Allie K. Miller

The search fund model is built on alignment. But "usually" isn’t "always." While search funds are collaborative by design, collaboration doesn’t eliminate tension. Based on experiences from both sides of the table, our latest note explores the moments when incentives between ETA CEOs and investors naturally drift apart. Why this matters: It’s Structural: These aren't "bad actor" stories; they are inherent constraints of the model. It’s Predictable: Tensions surface when timelines, personal realities, or stakes shift. It’s Navigable: Understanding these frictions upfront builds empathy, clearer expectations, and better discussions. Grateful to collaborate with Alex Hodgkin, CFA, and A.J. Wasserstein on a topic that rewards honesty and dialogue over optimism alone. Read the full paper at: https://lnkd.in/e_eskQ9V #ETA, #SearchFunds, #Searchfund, #EntrepreneurshipThroughAcquisition, #Entrepreneurship, #CorporateGovernance, #InvestorRelations, #PrivateEquity, #YaleSoM, #Kellogg, #Booth

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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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A few weeks back, I watched Maggie Hott, GTM leader at OpenAI, confidently navigate her first board meeting at Unify. Having worked with her through Emergence Capital's Operator in Residence (OIR) program, seeing her immediately contribute valuable insights made me think about how most board members receive virtually no training for this critical role. At Emergence, we've built our firm around developing board excellence. We grow all our partners from within and have established a culture of mentorship focused on board service. Junior investors aren't thrown into the deep end—we pair them with senior GPs to observe effective board dynamics firsthand. My initial experience was at DroneDeploy alongside my partner Kevin Spain, where I got great mentorship before taking on independent board responsibilities. We extend this methodology to our OIR program, where operators learn how to be effective board members. Based on my experience mentoring directors, here are the fundamental principles I share with first-timers for how board members can best support founders: 1. Reframe the purpose: Problem-solving, not reporting If your board meeting is primarily reporting, you're wasting your management team's time. Information sharing should happen asynchronously, with board members engaging with materials before the meeting. This enables the live session to leverage collective intelligence on critical challenges. This rarely happens because many directors overextend themselves across too many boards—another reason we maintain a disciplined investment pace. 2. Master the Socratic approach The most valuable contribution often comes through thoughtful questions rather than declarative statements. Your objective is to enhance the decision-making capability of management. I enter each meeting with 1-3 specific areas where I know I can add value, focusing questions on these topics. 3. Follow-through separates professionals from amateurs Diligently document your commitments, establish clear action items, and execute them. It's crazy how just doing this proactively makes a board member stand out. 4. Understand your unique contribution to the board ecosystem A high-functioning board resembles a great basketball team—you need complementary skills, not redundant ones. In every meeting, I stay conscious of my distinct value relative to others in the room, whether that's SaaS expertise, AI knowledge, or a particular relationship dynamic with the CEO. I calibrate my role based on needs—sometimes assertively addressing areas where others have less experience, other times asking probing questions where fellow members have deeper expertise. -- To my knowledge, Emergence is the only VC firm with a formalized program dedicated to board excellence. It's an investment that yields returns where they matter most—in bending the odds of success for our founders. Founders, I'm curious: What board member behaviors have you found most valuable?

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This week, Gloo also updated the general Flourishing AI (FAI) Benchmark. Originally launched in July, it showed leading frontier LLMs struggled to support holistic human wellbeing across 7 key dimensions (Character, Finances, Faith, etc.). The new data is promising! It shows that models made steady gains in core reasoning, safety alignment, and pragmatic guidance. But also confirms earlier patterns -- strong in fact-based dimensions, weak in personal viewpoints and values. Essentially, LLMs handle pragmatic guidance well, but struggle with nuanced, value-aligned reasoning. Still work to be done in supporting holistic human flourishing and wellbeing. www.gloo.com/fai 

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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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NYC is losing young technical founders to SF — and it’s not about vibes. It’s about cost of entry. SF has far more entry infrastructure than NYC: i.e. the housing, community, and early support (financial and otherwise) that lets founders start building before they raise capital. This is widening the gap between the two cities' tech sectors. We are specifically calling for ideas (and hopefully action) to address NYC’s dearth of hacker houses: physical spaces that combine housing, workspace, community, and early peer support. I’m convinced that seeding hacker houses, if done right, is a low-cost, high-impact way to attract more young technical founders to NYC — and critically, something this community can actually do. And we should. The data is stark. Venture investment in NYC is ~19% of SF’s total — the lowest since 2017 — and the biggest, most innovative companies (especially in AI) are overwhelmingly being built in San Francisco. People who want to be entrepreneurs tend to work where those companies are. Unsurprisingly, many students and young builders assume they must go west. But do they actually want to — or is it just easier to get started there? I spent significant time in the Bay last year, and one difference stood out immediately: SF is dense with hacker houses and founder residences that help people get from 0→1. These resources are especially critical for recent grads and first-time founders who might lack capital or built-in networks. NYC may have long-term pull, but at the earliest stage, higher upfront costs and friction (recent Economist data suggests ~50% higher rents than SF) push many founders away. Hacker houses may sound anachronistic, but they’re real centers of gravity. We estimate SF has at least ~10x more active hacker houses than NYC, and that these houses have helped foster hundreds of billions of dollars in market value. I’m an NYC tech evangelist. I’ve worked on tech ecosystem development at New York City Economic Development Corporation, helped design national innovation programs for the Obama White House, and now invest in early-stage companies as a GP at Max Ventures. From a dollars-to-impact perspective, seeding hacker houses in NYC is one of the most efficient levers the city can pull. We wrote an overview doc (linked below) that explores this concept — and we'd welcome feedback from the NYC tech community. We are also hosting a small series of conversations — starting with a dinner in February co-hosted with Tech:NYC, Keel (Brent J. Smith), Company Ventures and Inspired Capital — to bring together leaders across tech, real estate, and policy. 👉 If you’re a founder, operator, VC, student, or have built / lived in a hacker house: • Does this resonate? • What would make this work in NYC? • Who’s already doing something adjacent we should talk to? Would love to connect if you’re interested in contributing or joining the conversation.

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I recently sat down with David Prosser at Forbes to discuss how we, at AAF Management Ltd., have strategically positioned ourselves to ride — and invest through — the current AI wave. The conversation came at a meaningful inflection point for us: just days after announcing 𝘛𝘩𝘦 𝘈𝘹𝘪𝘴 𝘍𝘶𝘯𝘥, a $55 million early-stage hybrid vehicle anchored by Mubadala Capital. Over the past decade in venture, I’ve seen the industry evolve through extraordinary macro shifts — the rise and fall of online-native e-commerce brands, the boom and bust of biotech, and the irrational exuberance of the ZIRP-era liquidity that fueled a historic valuation run-up, followed by a painful but necessary reset. Each cycle has followed a familiar pattern: euphoria → over-investment → correction → consolidation → compounding. And every cycle reinforces the same truth: 𝘦𝘯𝘥𝘶𝘳𝘪𝘯𝘨 𝘷𝘢𝘭𝘶𝘦 𝘪𝘴 𝘣𝘶𝘪𝘭𝘵 𝘸𝘩𝘦𝘯 𝘥𝘪𝘴𝘤𝘪𝘱𝘭𝘪𝘯𝘦 𝘮𝘦𝘦𝘵𝘴 𝘤𝘰𝘯𝘷𝘪𝘤𝘵𝘪𝘰𝘯. So, are we in an AI bubble? The honest answer: it depends which asset class you mean. As I said in the interview: “It’s really a story of two different worlds. A handful of very large private companies have been flooded with liquidity and seen huge valuation increases — but that’s not been the experience of small start-ups raising their first $1M to $5M.” Because most investors follow momentum, we’re seeing overzealous valuations in public markets (e.g., NVIDIA) and late-stage private names (e.g., OpenAI, Anthropic, xAI). But in early stage, while Seed valuations have crept up, most AI startups raising $1–5M rounds remain sensible. We see AI as a once-in-a-generation platform shift, not a passing cycle. Through The Axis Fund, we’re intentionally positioned to capture both beta and alpha across this paradigm: Beta — via our 20% fund-of-funds allocation, giving us exposure to the next wave of category-defining AI companies: • Decagon – AI for customer service (backed by Andreessen Horowitz ) • ElevenLabs – AI voice and language models (backed by ICONIQ) • Sanas – AI-powered voice translation (backed by Insight Partners) • Legora – Legal AI for the EU (backed by General Catalyst) Alpha — by cherry-picking the most promising companies across Pre-Seed to Pre-IPO. Our AI thesis is clear: • 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐋𝐚𝐲𝐞𝐫: Agentic workflows driving automation, efficiency, and error reduction. • 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: Libraries, tools, and data systems enabling scalable model deployment. • 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐀𝐈 > 𝐚𝐛𝐬𝐭𝐫𝐚𝐜𝐭 𝐀𝐈:  Founders solving real, high-value problems in fintech, healthcare, SaaS, and industrial tech. • 𝐆𝐥𝐨𝐛𝐚𝐥 𝐩𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞, 𝐥𝐨𝐜𝐚𝐥 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧: Founders who think globally and execute precisely in their markets. We will stop talking about AI as a category the way we stopped talking about cloud or web protocols, 𝘪𝘵 𝘸𝘪𝘭𝘭 𝘣𝘦𝘤𝘰𝘮𝘦 𝘵𝘩𝘦 𝘥𝘦𝘧𝘢𝘶𝘭𝘵. 👇🏽 Read the full article: https://lnkd.in/ejwREwEe

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