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Good Products Are Hard to Vary.

161,680 görüntüleme • 9 ay önce •via X (Twitter)

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Good Products are Opinionated. “Every great founder I’ve seen up close, or even from afar, is highly opinionated and they’re almost dictatorial in how they run things. Also, early-stage teams are opinionated. And the products they build are opinionated. Opinionated means they have a strong vision for what it should and should not do. If you don’t have a strong vision of what it should and should not do, then you end up with a giant mess of competing features. jack Dorsey has a great phrase: “Limit the number of details and make every detail perfect.” And that’s especially important in consumer products. You have to be extremely opinionated. All the best products in consumer-land get there through simplicity. You could argue the recent success of ChatGPT and similar AI chatbots is because they’re even simpler than Google. Google looked like the simplest product you could possibly build. It was just a box. But even that box had limitations in what you could do. You were trained not to talk to it conversationally. You would enter keywords and you had to be careful with those keywords. You couldn’t just ask a question outright and get a sensible answer. It wouldn’t do proper synonym matching, and then it would spit you back a whole bunch of results. That was complicated. You’d have to sift through and figure out which ones were ads, which ones were real, were they sorted correctly, and then you’d have to click through and read it. ChatGPT and the chatbot simplified that even further. You just talk to it like a human—use your voice or you type and it gives you back a straight answer. It might not always be right, but it’s good enough, and it gives you back a straight answer in text or voice or images or whatever you prefer. So it simplifies what we looked at as the simplest product on the Internet, which was formerly Google, and makes it even simpler. And you just cannot make a product that’s simple enough. To be simple, you have to be extremely opinionated. You have to remove everything that doesn’t match your opinion of what the product should be doing. You have to meticulously remove every single click, every single extra button, every single setting. In fact, things in the settings menu are an indication that you’ve abdicated your responsibility to the user. Choices for the user are an abdication of your responsibility. Maybe for legal or important reasons, you can have a few of these, but you should struggle and resist against every single choice the user has to make. In the age of TikTok and ChatGPT, that’s more obvious than ever. People don’t want to make choices. They don’t want the cognitive load. They want you to figure out what the right defaults are and what they should be doing and looking at, and they want you to present it to them.”

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Great Engineers are Also Artists. “I characterize art as something that is done for its own sake, and done well, and often creates a sense of beauty or some strong emotion. And a lot of engineers are introverts. As an aside, I hate the term “incel.” It’s just a way of putting introverts down. It’s the new “nerd,” if you will. If someone says that somebody is an incel, I’m more likely to want to interview them. So let’s move away from the slurs. But introverts tend to want to express themselves through other things rather than going out and expressing themselves directly. So what are they going to do? They’re going to express themselves through their craft. They’re going to create art. In my current company, at least half the engineers have serious artwork they’ve done on the side. World-class artwork—everything from elegant mathematical proofs to beautiful computer art, to literally sculpting things with clay, designing clothing, designing doorknobs, water bottles. There’s one who’s done incredible music videos, really good stuff. And I see a lot of the better engineers tinker with the AI art products, much more so than even so-called artists do. I think a lot of artists are scared by AI art products saying, “This is going to replace me.” Whereas someone who doesn’t have that identity of an artist and doesn’t feel threatened by it—it’s just a tool and they try it out to see what it can create. Anything done for its own sake and done as well as one possibly can is art. And great engineers are also artists. They’re capable of anything. It’s just they’ve chosen to be engineers and focused on building things because engineering is the ability to turn your ideas and your art into things that actually work, that do something useful, that embody some knowledge in a way that it can be repeated and people can get utility out of it. But that doesn’t mean that it can’t be beautiful.”

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Is Traditional Software Engineering Dead? “Does this mean that traditional software engineering is dead? Absolutely not. Software engineers—even the ones who are not necessarily tuning or training AI models—these are now among the most leveraged people on earth. Sure, the guys who are training and tuning models are even more leveraged because they’re building the tool set that software engineers are using. But software engineers still have two massive advantages on you. First, they think in code, so they actually know what’s going on underneath. And all abstractions are leaky. So when you have a computer programming for you—when you have Claude Code or equivalent programming for you—it’s going to make mistakes. It’s going to have bugs. It’s going to have suboptimal architecture. So it’s not going to be quite right. And someone who understands what’s going on underneath will be able to plug the leaks as they occur. So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you’re going to want to have a software engineering background. The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution. For example, if they need to do a binary sort or reverse a linked list, they’ve seen countless examples of that, so they’re extremely good at it. But when you start getting out of their domain—where you have to write very high-performance code, when you’re running on architectures that are novel or brand new, when you’re actually creating new things or solving new problems, then you still need to get in there and hand code it. At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own… And remember: there is no demand for average. The average app—nobody wants it, at least as long as it’s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there’s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it’s cheaper, or something of the sort. But generally speaking, people only want the best of anything. So the bad news is there’s no point in being number two or number three—like in the famous Glengarry Glen Ross scene where Alec Baldwin says, “First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you’re fired.” That’s absolutely true in these winner-take-all markets. That’s the bad news: You have to be the best at something if you want to win. However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet of mine where I said, “Become the best in the world at what you do. Keep redefining what you do until this is true.” And I think that still applies in this age of AI.”

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Founders cannot outsource recruiting. “Recruiting is the most important thing because you need creativity; you need motivated people. Ideally, the early people are all geniuses. They’re self-managing, low-ego, hardworking, highly competent, builders, technical—maybe one or two sellers—but you can’t watch everything. You can’t micromanage everything. The early people are the DNA of the company. When you outsource recruiting, when you have other people hiring and interviewing and making hiring decisions without your direct involvement and veto, that’s a sad day. That’s the day that the company’s no longer being driven directly by you. There’s now a fly-by-wire element in between. There’s some mechanical linkage going through another human, often at a distance. And other people are not going to have the same level of selectivity that you will as a founder. The important size at which a company starts changing is not some arbitrary number, like 20 or 30 or 40. It’s the point at which the founder is not directly recruiting and managing everyone. The moment that there are middle layers of management, then you are somewhat disconnected from the company, and your ability to directly drive a product team that can take the company from zero to one goes away. So we really cannot outsource recruiting. People think you can. They hire recruiters, for example. Maybe you can outsource a little bit of sourcing, but I would even argue that’s difficult. The reason recruiting is so, so, so important—and a lot of it is obvious, I’ll skip the obvious reasons—but one non-obvious reason is that the best people truly only want to work with the best people. Working with anyone who’s not at their level is a cognitive load upon them. And the more people they’re surrounded by who are not as good as they are, the more keenly they’re aware that they belong somewhere else, or they should be doing their own thing. The best teams are mutually motivated. They reinforce each other. Everyone’s trying to impress each other. One good test is when you’re recruiting a new person, you should be able to say to them, “Walk into that room where the rest of the team is sitting. Take anyone you want—pick them at random—pull them aside for 30 minutes, and interview them. And if you aren’t impressed by them, don’t join.” When you do that test, you will instinctively flinch at the idea of them interviewing randomly a certain person that’s kind of in the back of your mind. That’s the person you need to let go. Because that’s the person keeping you from having this high-functioning team that all wants to impress each other.”

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