Anne Dwane

I’m lucky to work alongside colleagues like Richard Fruehauf, who constantly push my thinking. His latest piece unpacks why U.S. robotics and drone manufacturing faces uphill economics, and how public policy can help turn the tide. One key takeaway: 232 tariffs on robotics imports could help reset the economics that are holding back U.S. investment and production. It’s a sharp perspective on how policy can shape the future of advanced tech here at home. Well worth a read: https://lnkd.in/edMPTQPQ Richard Fruehauf, Robert J. Szczerba, Michael Lutzky, Edward Ovando, Karl Sanchack, Herman Herman, Jeff Legault, Phil English, Richard Fruehauf, Ryan Aument, Michael Guido, Sheila Fitzgerald Sterrett, David McCormick

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"We've become so insular in who we talk to and listen to, and I didn't realize how much that was keeping me in tunnel vision and tunnel thinking." Seth Levine, Co-Author of Capital Evolution and Partner at Foundry, talks about seeking out more diversity of thought on Tech Scenes Unplugged. #venturebacked #vcbacked #venturecapital #leadership #ceo #founder #operatingsystem #peakOS #foundermode

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For the last decade, tech companies optimized for scale: repeatable hiring plans, functional specialization, predictable org charts. I think the next decade will be defined by something harder to achieve: leverage.  The defining trait of AI-first companies won’t necessarily be how much AI they deploy. It will be how willing they are to revisit long-held assumptions about what work exists, who should do it, and how organizations should be structured in the first place. Very excited to finally share the thought piece we at ICONIQ have been working on. Thank you to the many contributors Anu Bharadwaj Dennis Lyandres Diane K. Adams Kipp Bodnar Matt Eccleston Michael Curtis Michelle Morris Jesse Collins Patrick Forquer Rob Bernshteyn who shared their perspectives. This space is evolving faster than any single perspective can capture. If you’re experimenting with new workforce models, seeing something different in your organization, or simply disagree with parts of this thesis, I’d love to hear from you! https://lnkd.in/g66NxYVK

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AI doesn’t have to be complicated, but it does need to work for society’s most critical industries. From healthcare to defense, current solutions lack the deep knowledge to solve organizations’ highly complex use cases. Enter Trase, led by Grant Verstandig, Baskar Sridharan, and Joe Laws. Trase is combining industry-leading tech with deep domain expertise to deliver autonomous, end-to-end, turnkey agents designed to drive real ROI across highly regulated sectors, with compliance, trust, and security guiding their every move. Today, Trase launched out of stealth with $10.5 million in pre-seed funding from Red Cell Partners and VIPC | Virginia Innovation Partnership Corporation. Learn how we’re enabling last-mile AI adoption across various enterprises, starting with healthcare, energy, and national security: https://lnkd.in/egJYdNKz

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One of the most important conversations I heard in Davos today wasn’t about more AI. It was about whether we trust the systems we’re building enough to deploy them at scale. At a Rethinking Risk session at Davos 2026, leaders from media, government, multilateral institutions, and global finance kept circling the same concern: the erosion of trust. The conversation included Ravi Agrawal, Editor-in-Chief, Foreign Policy; Rebeca Grynspan, Secretary-General, UN Conference on Trade and Development (UNCTAD); Amer Bisat, Minister of Economy and Trade, Republic of Lebanon; Amb. Yusuf Maitama Tuggar, Minister of Foreign Affairs, Federal Republic of Nigeria; Stephanie von Friedeburg, Managing Director & Global Head of Public Sector, Citi. Across very different vantage points, the message was consistent: misinformation, selective or low-quality data, and a growing post-truth environment are undermining consensus, multilateralism, and sound risk analysis. When trust erodes: — due diligence weakens — uncertainty rises and risk premia increase — fact-based decision-making breaks down for governments and businesses alike The key takeaway: AI doesn’t fail at deployment because the models aren’t powerful enough. It fails when the systems around it aren’t trusted. Rebuilding trust isn’t just a technical challenge. It requires rigorous verification and higher-quality data; transparent analytics and governance; and inclusive, cross-stakeholder consensus-building. As the World Economic Forum continues to emphasize, trust isn’t a soft value layered onto innovation. It’s a prerequisite for scale, resilience, and long-term economic coordination. If we want AI to reduce risk rather than amplify it, we have to start by designing systems people and institutions can trust. That may be the hardest work ahead. And also the most important.

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Reposting perspectives from Cleo Valeroso, CDR, our VP of Global People Operations and Chief of Staff at AI Squared. As AI becomes integral to HR, getting caught up in automation and efficiency is easy, but the best results happen when we blend AI’s power with clear boundaries, responsible oversight, and honest communication about what technology can (and can’t) do. #AI #HRTech #PeopleOps #Trust #FutureOfWork #Leadership #HumanResources

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Company building in energy is shaped by early decisions that compound over time—how capital is structured, how technical risk is absorbed, and how teams prepare for scale well before it arrives.    Much of my work with founders centers on navigating those choices as deep science becomes real businesses. The details differ across power, materials, and industrial systems, but the challenge is consistent: building companies that can operate, adapt, and grow over long horizons.  You can see that work taking shape across the Breakthrough Energy portfolio. https://lnkd.in/eXd72trE

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