YouSaid · the spoken record

Bret Taylor

lines on the record: 154
first: 2025-04-15
most recent: 2025-04-15
sittings or episodes: 1
sources: podcast

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“With a distilled model and moving more to inference time, it changes the economics of it. You have data, you say, gosh, we're running out of textual data to train on. Well, now we can generate reasoning. We can do simulations. Oh, that's an interesting breakthrough. And then on the algorithm side, as I mentioned, just the idea of these reasoning models is really novel itself. And each of these at any given point, if you talk to an expert in one of them and I'm an expert in none of them, they will tell you the sort of current plateau that they can see on the horizon and there usually is one. I mean, you'll talk to different people about how long the scaling laws for something will continue and you'll get slightly different opinions, but no one thinks it's going to last forever.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“The biggest breakthrough was obviously the Transformers model. Attention is all you need, that paper from Google that sort of led to where we are now, but there's been a number of really important papers since then from the idea of chain of thought reasoning to what at OpenAI, what we did with the O1 model, which is to do some reinforcement learning on those chains of thought to really reach new levels of intelligence. And so I do think that I mentioned some anecdotes about some breakthroughs there because my view is that each one of them has their own problems, you know, compute. It's very capital intensive. And a lot of these models, the half-life of their value is pretty short because new ones come out so frequently. And so you wonder, can we afford? What's the business case for investing this CapEx? And then you have a breakthrough like, you know, 01 and you're like, gosh.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Really optimistic these models are generating net new ideas. And so it really affords the opportunity some of the data wall as well. So data is one thing. And I think both synthetic data and simulation are really interesting opportunities to grow there. Then you have compute. And this is something that's why there's so many data center investments. It's why NVIDIA as a company has grown so much. Probably the most interesting kind of breakthroughs there are these reasoning models where there's not quite such a formal separation between the training process and the inference process where you can spin more compute at the time of inference to generate more intelligence, which has really been a breakthrough in a variety of ways, I think is really interesting, but it shows you how you can.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I've used simulation as based on a set of principles like the laws of physics. So if you build a real world simulation for training a self-driving car, you're not just generating arbitrary data like the roads don't turn into loop-de-loops, you know, because that's not possible with physics. So by constraining a simulation with a set of real world constraints, the data has more efficacy. And so, and there's sort of a, it constrains the different permutations of data you can generate from it. So I think a little bit higher quality. But then along those lines, a lot of people wonder if you generate synthetic data, how much value can that add to a training process? Is it sort of regurgitating information already had? What's really interesting about reasoning and reasoning models is I think I feel”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I would say that synthetic data. The synthetic data has a Simulation and synthetic data are a little different. So you can generate synthetic data, like generate a novel. Simulation, I would put, at least in my head, and I'm sure that academics might critique what I'm saying, but”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“The scaling laws a couple years ago indicated the larger you make the model, the more intelligent it would be. And at a degree of efficiency that was tolerable. And we are, you know, there's lots of stuff written about this, but there's in terms of just textual content to train on the availability of new content is certainly waning. And some people would say, I think there's like a data wall. I'm not an expert in that domain, but it's been talked about a lot, and you can read a lot about it. There's a lot of interesting opportunities though to generate data too. So there's a lot of people working on simulation. If you think about a domain like self-driving cars simulation is a really interesting way to generate.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, what you said is roughly how I think about it. I'll put it into my own words though. Oh, please do. I think the three primary inputs are data, compute, and algorithms. And data is probably obvious, but one of the things after the transformers model was introduced is it afforded an architecture with just much greater parallelism, which meant models could be much bigger and train more quickly on much more data, which just led to a lot of the breakthroughs with, that's the L and LLM, just they're large.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Intelligent a system would be in discovering new therapies, it may not materially change that. And so you may have something that's discovering new insights in math, and that would be delightful and amazing. But the existence of that system that's super intelligent in one domain may not translate to all domains equally. I just heard at least a snippet of a talk by Tyler Cohen, the economist, and I was really interested to hear his framing on this about which parts of the economy could sort of absorb intelligence more quickly than others. And so I choose that definition of AGI, recognizing that there's not a perfect definition because it captures the ability of this intelligence to generalize while also recognizing that the domains of society, like it might not apply with”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“It is a bar that means, like, if there's a digital interface to that system, it affords the ability for AI to interact with it, which is why that's a bar that's reasonable to hit. I say that because one of the interesting questions around AGI is how quickly it does generalize. And there are domains in the world that the progress in that domain isn't necessarily limited by intelligence, but by other social artifacts. So as an example, and I'm not an expert in this area, but if you think about the pharmaceutical industry, my understanding is one of the main bottlenecks is clinical trials. So no matter how”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Than a person sort of trained in that domain. And I think that's sort of the at or better than a person is certainly a good standard there. And that's sort of the definition of superintelligence. The reason I mention at a computer is I do think that”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I think a reasonable definition of AGI might be that. Any task that a person can do at a computer, that system can do on par or better. I'm not sure that's a precise definition, but I'll tell you where that comes from and its flaws, but there's not a perfect definition of AGI, in my opinion, or there's not a precise definition of AGI. I'm sure there's good answers. One of the things about the G and AGI is about generalization. So can you have a system that is intelligent in domains that it wasn't explicitly trained to be intelligent on? And so I think that's one of the most important things is like given a net new domain, can this system become more competent and more intelligent?”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Small talk came out of the development of the graphical user interface at Xerox Park. And there was sort of a confluence of message passing as a metaphor and the graphical user interface. And then there was a lot of really interesting principles that came out of networking and sort of distributed systems, distributed locking, sequencing. I think we should recognize that we're in this brand new era as significant as the GUI. It's like a completely new era of software development. And if you were just to say, I'm going to design a programming system for this new world from first principles, what would it be? And I think when we develop it, I think it'll be really exciting because rather than automating and turning up the Control to the people who are orchestrating the system in a way that I think will really benefit software overall.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Thing that I'm trying to figure out is what is the system that a human operator is using to orchestrate all those tasks? And I go back to the history of software development and most of the really interesting metaphors in software development came from breakthroughs and computing. So the C programming language came from Unix. And when these time-sharing systems were really, it went from sort of punch cards to something that were a lot more agile.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“That's a great question. But actually, it's still funny to me that we'd be generating Python just because for anyone who's listening right now has ever operated a web service running Python, it's CPU end intensive, really inefficient. Should we be taking most of the unsafe C code that we've written and converting it to a safer system like Rust, if authoring these things and checking it are relatively free, shouldn't all of our programs be incredibly efficient? Should they all be formally verified? Should they all be analyzed by a great agent? I do think it can be turtles all the way down. You can use AI to solve most problems in AI.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Which is sort of where the world is going, it doesn't change the fact that who's accountable for the quality of it, who's fixing it? And I think there is a world where we can make reasonable software by just automating what we as software engineers do every day. But I have a strong suspicion that if we designed these systems with the role of a software engineer in mind being an operator of a machine rather than the author of the code, we could make the process much more robust and much more productive. And it feels like a research problem to me. It doesn't feel, and I think a lot of people for good reason, including me, are just excited about the efficiency of software development going up. And I want to see the new thing, though. I'm constructively dissatisfied with where we are.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“And then similarly, you know, there's things go in and out of fashion, but like test driven development, where you write your unit test first or your integration test first and then write code until it fulfills the test. Most programmers I know who are really good, not despise it, but it's just like a, it sounds better than it is in practice. But again, writing code is free. So writing tests is free. How can you create a programming system where the combination of great programming language design, formal verification, robust tests because you didn't have to do the tedious part of writing them all? Could you make something that made it possible to write increasingly complex systems that were increasingly robust? And then similarly, like the elephant in the room for me is the anchor tenant of most of these code generating systems are an IDE, right now, you know. That obviously doesn't seem as important in this world. And even with code.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Are there programming language designs that are designed so a human looking at it can very quickly evaluate, does this do what I intended it to do? There's an area of computer science I studied in college called formal verification, which at the time was turning a lot of computer programs into math proofs and finding inconsistencies and it sort of worked well, not as well as you'd hope. But in a world where AI is generating a lot of code, should we be investing more informal verification so that the operator of that code generating machine can more easily verify that it does in fact do what they intended us to do and could a combination of a programming language that is more structurally correct and structurally safe and exposes more primitives for verification plus a tool to verify could you make an operator of a code generating machine 20 times more productive but more importantly make the robustness of their output 20 times greater”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Or going towards free, what would be the programming systems that we would design? So, for example, Rust is an example of a programming language that was designed for safety, not for programming convenience. My understanding is that Mozilla project, there were so many security holes in Firefox, they said, let's make a programming language that's very fast, but everything can be checked statically, including memory safety. Well, it's a really interesting direction where you weren't optimizing for authorship convenience or optimizing for correctness.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“You've ever looked at someone else's code, which a lot of people do professionally. It's called the Code Review, it's actually quite hard to do a code review. You end up interpreting, you're trying to basically put the system in your head and simulate it as you're reading the code to find errors in it. So the irony now of taking things that are code programming languages that were designed for authors and now having humans do the job of essentially code reviewing code written by an AI and yet all of the AIs being in the code generation part of it, I'm like, I'm not sure it's great, but we're generating a lot of code with similar flaws so that we've been generating before from security holes to just functional bugs and in greater volumes. And I think what I would like to see is if you start with the premise that generating code is free.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“But it's notoriously not robust. Most Python bugs are found by running the program because there's not static type check-in. Similarly, there's most bugs while you could run a fancy static analysis. Like MOC's bugs show up simply at runtime because it's just not designed. It's designed to be ergonomic to write. Yet we're using AI to generate that. And so we've sort of designed most of our computer programming systems to make it easy for the author of code to type it quickly. And we're in a world where we're actually generating code is going to like the marginal cost of doing that is going to zero, but we're still generating code in programming languages that were designed for human authors. And similarly, if you”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“It feels like a local maximum in a really obvious way to me, which is you have a bunch of code written by people, written in programming languages that were designed to make it easy for people to tell a computer what to do. Probably this funniest example of this is Python. It almost looks like natural language.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I actually wrote a blog post right before Christmas about this. I think this is an area that deserves a lot more research. I'll describe where I think we are today, and smart people may disagree, but a lot of the modern large language models, both the traditional large language models and sort of the new reasoning models are trained on a lot of source code. And it's an important input to all of the knowledge that they're trained on. As a consequence, even the early models were very good at generating code. So every single engineer at CIRA uses cursor, which is a great product that basically integrates with”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“In a world where making software is easier than it ever is before and you're delivering outcomes for your customer, the delivery model of software probably should change as well. And we've really tried to reimagine what the software company of the future should look like and trying to model that in everything that we do.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Everything from, I'll say a couple examples in our business are pricing model is really unique and comes from first principles thinking rather than having our customers pay a license for the privilege of using our platform. We only charge our customers for the outcomes, meaning if the AI agent they've built for their customers solves the problem. There's like usually a pre-negotiated rate for that. And that comes from the principle that in the age of AI, software isn't just helping you be more productive, but actually completing a task. What is the right and logical business model for something that completes a task? Well, charging for a job well done rather than charging for the privileges using the software. Similarly, with a lot of our customers, we helped deliver them a fully working AI agent. We don't hand them a bunch of software and say, good luck, configure it yourself. And the logic there is, you know,”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“With modern large language models, one of the careers that is being most transformed is software engineering. And one of the things I think a lot about is how many software engineers will we have our company three years from now? What will the role of a software engineer be as we go from being authors of code to operators of code generating machines? What does that mean for the type of people we should recruit? And if I look at the actual craft of software engineering that we're doing right now, I think it's literally a fact that will be completely different to years from now. Yet I think a lot of people building companies hire for the problem in front of them rather than doing that. But two years is not that long. Those people that you hire now will just be getting really productive a couple years from now. So we try to think about most of our long-term business from first principles.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“And you have across so many domains in the enterprise really rapid transformation. The law is being transformed. Marketing is being transformed. Customer service, which is where my company, Sira Works, is being transformed. Software engineering is being transformed. And the amount of change in such a short period of time is, I think, unprecedented. And perhaps I lack the historical context, but it feels faster than anything I've experienced in my career. And so as a consequence, I think if you are responding to the facts in front of you and not thinking from first principles about why we're at this point and where it will probably be 12 months from now, the likelihood that you will make the right strategic decision is almost zero. So as an example, it's really interesting to me that”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, it's particularly important right now because the market of AI is changing so rapidly. So if you rewind two years, most people hadn't used ChatGPT yet. Most companies hadn't heard the phrase large language models or generative AI yet. And in two years, you have ChatGPT becoming one of the most popular consumer services in history faster than any service in history.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Which is driven in social media and very fast paced. Having a systematic first principles discussion about every tweet you do is probably not a great comm strategy. And so, and then similarly, there are some aspects of, say, enterprise software sales that aren't rational, but they're human. Forming personal relationships and the importance of those to building trust with a partner. It's not all just product and technology. And so I would say I think a lot of things coming with an engineer mindset could really benefit. But I do think that taking that to its like logical extreme can lead to analysis paralysis, can lead to over intellectualizing some things that are fundamentally human problems. Yeah, I think a lot can benefit from engineering, but I wouldn't say everything's an engineering problem in my experience.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“That's a deeper philosophical question that I think I have the capacity to answer. What is engineering? What I like about approaching problems as an engineer is first principles thinking and understanding the root causes of issues rather than simply addressing the symptoms of the problem. And I do think that coming from a background in engineering that is everything from process like how engineers do a root cause analysis of an outage on a server is a really great way to analyze why you lost a sales deal. You know, like I love the systematic approach of engineering. One thing that I think going back to good ideas that can become caricatures of themselves, like one thing I've seen though with engineers who go into other disciplines is sometimes you can overanalyze decisions in some domains. Let's just take modern communications.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Especially engineers, is you're not like the product manager for the company, you're the CEO. And at any given day, do you spend time recruiting an executive because you have a need? Do you spend time on sales? Engineers who are unwilling to elevate their identity from what they were to what it needs to be in the moment often leads to sort of plateaus in companies growth. So 100% I think engineers make great leaders and it's not a coincidence I think that most of the Silicon Valley great Silicon Valley CEOs came from engineering backgrounds. But I also don't think that's sufficient either as your company scales. And I think that making that transition as all the great ones have is incredibly important.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Businesses are multifaceted and rarely is a business's success due to one thing like engineering or product, which is where a lot of founders come from. Often your go-to-market model is important for consumer companies, how you engage with the world in public policy becomes extremely important. And I think as you see founders grow from doing one thing to growing to being a real meaningful company like Airbnb or Meta or something, you can see those founders really transform from being one thing to many things. So I do think engineers make great leaders. I think the first principles thinking, the system design thinking really benefits things like organization design, strategy. But I also think that when we were speaking earlier about identity, I think one of the main transitions founders need to make”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I do think engineers make good leaders, but one thing I've seen is that I think that I really believe that great CEOs and great founders start usually with one specialty but become More broadly, specialists in all parts of their business. You know, I think the”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Out, I could sort of see it all happening, which is like some people take them, be like, you know what? You're right. I need to go down and be in the details, and some people do it and probably make everyone who works from the miserable. And probably both will happen as a consequence.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“And most great companies are filled with extremely great individual contributors who make good decisions and work really hard. And companies that are solely executing through the judgment of individual probably aren't going to be able to scale to be truly great companies. So I have a very nuanced point because I actually believe in founders. I believe in actually that accountability that comes from the top. I believe in cultures where founders have license to go in and all the way to a small decision and fix it the infamous question mark emails from Jeff Bezos, you know, that type of thing. That's the right way to run a company. But that doesn't mean that you don't have a culture where individuals are accountable and empowered. And you don't want people trying to make business decisions because of what will please our dual leader, which is like the caricature of this. And so after that came.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“The issue I have not with Brian's statements, Brian's amazing is how people can sort of interpret that and sort of execute it as a caricature of what I think it means. I remember after Steve Jobs passed away and I don't know, I've met Steve a couple times. have I never worked with him in any meaningful way, but he was sort of, if you believe the story is like kind of pretty hard on his employees and very exacting. And I think a lot of founders were like mimicking that done to wearing a black turtleneck and yelling at their employees. I'm like, I'm not sure that was the cause. I think Steve Jobs' taste and judgment through executed through that packaging was the cause of their success. And somehow, and then similarly, I think founder mode can be weaponized as an excuse for just like overt micromanagement. And that probably won't lead to great outcomes.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“The founder mode, I have such a nuanced point of view on this because it is decidedly not simple. So broadly speaking, I really like the spirit of founder mode, which is just having Deep founder led accountability for every decision at your company. I think that that's how great companies operate. And when you proverbially make decisions by committee or you're more focused on process than outcomes, that produces all the experiences we hate as employees, as customers. That's the proverbial DMV, right? You know, it's like process over outcomes. And then similarly You look at the disruption in all industries right now because of AI, you know, the companies that will recognize where things are clearly going to change. Like everyone can see it. It's like a slow motion car wreck. Everyone knows how it ends. You need that kind of decisive breakthrough boundaries layers of management to actually make change as fast as required in business right now.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Amazon has gone through that transition. Microsoft has gone through that transition for that reason. But I love working with founders. I love working with people like Toby and Sam because they're so different than me. Yet, and I can see how they operate their businesses and I am inspired by it. I learned from it. And obviously working for Mark at Salesforce, you're like, wow, that's really interesting. I'm almost like an anthropologist. Why did you do that? I want to learn more. And so I love working with founders that inspire me because I just learned so much from them.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“There's exceptions like Satya, I think, is one of the greatest, if not the greatest CEO of our generation and as a professional manager, but you look at everyone from Toby Luke to Mark Bennioff to Mark Zuckerberg to Sam at OpenAI. And I think when you have founded a company, all your stakeholders, employees in particular, give you the benefit of the doubt. You created this thing, and if you say, hey, we need to do a major shift in our strategy, even hard things like layoffs, founders tend to get a lot of latitude and are judged, I think differently. And I think rightfully so. In some ways, because of the interconnection of their identity to the thing that they've created. And so I actually really believe in Founder-led companies. One of the real interests is going from a Founder-Led company to not.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Learning how to be an advisor is a very different vantage point that I think you see how other companies operate and you also learn how to have an impact and add value without doing it yourself. And it's very, and I've really, I think, become a better leader having learned to do that. I have really only joined boards that were led by founders because typically I think they you can speak to them, but I think they sought me out because I'm a founder and I like working with founder-led companies. I think the founders, I'm sure there's lots of studies on this, but I think founders drive better outcomes for companies. I think founders tend to have permission to make bolder more disruptive decisions about their business than a professor.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I really like being involved in a board. And I've been involved in multiple boards because I think I am an operator through and through. I probably self-identify as an engineer first more than anything.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Awkward waiting period there. And that's a time, I think, where the strategic decision makers in those moments can get together and say, let's talk through what this really means. And the nice part about having them for all parties is you've kind of made the commitment to each other. So I think you have more social permission to have real conversations at that point. But you also haven't consummated the relationship. There's the power imbalance isn't totally there. And you can really talk through it. And it also, I think, engenders trust, just because by having harder conversations in those moments, you're learning how to have real conversations and learning how each other works. So that's my personal opinion when having it.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“My personal take is it's not something you have, you have to get to the point where the two parties want to merge, you know, and that's obviously a financial decision, particularly if it's like a public company. There's a board and shareholders. Most acquisitions in the valley are a larger firm acquiring a private firm. That's not all of them, but I would say that's the vast majority. And in those cases, there's often a qualitative threshold where someone's like, yeah, let's do this. We kind of have the high level terms. Sometimes a term sheet, you know, formally, I think is right after that. So where people have really committed to the key things, how much value, why are we doing this, the big stuff. And there's usually lots of layers being paid lots of money to turn those termsheets into more complete set of documents, usually more complete due diligence, stuff like that.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“So that when you're approaching it, you not only get the hey, y is one plus one equal greater than two, everything's going to be awesome. But no, for real, like what does success look like here? And then as a founder, your job of an acquiring acquired company is to tell your team that and align your team to that. And I think founders don't take on enough accountability towards making these acquisitions successful as I think they should. And it goes back to, again, a certain naivete, you know, it's like you're not your company anymore. You're part of something larger. And I think, you know, successful ones work when everyone embraces that.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Down to brass talks about how things work and what's important. The other thing that I think is really important is being really clear what success looks like. And I think sometimes it's a business outcome. Sometimes it's a product goal. But I found that if you went to most of the larger acquisitions in the valley and you two weeks after it was closed interviewed the management team of the acquiring company and the acquired company and you asked them like what does success look like to years from now, my guess is like 80% of the time you get different answers. And I think it goes back to this sort of storytelling thing where you're talking about the benefits of the acquisition, talking about like what does success look like. So I really tried to approach it. I tried to pull forward some harder conversations when we're doing acquisitions or even when I'm being acquired since it's happened to me not twice.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I find that people, because there's sort of a craft of storytelling for both sides to come to the same conclusion that they should do this acquisition, sometimes either simplifies or sugarcoats like some of the realities of it, you know, little things like how much control will the founding team of the acquired company have over those decisions? Will it be operated as a standalone business unit or will your team be sort of broken up into functional groups within the larger company? And it's sort of those little, they're not little, but those, I'll say boring but important things that often people don't talk enough about. And you don't need to figure out every part of an acquisition to make it successful, but often you can end up running into like true third rails that you didn't find because you were having the storytelling discussions rather than”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“One greater than two. You know, that's why you do an acquisition just from first principles. It's often an exercise in storytelling. You bring this product together with our product and customers will find the hole greater than the sum of its parts. This team applied to our sales channel or your Google acquisition, imagine the traffic we can drive to this product experience. In the case of something like an Instagram, imagine our ad sales team attached to your amazing product and how quickly we can help you realize that value, whatever it might be.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“I'll talk abstract, I'll talk to you about some specific acquisitions too, but. First, I think I tried to approach it with more empathy and more realism. there's the period of doing the acquisition. There's sort of the period after you've decided to do it of doing due diligence. And then there's a period when it's done and you're integrating the company and sort of the period after. One of the things that I have observed is that companies doing acquisitions, often the part of deciding to do it is a bit of a mutual sales process. You're trying to find a fair value for the company and there's some back and forth there. But at the end of the day, there's usually some objective measure of that influenced by a lot of factors, but there's some fair value of that. But what you're trying to do is what are, and corporate speak would be synergies, but like, why do this? Why is one plus”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Before and having acquired some companies before when I got to Salesforce, I really tried to be self-aware about that and really tried to be a part of Salesforce and tried to shift my identity and not be a single issue voter around Quiff. I'd really tried to embrace it. And I think it's really hard for some founders to do. And some founders don't want to, honestly. maybe cash the check and it's more of a transactional relationship. I really actually am so grateful for the experience of having been at Facebook and Salesforce. I learned so much. But it really took a lot of effort on my part to just transform my perception of myself and who I am to get that value out of the company that acquired us.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Your identity. You need to go from being the head of Instagram, in my case, the head of Quip to being an employee of Salesforce or going from being the CEO of FriendFeed to being an employee of Facebook. What I've observed is it's that identity shift is a prerequisite for most of the other things. It's not simply your ability to handle the politics and bureaucracy of bigger company or to navigate a new structure. I actually think most founders don't make that leap where they actually identify with that new thing. It's even harder for some of the employees too because most of the time in an acquisition, an employee of an acquired company didn't choose that path. And in fact, they chose to work for a different company and they, you know, the acquisition determined a different outcome. And that's why integrating acquisitions is so nuanced. And I would say that having the experience of having been acquired.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source
“Acquiring company, but even in those cases, the founders didn't stay around that long. That's maybe a little unfair. Stick around for a little bit. I think the interesting thing about being a founder is it's not just building a business, but it's very much your identity. And I think it's very hard for people, aren't founders, to experience it. If you take everything very personally from the product to the customers to the press to your competitors, both inner and outer measures of success. And I think when you go to be an acquired, there's a business aspect to it. And can you operate within a larger company? But that's intertwined with a sense of identity. You go from being the founder of a company and the CEO of a company or CTO of a company, whatever your title happens to be as one of the co-founders, to be in a part of a larger organization and to fully embrace that, you actually need to change.”
2025-04-15 · The Knowledge Project with Shane Parrish · Bret Taylor: A Vision for AI’s Next Frontier · IDENTIFIED FROM THE TRANSCRIPT · source