Mike Krieger

You can always build something you’ve already sold. But you can’t always sell something you’ve already built. When I was at IDEO, I watched David Kelley say “yes” to client projects that sounded impossible - six-week timelines, half the budget, specs that defied physics. He’d nod, smile, and say, “We can make that happen.” Then we’d start sketching concepts and building prototypes in the shop, and before long, we had figured out how. Kelley knew it was easier to build toward a committed outcome than to sell an idea no one had asked for. I still see this play out with founders. Many fall in love with the thing they’ve already built - the clever piece of tech, the whiz-bang widget - and then realize nobody’s asking for it. The best founders uncover hidden demand and build products that bring to light opportunities that would otherwise remain unseen. That order matters. Start with the problem or opportunity, then design the solution.

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This woman built tech that can spot bipolar episodes, detect postpartum depression, and keep her diabetic son alive. Vivienne Ming is a theoretical neuroscientist, a serial entrepreneur, and a self-proclaimed “mad scientist.” Her obsession? Maximizing human potential. Vivienne was born Evan Campbell Smith. By her early twenties, she had dropped out of college, fallen into depression, and was contemplating suicide. Then she made a decision: if she was going to keep living, she was going to do something substantial. She flipped a coin between economics and cognitive science. It landed on cognitive science. She went back to UC San Diego, earned a degree in cognitive neuroscience, then completed a PhD in psychology and theoretical neuroscience at Carnegie Mellon. While in grad school, she met Norma, a fellow PhD student. They fell in love. And one night, Vivienne told her the truth. “My secret is that I wish I were a woman.” Norma didn’t run. She listened. Vivienne underwent hormone therapy after conceiving their first child, Baxter, and completed gender confirmation surgery in 2008. They later had a second child, Thalia. Over the next two decades, Vivienne launched six startups, and served as chief scientist at two others. She invented AI systems that could: - Predict manic episodes in bipolar patients - Reunite refugee orphans with surviving relatives - Help autistic children learn to read facial expressions - Manage her son’s diabetes in real-time - Identify and mitigate bias in hiring - Improve cognitive recovery in TBI and dementia patients - Assess student creativity and emotional intelligence In 2011, she co-founded Socos Labs, her fifth company, a “mad science incubator” focused on the intersection of neuroscience, AI, education, and human development. Then she built The Human Trust, a nonprofit data trust that works on complex social challenges: disability, economic exclusion, algorithmic justice… She also co-founded Dionysus Health, where she helped create the world’s first biological test for postpartum depression, using AI and epigenetics to identify risk before symptoms appear. Throughout it all, her central thesis never changed. AI is not the end of the world. It’s not salvation either. It’s a tool, it’s only as useful as the humans who wield it. The real danger, she says, is that we’ll use AI to do just enough. That we’ll automate away our creativity. Flatten our curiosity. Become passive operators of tools we don’t fully understand. When writing her latest book, Robot-Proof, she fed every chapter into Gemini. But not to edit. “I tell it: You’re my nemesis. Tear this apart. Tell me where I’m wrong. Then I run it again: Now you’re a bored reader. Show me where you got lost.” Her work has earned her a spot on the BBC 100 Women list, Inc. Magazine’s 10 Women to Watch in Tech, and more than a dozen research and innovation awards. 💡 Follow Justine Juillard for daily #femalefounder spotlights

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Three years ago, we launched Wisdom Ventures with a clear intention to support founders building at the intersection of well-being, human connection, and transformative tech. Since then, we’ve made 37 investments from our oversubscribed "minimum viable" $10M Fund I, backing early-stage companies in physical and mental wellbeing, women’s health, ethical AI, and human connection-centered innovation. We’ve always known we are on to something—what we didn’t expect was how quickly the data would back it up. Recent industry benchmarks show that most 2022-vintage emerging funds are experiencing the usual J-curve dip. In contrast, Wisdom Ventures is showing strong early performance: 📈 Net IRR (internal rate of return): >10% 📊 MOIC (multiple on invested capital): ~2x* ⏰ Median investment age: 18 months 💥 ....and # of our companies have a diverse founder by gender, race, or sexual orientation: 75% As we get ready to make our 38th and final investment out of Fund I and start deploying out of our significantly larger Fund II (first close May 1st), we’re filled with gratitude—for our founders, our LPs, our early supporters, our early believers, and this growing movement toward a more conscious, connected future, fueled by innovation from the ❤️ *Based on most current reports **Not in photo: Our fantastic operating partner, Zoe Rogers #WisdomVentures #ImpactInvesting #ConsciousTech #Wellbeing #AIForGood #FutureOfWork #VentureCapital

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There is so much magic for scientists locked away in LLMs. But unlocking it requires a rare blend of scientific and engineering expertise. That’s why I’m thrilled that Nicholas Larus-Stone and Sphinx Bio are joining Benchling. I’ve gotten to know Nicholas over the last few months. We share a vision for what AI agents can do for scientists – and an obsession with turning that potential into real, everyday value. Together, we’re building agents that automate toil and answer complex questions. See what we’re building: https://lnkd.in/gtDHZpnt

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My first reaction to the Anthropic safety pledge change this week? Sh*t. As an AI-skeptical founder who's spent the last few years building an AI company with Dewey Labs, Anthropic's original pledge – to pause scaling and deployment if safety measures couldn't keep pace – felt like a rare moment of our better angels winning. And these headlines felt depressing. But then I re-read the stories, and dug a bit deeper into the original sources from Anthropic. And I think the media has missed a much more nuanced story in the service of a good headline. The old pledge put Anthropic's safety researchers in a trap. Raise serious concerns about a model's risks, and you might freeze the company's development pipeline – with consequences for competitive position, for stock value, for careers. Stay quiet, and the industry loses critical information about where real dangers are emerging. There's no good answer there. And as Anthropic's own assessment admits, capability thresholds turned out to be far more ambiguous than they'd hoped. Clean go/no-go calls on genuinely murky definitions aren't just hard. They distort how research gets done. The new structure largely eliminates that conflict. Safety teams can now push hard, publish often, and do it without holding a sword over the company's head. Anthropic committed to Risk Reports every 3–6 months – graded publicly against specific, stated goals. Holden Karnofsky, who helped design this change and by his own account pushed for it for over a year, doesn't describe it as a capitulation. He calls the old approach a design flaw. When you find a flaw, you update it, even if it doesn’t play well in the public eye. I get it – this can still read as competitive pressure winning out over principle. There are real business incentives at play and I'm not naive about that. The political climate around AI regulation has also shifted significantly, which Anthropic doesn't try to hide. But a single company committing to pause while its competitors keep building doesn't make AI safer. It just makes the safety-conscious lab smaller and less influential – and puts the pace of development in the hands of whoever has the fewest guardrails. Anthropic isn't wrong about this. And they're not alone: a RAND report they cite directly says certain security standards (designed to defend against state-level attacks) are "currently not possible" for any single company. Pledging to achieve them unilaterally was never going to work. Is it perfect? No. Nothing in this space is, especially at the speed we're moving. But trading a symbolic pledge for a more functional accountability structure seems like the right direction – even if it's a harder case to make in a headline.

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The most transformative growth doesn't happen in isolation—it emerges from ecosystems. Through my work building ecosystems like Energize Colorado, Elevate Quantum, State-funded advanced industry ecosystems (Space, Climate, and Water), and a current early stage project on a Creative Hub (ecosystem) for film and music, I've seen how both innovation ecosystems (connecting startups, corporations, universities, investors) and community ecosystems (building networks of trust and shared purpose) create greater value when a diverse group of partners collaborate. Whether building an innovation or community ecosystem, the same principles drive success: -Diversity of participants brings complementary skills and fresh perspectives. - Flow of resources (ideas, funding, mentorship, networks, social capital) accelerates progress for everyone. - Shared purpose aligns individual success with collective impact. The magic happens when we shift from "what can I achieve alone?" to "what can we accomplish together?"

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