Silicon Valley Girl: AI, Tech and Career Growth

Using AI every day doesn’t automatically make you better at your job.
So how do you use it to build real expertise?
In this episode, I talked to Karim R. Lakhani, a Harvard Business School professor whose research with BCG, Procter & Gamble, and H&M explores how AI changes the way we work.
We talk about three ways people work with AI – cyborgs, centaurs, and self-automators – and why the way you delegate matters for what you actually learn. Karim shares why he never takes the first answer, how to make AI challenge your assumptions, and why “the AI gave me that” is no excuse for poor work.We also get into what Harvard MBA students now build with AI, how juniors can develop judgment and taste, why CEOs need hands-on experience with these tools, and how to set bigger business goals as AI gets more capable. And we end with a question every founder should be asking: when the next AI model launches, does your business become more valuable – or does the model absorb what you do?

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Felix Rieseberg has led engineering for Claude.ai, Cowork, and Claude Code Desktop at Anthropic. He thinks many of us are still giving AI tasks it has already outgrown. If you’re only asking Claude to summarize emails, what are you missing?
How to hand AI bigger goals. Why “you’re an expert” isn’t enough аnd how to catch mistakes when the answers sound convincing. Felix shares how to start trusting AI with more – and stop being the bottleneck in your own company.

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James Manyika runs research and labs at Google, and his team recently studied millions of real Gemini conversations to see how people use AI at work. In a typical job, it's only about a fifth of the tasks. I asked him what that means for your job and your salary, why he bet against the people who predicted half of white-collar jobs would disappear in two years, which three signals would change his forecast, and which AI breakthroughs are already in your life without you noticing.📩 Follow my Newsletter: https://siliconvalleygirl.beehiiv.com/subscribe?utm_source=spotify&utm_medium=description&utm_campaign=futureproof-sub&utm_content=30-days-plan&utm_term=james-manyika

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Brian Chesky built Airbnb into an S&P 500 company, and he says starting a business today is easier than it was 20 years ago.
In this episode we go step by step: how Airbnb is becoming AI-native, why chat is the wrong interface for most work, how Brian generates 30,000 ideas a year and picks the ones worth doing, why the phone is the enemy of focus, and the one habit that separates real builders from everyone else.
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Daron Acemoglu is an MIT economist and a 2024 Nobel laureate in Economic Sciences. He believes some of AI’s biggest business opportunities are being overlooked—but where does he see the real money, and what should you learn to stay valuable?

In this episode, I ask Daron where founders should look for opportunities beyond the AI hype. We talk about why helping workers become more productive can be better for business than replacing them, why existing models are already powerful enough to build useful applications, and where high-quality data creates an advantage. Daron also shares what he would study now and why builders need to spend more time talking to workers.

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