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Most PMs still think in tasks. Write a PRD. Update JIRA. Review designs. AI native PMs think differently. They think in prompts. .Mike Bal calls it "thinking in prompts" and admits it sounded silly at first. But once you integrate AI into daily work, it becomes natural. Instead of...

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Aakash Gupta

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16,788 Aufrufe • vor 8 Monaten •via X (Twitter)

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Watch this game-changing dissertation on "expert writing." Expert writers write to "think" about the world. 99% of experts write and think at the same time. They use the writing process to help themselves think. This is how they do their best thinking. Write to think about the world. Do this because you care, because you want to be part of progress, because you want to make a dent in the universe. Write to inspire and influence. And when you are finished writing, and you click publish, think about your work this way... the intent of your text is to cause readers to change the way they think about the world. Engagement metrics don't really matter in comparison. Whether or not your text is valuable, depends on whether or not your readers perceive that you have valuably changed what they think, or what they do, or how they decide. One of the reasons it's so hard for smart people to write well is because they don't write to change the way people think about the world. They write to complete a project, to earn a grade, to be assessed. Or they write to publish *their* thoughts without going through a mental and soulful exercise of writing to think about the world, without writing to change how people think about the world. Write to think about the world. Change how people think about the world. In an era of #GenerativeAI, content isn't the end game. Your goal isn't just to get someone's attention, generate reactions, or show up in search. Your mission is to change how people think about the world. Change How People Think About the World. Thank you, Larry McEnerney (now-retired former Director of the University of Chicago's Writing Program).

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.Balaji on public disclosed AI vs. public undisclosed AI: "Whenever I see a slide deck that has AI content in it, it just shows that either they're dumb or they think you're dumb." "They're dumb because they can't tell the difference between normal text and AI text, or they think you're dumb and they can get one over on you and spend a little bit of effort to just flood you with a bunch of words."

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Elon Musk: Programming explicit morality into AI can backfire dangerously. “I do think there's some danger associated with digital superintelligence. I think the biggest issue is that it has to be trained to be rigorously truthful, and it has to be trained to be curious. And I've thought a lot about AI safety for a long time. One of the challenges you have with programming explicit morality into AI is what people sometimes call the Waluigi problem. If you program Luigi, you can automatically invert that and create Waluigi – bad Luigi. What you cannot invert is physical reality. You can't invert the rules of physics. You can't invert logic. I think what regulators should be concerned about is, is the AI being rigorously truthful? Is it giving an answer that is most probably correct with acknowledged error? I think that's the best move, and that's what we're trying to do at xAI.” Viva Tech Paris, May 23, 2024

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"What is an AI Agent and why do they matter?" An agent is a program that autonomously completes tasks or makes decisions based on data. What do I mean by autonomous? The agent understands task intent, can plan steps to solve the problem, decide and execute and actions and adapt to the environment. Consider how many of us use AI chat interfaces today. You might ask ChatGPT to write an article from start to finish and get a one-shot response. You probably need to do some work to iterate on it yourself. An agentic version is more nuanced - it might write an outline, decide if research is needed, write a draft, evaluate if it needs work and revise itself. Unlike traditional AI models that simply respond to queries, agents are designed to be autonomous and proactive. Think of them as assistants that can not only understand what you need but also take initiative to accomplish tasks by using various tools and making decisions along the way. For example, an AI agent might help a marketing team by not just analyzing campaign data, but actively monitoring performance, adjusting budget allocations, and even drafting social media posts based on real-time engagement metrics. The significance of AI agents lies in their potential to transform how we work. In customer service, agents can handle complex inquiries by accessing multiple databases, processing payments, and updating records - all while maintaining natural conversations with customers. In software development, they can assist programmers by not just suggesting code but actively debugging issues, writing test cases, and even refactoring entire codebases. This level of autonomy and capability represents a fundamental shift from AI as a tool to AI as a collaborative partner. While there remain many unknowns, I'm excited about the potential for agents and we're thinking about how they can help users and developers on the web over in Chrome. The key to success will likely be finding the right balance between human oversight and agent autonomy, ensuring that these powerful tools enhance rather than diminish the human element in business operations.

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Mark Cuban said what every CEO in America needs to hear. "There are only two types of companies in this world, those who are great at AI, and everybody else. If you don't know AI, you are going to fail. Period, end of story." Mark Cuban didn't stop there. "Whether you are an employee, you're going to have to understand how AI impacts your job and how you can use it to be better at your job. Same if you're a student. And if you're a CEO, you can't just say, okay, I'm going to get my tech guys to understand it and educate me on it. You have to understand it yourself because it will have significant impact on every single thing that you do. There's no avoiding it." This is coming from someone who built and sold the Dallas Mavericks, who made his first fortune selling a company to Yahoo for $5.7 billion in 1999, and who has spent the last two years going deeper on AI than almost any investor his age. He is describing the Innovator's AI Dilemma, entrepreneurs are right now building AI-native companies designed to displace every major incumbent. If a CEO tears down their company to rebuild it AI native, investors revolt but if they do nothing, AI-native startups eat their market and investors revolt anyway. Either path leads to shareholder lawsuits and there is no comfortable middle. The companies that survive will be the ones where leadership, not just the tech team, genuinely understands what the technology can do. The ones that don't will look back at this moment the same way Blockbuster looks at 2005.

StockMarket.News

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Chamath Palihapitiya Chamath Palihapitiya "Bro, there is no failure." "That is what other people think of you to keep you down. There's no failure. If you were left on an island and it happened, you would just brush it off and move on. It's everybody else that you think is judging you. But then, here's the secret. They don't give a fuck about you. They are living their own lives. So it's your perception of what they think of you." "There is no failure. There's do and learn. Do and learn. Do and learn. Do and learn." Stanford AI Lab
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Chamath Palihapitiya Chamath Palihapitiya "Bro, there is no failure." "That is what other people think of you to keep you down. There's no failure. If you were left on an island and it happened, you would just brush it off and move on. It's everybody else that you think is judging you. But then, here's the secret. They don't give a fuck about you. They are living their own lives. So it's your perception of what they think of you." "There is no failure. There's do and learn. Do and learn. Do and learn. Do and learn." Stanford AI Lab

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