Where We Are in the AI Cycle

0:00People are still trying to figure out how everything works. What I love about the vibe writing concept actually is it's a place in which full autonomy can be fulfilled today. You're prompting, although it's English -like, it turns out you're just programming. And you're just programming in prompt. 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 we need PMs. It was extreme in 1990 and it's extreme today. Where are we really in the AI computing shift? Is this the Windows 3 .1 moment or more like the 64K IBM PC?

0:38In this episode, part of our this week in consumer series, I'm joined by A16D General Partner, Anisha Charia and board member Steven Sinovsky, former Microsoft president in one of the most influential product thinkers in tech to unpack where we are in the AI platform cycle and what's coming next. We dig into the framework shaping this moment, partial autonomy, jagged intelligence, vibe coding versus vibrating, what builders are wrong about agents, what Google's I .O signals about platform strategy, and why the future might be less about killer apps and more about control sliders. We begin by discussing this week's talk from Andre Carpathi on why software is changing again.

1:15Let's get into it. As a reminder, the content here is for informational purposes only. should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the company's discussed in this podcast. For more details, including a link to our investments, please see A16Z .com forward slash disclosures.

1:48And niche, Steven, we were having such a good conversation offline that I wanted to get this on the podcast. There are a few topics we wanted to discuss. First, we were all fascinated by Andre Carpathy's talk at startup school. Steven, what did you find so interesting? Where were your takeaways or reactions from it? Well, I totally love the talk. He did an unbelievable, like a philosopher king version of where we are. And I just found his metaphors really compelling. In fact, what I might do is even take it further back and just say, since he used an analogy of where we are in computing, I'm talking about the Windows 3 era and stuff like that.

2:27And having lived through all of them, I tend to think we're at the 64K IBM PC era of the micro computer. And the reason I think that 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 64K of memory and our programs are all too big and we have no display in all these problems. And with AI, people are like, it's going to replace search, it's going to replace Excel, and it's going to replace all these things, but it doesn't add very well.

3:08It gives you a lot of errors. Like the thing that you say it's going to 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. You know, the thing that struck me the most was he talked a lot about our relationship with this new tool. You know, in a sense, we want to use it in the same way that we've used all the other computing tools and technologies we've used in the past. But you really talked about this kind of inversion of the relationship of LLMs as people, spirits, the fact that they have jagged intelligence.

3:43So 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. I think tools is a super interesting point because the talk is anchored in tools, but the world itself is anchored in tools and the early stages of a platform are always about tools. And so you kind of get a little confused like right now. Now of course, he was talking about vibe coding, clearly because he pioneered the term and invented the concept and is living it. And it's very interesting is I actually think 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 kind of work and come along.

4:23But I really think that the most interesting thing for me what's being underestimated in the near term is sort of vibe writing. I mean, it seems weird to say anything with AI is underestimated because Lord knows that's not what we are. But the thing is is that vibe writing is so here. Like if you're in college, you're already vibe writing. And businesses are still working through the, well, can we use this doesn't seem appropriate. And that's a thing I've definitely lived through with word processors, you know, I had to get permission from the dean in college to use a computer to write papers.

4:57but 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 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 of the tool. Like I have a power drill. So I do not know how to use like one of those omniscient drill things, you know, and the world moves up the stack. And so that's where we are and it's just super exciting. What I love about the vibe writing concept actually is it's a place in which full autonomy can be fulfilled today.

5:31So 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 going to define a lot of the text to code stuff for the next two years. Well, I push back a little bit on that because of course I agree on the coding side. And I think one of the things developers do early in a platform is they love to tell you that they're doing something every day And it's working, but 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 they're actually not and they spent 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 if you have a job and your salary depends on you submitting that or you're a student and you're a grade depends on you It's actually better be right and you can't just say look I broke this and here you go And I think people don't get confused when it comes to like math like everybody knows You have to go check to the math if you ask it 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 vibrating 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 Azillian other problems that are going to happen from vibe coding In essence, we've seen this already, right?

7:08We 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. We should also give him credit. Many people have talked about this, but he did a fantastic job using the Iron Man analogy of how we're going to have autonomy, partial autonomy, and a slider to control what you want. I actually think that's a fantastic analogy and a way of thinking that gives you a very clear picture from the movies.

7:41But at the same time, people are very, very aggressive on their timeline of agents. and there's a very, very long history in trying to automate things that turn out to be very, very difficult to automate. And he did a fantastic job. He said, people are talking about like the year of agents. Yeah, that's a good consultant phrase. 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. It's an interesting point. I think a lot about agents has applied to financial services. And I think there's a set of problems and financial services that are high friction load judgment.

8:20So for example, when I want to go refinance my personal loan, I don't really feel attached to any 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 Stephen, how much risk do you want to take on your taxes? is how many things you want to report or not report. That requires an enormous amount of judgment, and of course it also is high friction.

8:48So when I think of the two by two of where is automation going to come first, I think a lot about high friction load judgment. I want to build that because I actually think it's super important to also consider that for anyone to offer the alternatives to the market, there has to be an ability to differentiate, to explain. And so you end up with this kind of thing where I just want the cheapest flight. And of course, for 20 years, all of the flight searches and stuff is worked on the cheap stuff. But it turns out that's not actually what you want. That's right. Plus, a lot of people want to intervene in presenting your choices to you.

9:21And so this idea that all choice in life is going to be reduced to some headless API. Right. I don't understand. People have to go build that and make a living building those things. So to your example of refinancing a home, like the only reason that it can exist as a search problem today is because the different people who want to refinance you can target you with an ad and attract you as a customer and differentiate themselves on that offering. And if you can't do that, then your ability to actually automate that task isn't going to exist because there's no economic incentive to just be, hi, I'm the headless, faceless, nameless, low -priced mortgage leader.

9:59It's not really a business. There's nothing there. Just headless, faceless, nameless food isn't a thing. It doesn't show up in a white can labeled food. And then you consume it and you're, okay, oh good, I have food now. Well, maybe so, Ellen. But yes, in the future, the dystopian future of repo, man, that's where we end up, but that's not gonna happen. I want the cheapest flight as long as it's not on spared airlines. Right, I want the cheapest flight, but I'm traveling with a family of three. I don't wanna leave it 5 a .m. No, Red Eye. Yeah, like I want miles on this airline. Yes. A lot of things don't add up to that.

10:31This 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 Amazon knows they complain about the choice, but they really don't want just phone case to show up as the thing because it was $6. I think this is a real throughline through the talk, which is partial autonomy, jagged intelligence, Carpathy 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. And he does a great job very much as this philosopher that I love, his delivery, his tone.

11:08Don't just go read the summaries. Don't read a post. Go just watch the video immersively. Well, I want to get to automation and employment particularly on the entry level side. But first I want to ask the broader question of there was this idea of AI plus human, I think it was chess could beat AI for some period of time. And that was kind of the co -pilot view of the world. The human plus AI will have a better product. And then it turned out, I think it was chess, maybe it was Goik or maybe it was both, that actually that was a temporary thing and AI is just better. And then there's the question as to how much of the world is like chess, where human plus AI is only better for a certain period of time and then the models get better or how much the world is like something else.

11:48We're always gonna want that human plus AI is just better or we're just always gonna want humans to do it. 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 demands where you don't have a formal definition of correctness or where a ton of human judgment is necessary and human choice and serve a human direction, we're just 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.

12:19We're back to the early stages of 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 want to automate this or I'm going to reduce your job to a tiny shell script kind of mentality. And I just look at the world as everything 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 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.

12:59He 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. And so fast forward, first I've spent 25 years with a doctor, but that's a different, but if there was a story this week about radiologists. And so very early, actually, if you go to ImageNet, that everybody was immediately radiology is doomed. Oh, like you never need to get a skin cancer biopsy, you'll just take pictures of your mole and it will just tell you. And then you find out, wow, there's judgment there.

13:34And there's even judgment in doing the biop in how to do the biopsy and then what to biopsy and all this. But it turns out the radiologists have like fully embraced AI. But they embraced it no different than they embraced the latest MRI technology. You're the latest software update from GE for a CAT scan. Like, I just think there are so many things like that. And so many jobs are either very, very uncertain, or most of the job is basically exception handling. And people like, oh, we're going to automate our taxes. Okay, taxes are literally a giant cascading if and switch statements of exceptions.

14:14And so the idea that you will just automate that. that, well, you have to know the answer to all the exceptions. And if you're going to prompt it with the answer to all the exceptions, then you're doing your taxes manually. But sort of like 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 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. So if maybe I could just buy that software and then type it in.

14:46And I said that and he's like, well, you're welcome to, but you will go to jail. And he explains, 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 feel anything on that form and stuff like that. Automation is extremely difficult. And it's exception bound, it's judgment bound, and it's all uncertain. I feel in which this question comes up a ton of product management. I've had so many conversations with product managers of the last two years about the death of product management, it's the end of the field, why we need PMs.

15:20And I think 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 a 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 and 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.

15:50Yeah, I think that really gets to the vibe coding challenge we're dealing with, which is like how fast can we go text to app? And I think here, what's so interesting in the long arc of platform transitions is that we're also having this platform transition happen not just out on the open. 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 Coverley Community Center down the street, or in magazines, or in newsletters, and then with news groups, then the internet, and so on. The whole internet was all I .C .Q, and it was all in the open.

16:24But now it's like happening on CNN, on the nightly news. Everyone knows about the platform transition that's happening in particular on social in Discord. And so what's happening is you're getting a lot of like vibe coding for Cloud. And so you're getting a lot of this, I had an idea. I prompted it and it worked and here I am. At some point I just go, I'm calling DS on that. That's like not a thing and then I sound like an old person and because some people think I am, I don't, but some people think I am. I don't either. It looks like, hey, you're just being old. Yes. But then you dig in and you find out like, wow, you're prompting, although it's English -like, it turns out you're just programming.

17:06Yes. And you're just programming in prompts. Yes. And people are like, oh, this is what we're gonna do we're just going to get the model to require a little bit more structure. And I'm like, you're writing a new programming language. Yes. And this path of text app and vibe coding is just developing a new language, which is super cool. Yes. Lord knows the world is built on programming languages in the 80s. If you drove slowly past the computer science department trying to get a PhD, they would just invent a new programming language right then and there. If you stood outside the building for too short of time.

17:37But we can't lose sight of the fact that the arc of programming has been one of basically over -promise and under -deliver. When I was in college, like the theory was, the market was going to need so many programmers that the whole employment force, the whole workforce would just be software people. And that never happened. And now here we are, we're not going to need any. They're all just going to go away. And I think it was extreme in 1990 and it's extreme today. And I think that the big thing is this over promising at each transition, even just most recently, low code. You even says that word anymore.

18:11Like we're not allowed to even mention it. And it's because 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 a domain spin or a branding logo or something, we see this with Wix and with website templates like it's possible. But you're not going to run a company on any of those. I totally agree where I disagree actually is I think that 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 of these products today, 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.

18:52In 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 in the metaphor is improving dramatically. I think we'll get there at least make more progress than we think. Versus a traditional programming language like object oriented, it didn't feel like it 100x the number of programmers or one 100th the amount of time to ship something to production. We just got new tools and sort of new problems to solve. Well, of course, you're benefiting from hindsight. Yes. And that's a key thing. First, I agree.

19:22We're in an exponential improvement cycle. with the models. So any predictive power goes out the window. And anyone who says, like something negative, you're gonna be the next person who says the internet is gonna be a vaccine -fat, like a vaccine sheet. 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 making predictions because you see how foolish people look for a long time. But take something like object -oriented. I mean, this thing was hyped to the moon. This is a wave of programming languages, just to give you an idea, again, how the speed things move.

19:59They started in 1980. And by 1990, they finally reached peak hype. So it was like 10 years of incremental improvement. And by then, they were also over. Like any programmer would have kind of said, it's sort of just changing the old programming paradigms of abstraction and polymorphism and stuff like that. But meanwhile, the magazines, which was the key measure of success at the time, There was one magazine that had a picture of a baby of diapers, not a picture of drawing, on the programming. How programming will get made easy? I remember seeing it at the newsstand and I was working on the C++ compiler at the time.

20:36C++ was a brand new language in 1990 and it didn't work yet. And here was a baby who was gonna make programming possible for other babies at baby care or something. And whether it was that or all the database programming languages like Delphi or Power Builder, 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 order magnitude. Order magnitude. And what I believe is with writing right now, it's changing order of magnitude. And so 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 not really accurate already.

21:20It's very much like auto correct. Like auto correct, fixed all the common typos, like TEH to THG in English, and just replaced them with these wild new auto corrects that just replaced what you typed with a word that has no meaning in the context of the sentence, which is what we face on phones all the time. So what we're going to see is a whole different set of errors in business writing or academic writing in schools that just replace other errors that have always creeped in. Totally. I remember small talk was the hot language, right? Well, small talk was the start of it. And it was called small talk 80.

21:52Yes. And then it really didn't ever achieve any momentum outside of Palo Alto. But then C++ came along. Yes. And there were 50 languages in the middle that people don't talk about. Like objective C being one of them that was the iPhone language, which was really one Steve Jobs. There was object Pascal and Pascal Pascal with the relational database attached. But this was my master's degree. Then I quit grad school. I could go on about this one for far too long. I'm so I'll just stop now. Do you think there will be best -selling novels that are entirely AI generator, nearly entirely in the next few years?

22:23100%. I don't think Stephen King is gonna do that, 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. Absolutely. And the copyright suit that follows from training models and stuff, that's a different issue. I think there's two things on this actually that are really interesting. So one is these language models are these averaging machines. And with art, you almost definitely don't want the average of all the novels or all the writing or all the authors.

22:58You 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 going to see artists that are native in the technology. Instead, we're seeing a lot out there what's called the slap 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?

23:31Without going all to shop on what is art? I mean, bad sitcoms are part of society too, but 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 slob. Yeah, I mean, this is why, and look, I've written a lot of business writing, so I can say this confidently about what I've written and what gets written, but 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. I'm telling you, GPT generates a better enterprise case studies faster than the typical marketing associate does at a company in like one million to effort.

24:16Yes. And does the content need to exist? It actually does. It's just an important part of the selling process. Yes. And so at the extreme, like with something like medical diagnosis, 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 80 % of the world has no access to anything. So wherever you think of medical LLM is, as in the SlopScale, most people don't have access to anything average. So we have to just make sure that the whole debate does not center around like what is Francis Ford Coppola using as the book and who are the actors and who is the cinematographer because that corporate case study, well they often go and interview the person and film it.