficult to understand problems with the finest hospitals with the most resources. But you have to remember, like eighty percent of the world has no access to anything.

Anish Acharya 25:47 Yes.

Steven Sinofsky 25:47 So, so whatever, wherever you think of medical LLM is as in the slop scale-

Anish Acharya 25:55 Yes

Steven Sinofsky 25:55 ... most people don't have access to anything average. So y-you have to... We, we, we have to just make sure that the whole debate does not center around, you know, like what is the Francis Ford Coppola using as the book, and who are-

Anish Acharya 26:11 Yes

Steven Sinofsky 26:11 ... the actors-

Anish Acharya 26:12 Yeah

Steven Sinofsky 26:12 ... and who is the cinematographer? 'Cause like, you know, 'cause that corporate case study, well, they often go and interview the person and film it. Well, like all of a sudden we see it today, those things are done over Zoom.

Anish Acharya 26:25 Yes.

Steven Sinofsky 26:25 So suddenly flying in with this... We're getting a satellite and booking a stu- We, we've changed our view of excellent because we wanted more access, and, and I think that that's absolutely gonna happen. Should you get graded on slop in school? That's a different problem. But m-most stuff is pretty average.

Anish Acharya 26:44 The world needs more slop, says Steven.

Steven Sinofsky 26:46 I, I, I feel like this isn't a press interview where you can put words in my mouth like that.

Erik Torenberg 26:50 [laughs]

Anish Acharya 26:50 The world needs more slop. That'll be the title. Well, so, so actually Mar-Mark makes this point, I think it's a really good one, you know, which is, is, is the bar, is the bar for success perfection? Is the bar for success what people can do today, or is the bar for success just something that's better than the alternative? And in your case of eighty percent of the world that has access to no medical knowledge, no medical services, no medical opinion, of course, this is dramatically better.

Steven Sinofsky 27:12 Yeah. I, I look at it like when I had to get permission to use a word processor in college, one of the stumbling blocks was that my printer was like a, a, a, an Epson MX80 dot matrix printer. Z-z-z. And, and, you know, it, it looked like, like a printer, like a computer printer, which like the, the r-rules for the papers were they had to be written on a typewriter.

Anish Acharya 27:35 Yes.

Steven Sinofsky 27:35 And so like... And then the Macintosh came out in the spring and only had an image writer, which is another dot matrix printer. So all of a sudden the, the standard changed because the value of being able to revise and edit and update and copy-paste and use fonts was just so much higher than the fidelity of the teacher reading it on, you know, bond paper with, with Courier. And that's gonna happen with content a-as well.

Anish Acharya 28:02 What I would love to talk to you about, Steven, is actually just hearing your take on IO.

Anish Acharya 28:06 There was a lot of conversation around Google and how Google had sort of fallen behind and lost their ability to make new things. They released a ton of new software at every part of the stack in IO. You know, what do you think that says for Google, about Google? Do you think the sort of demise of Google is overstated?

Steven Sinofsky 28:22 Well, of course, I think the demise of Google is an absurd proposition.

Anish Acharya 28:25 [laughs]

Steven Sinofsky 28:26 The demise of a giant company is, is a crazy thing to say. Um, they will... I mean, like I was just, uh, driving in, I was listening on CNBC, someone, some investor or whatever, talking their book, talking about, um, about IBM and is the one to buy. I, I almost wanted to pull over to the side of the road and think-

Anish Acharya 28:48 [laughs]

Steven Sinofsky 28:48 ... what, what universe am I in where, where this company that has died like nine times in my career?

Anish Acharya 28:55 Right.

Steven Sinofsky 28:56 And so death of is just such a dumb thing. Losing a position of influence, however, is a very real thing.

Anish Acharya 29:01 Mm-hmm.

Steven Sinofsky 29:02 In, in these platform transitions, big companies have an enormous asset, which is the, the shock and awe asset. And so they have the ability to j-- to, to tell the story called, "We're pivoting our whole company around this, and we're a zillion-dollar company, and here is like a full assault across the board for every single asset we have and every single category the world is talking about-

Anish Acharya 29:32 Mm-hmm

Steven Sinofsky 29:33 ... that matters." And that's what, that's what you could do. And so, uh, it was totally predictable that Google would show up with like literally the B2 bombers of, of software.

Anish Acharya 29:45 Mm-hmm.

Steven Sinofsky 29:46 But the question is really much deeper than that, and it's really will they alter their context of how they build products and their go-to-market? Because that's really what undermines the big technology companies. And so what I'm looking at with, with Google is not like can they present all the technologies in the context of Google search and ads-

Anish Acharya 30:10 Mm-hmm

Steven Sinofsky 30:10 ... but can they transform the way they think to something new? Because that's really where the disruption is gonna happen.

Anish Acharya 30:18 I love that point.

Erik Torenberg 30:19 Awesome. Uh, Anish, Steven, thanks so much for this week in, uh-

Steven Sinofsky 30:22 Sure thing.

Erik Torenberg 30:22 This Week in Consumer AI.

Steven Sinofsky 30:22 Thank you. Super fun. [outro music]