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Podcast

Where We Are in the AI Cycle

The a16z Show

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  • AI Platform Is in Early Stage
    • We are at an early AI platform stage comparable to the 64K IBM PC era, not yet at Windows 3.1 level.
    • User and developer understanding of AI tooling and its bounds is still evolving, shaping future progress. Transcript: Erik Torenberg Stephen, what did you find so interesting? What were your takeaways or reactions from it? Steven Sinofsky The 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 like where we are in computing, I’m 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 64K IBM PC era of the microcomputer. 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 and 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. It 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. Anish Acharya 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, and 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 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 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, of course, he was talking about vibe coding, clearly, because he pioneered the term, invented the concept and is living it. And it’s very interesting because 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 going to make their tooling kind of work and come along. But 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. I had to get permission from the dean in college to use a computer to write papers. 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 like, well, you’re not going to 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 a tool. Like I have a power drill, so I do not know how to use like one of those Amish 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. Anish Acharya 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 going to define a lot of the text to code stuff for the next two years. Well, (Time 0:02:00)
  • Vibe Writing Beats Vibe Coding
    • Vibe writing with AI is already practical and impactful, unlike vibe coding which faces strict constraints.
    • Full autonomy in writing can be achieved today but requires human editorial oversight for accuracy. Transcript: Anish Acharya 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. Steven Sinofsky Well, I’d 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 your grade depends on you submitting that, it actually better be right. And you can’t just say, look, Vibe wrote 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 going to 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 going to happen from Vibe coding. In a sense, we’ve seen this already, right? We saw a bunch of lawsuits that (Time 0:05:38)
  • Human Judgment Limits Automation
    • Domains with formal correctness like chess progress from no autonomy to full autonomy in AI.
    • Areas requiring high human judgment, such as taxes, demand human involvement despite automation efforts. Transcript: Anish Acharya 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 serve a human direction, 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. Steven Sinofsky We’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. 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. 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, 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. And there’s even judgment in doing the biop and 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 or the latest software update from GE for a CAT scan. 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. Right. And like people like, oh, we’re going to automate our taxes. Okay. Taxes are literally a giant cascading if and switch statements of exceptions. 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 going to prompt it with the answer to all the exceptions, then you’re doing your taxes manually. It’s 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 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. 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 fill anything in on that form and stuff like that. (Time 0:11:53)
  • Product Managers Handle Ambiguity
    • Product management persists because its core job is handling ambiguity in complex business and human systems.
    • Conversations about PM roles dying reflect a developer generation’s resentment but overlook the importance of judgment. Transcript: Anish Acharya 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 we need PMs. And 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 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 and companies is these complex adaptive systems where there will always be ambiguity. (Time 0:15:10)
  • Prompting Is New Programming Language
    • Prompting AI is akin to programming in a new language called prompt engineering.
    • Over-promising and under-delivering on AI coding tools reflects historical platform transition patterns. Transcript: Steven Sinofsky 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 Cumberley Community Center down the Street or in magazines or newsletters and then with news groups and the internet and so on. 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. 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 clout. 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 BS 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. Yes. And you’re just programming in prompts. Yes. And people are like, oh, this is what we’re going to do is 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. And this path of text to app and Vybe coding is just developing a new language, which is super cool. 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 a time. But 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. Who even says that word anymore? Like we’re not allowed to even mention it. (Time 0:15:54)
  • AI-Novels by New Writers Expected
    • AI will produce best-selling novels, likely by new writers using prompts as seeds, edited by humans.
    • Language models average data, but great art requires pushing toward the cultural edge rather than the average. Transcript: Steven Sinofsky A hundred percent. I don’t think Stephen King is going to 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. Anish Acharya 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. 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 any new tools. And we’re going to see artists that are native in the technology. Instead, what we’re seeing a lot 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 Without going all de champa 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. (Time 0:22:23)
  • AI Ups Access, Lowers Quality Bar
    • Most business writing today is mediocre, and AI-generated ‘slop’ writing often exceeds typical quality.
    • AI can elevate access to services and content for the majority who currently lack it, shifting quality expectations. Transcript: Steven Sinofsky 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 slop scale, 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. Well, like, all of a sudden, we see it today. Those things are done over Zoom. Yes. So suddenly, flying in or getting a satellite and booking, we’ve changed our view of excellent because we wanted more access. And I think that’s absolutely going to happen. Should you get graded on slop in school? That’s a different problem. But most stuff is pretty average. (Time 0:24:22)
  • Big Tech Must Transform To Win
    • Big companies like Google can muster vast resources to pivot in AI but must change product-building mindsets.
    • The critical challenge is not tech release but transforming development and go-to-market strategies to survive disruption. Transcript: Anish Acharya Just hearing your take on I.O. And if you felt like a Google I.O. Oh, yeah, yeah. So essentially, 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 I.O. What do you think that says for Google about Google? Steven Sinofsky Do you think the sort of demise of Google is overstated? Well, of course, I think the demise of Google is an absurd proposition. The demise of a giant company is a crazy thing to say. Driving in, I was listening on CNBC, some investor or whatever talking their book, talking about IBM is the one to buy. I almost wanted to pull over to the side of the road and think, what universe am I in where this company that has died like nine times in my career? And so death of is just such a done thing. Losing a position of influence, however, is a very real thing. In these platform transitions, big companies have an enormous asset, which is the shock and awe asset. And so they have the ability to tell the story called we’re pivoting our whole company around this and we’re a zillion dollar in whole 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 that matters. And that’s what you could do. Someone was asking me on Twitter yesterday about this event Microsoft held in 2000 called Forum 2000. And it was when we announced like a whole bunch of internet stuff and the early cloud stuff. It wasn’t called cloud, but early cloud stuff. And nobody in that room understood what we were talking about. Not a person, but they all left like, oh my God, there is so much stuff here, which was a repeat of five years earlier when we did what was called Strategy Day. And like the headlines were literally Sleeping Giant awoke. And so it was totally predictable that Google would show up with like literally the B2 bombers of software. 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 Because that’s really what undermines the big technology companies. And so with Microsoft, the interesting thing was all those products that got announced over that five-year span or 10-year span, none of them are around today. I should be very careful every time I say something like this, I get assaulted. But like the big announcement at Forum 2000 was the.NET framework in C Sharp, which by almost any measure, one would call a legacy platform today. So it like came and went in six or seven years. And everything was about virtual machines and clustering and all this stuff that VMware was doing. And that’s not where anything was. And on top of all that, the economic model became SaaS. And so what I’m looking at with Google is not, can they present all the technologies in the context of Google search and ads, but can they transform the way they think to something new? (Time 0:26:40)