Fund Structuring Insights

🚀 Thrilled to share my latest piece with ImpactAlpha: “Innovative Finance Initiative’s fund designs for radical impact” — co-authored with the brilliant Erinch Sahan of the Doughnut Economics Action Lab (DEAL). Over the past decade, we’ve seen impact investing and sustainable finance gain serious momentum. But here’s the uncomfortable truth: despite this growth, our social and ecological crises have only deepened. Why? Because most financial tools have tried to fit into traditional systems, rather than transform them. It’s time to reimagine. We’re calling this next chapter Impact Investing 3.0—a refresh that moves us from tweaking systems to building new ones, rooted in accountability, inclusion, and regeneration. 🌱 A major piece of this shift? Fund design. Too often, we start with structure—10 year closed end fund, equity investments, etc. —and retrofit the mission. What if we flipped that? What if fund managers designed structures from the ground up, starting with purpose? We lay out a five-part framework for how fund managers can unlock deeper, more transformative impact: 🎯 Purpose – Anchor the fund in a regenerative investment thesis. Think long-term stewardship, not short-term shareholder value. 🧱 Structure – Embrace vehicles beyond the usual suspects. Open-ended funds, permanent capital, and blended finance can provide the flexibility impact needs. ⚖️ Incentives – Align manager comp and investee terms with real impact—not just IRR. 🗳️ Governance – Include the voices of those most affected by investment decisions. 🔁 Exit – Redesign exits to preserve impact: employee ownership, community buyouts, or even self-liquidating structures. This draws on the best of Adventure Finance, Doughnut Economics (Kate Raworth), and Marjorie Kelly’s vision for economic redesign. And it’s already happening: check out innovators like Purpose Economy, Fair Capital Partners, Prime Coalition, Citizenfund Brussels, and Apis & Heritage Capital Partners. 💡 If we’re serious about transformative change, our capital must reflect it—from structure to strategy. 📰 Read the full article on ImpactAlpha (link below) and join the conversation at the Innovative Finance Initiative (link also below). Let’s build the next generation of funds—designed for impact, not just returns. #ImpactInvesting #FundDesign #InnovativeFinance #ImpactAlpha #DoughnutEconomics #Investing3point0 #RegenerativeFinance #SystemsChange

Only 15% of VCs understand this fund structure hack. The rest are leaving MILLIONS on the table👇 ◾️ Most VCs invest just 80-85% of the capital they raise. Why? Management fees consume the rest. On a $100M fund with standard fees over 10 years, that's $15-20M never invested in startups. That's amount that can never generate returns for LPs or carry for GPs. ◾️ The hack? Management fee recycling. Instead of distributing early exit proceeds, smart VCs reinvest them. This gets the FULL $100M working in portfolio companies - or even more. Elite firms like Foundry and Union Square Ventures aim for 110% deployment. ◾️ The math is astonishing (with 1.5% MF): - Without recycling: $85M invested needs a 4.1x multiple to achieve a 3x net return to LPs. - With recycling: $100M invested only needs a 3.65x multiple for the same 3x return. That's 11% less pressure on performance. ◾️ Think about that: you're asked to generate the SAME returns with LESS capital. Brad Feld puts it perfectly: "If an LP gives us a $1 to invest, we should invest at least that $1, not $0.85." When you frame it this way, NOT recycling seems absurd. Yet 85% of VCs still don't do this effectively. ◾️ For emerging fund managers, this is your edge. Established funds often get away with poor recycling because of their track record. You don't have that luxury. Offer better structural alignment and you'll stand out in LP conversations immediately. ◾️ What early-stage companies deserve recycling capital? - "Singles" that return 1-2x quickly. - Small positions in companies that get acquired early. - Secondary sales of promising but not rocket ship companies. Don't recycle your home runs. Let those distribute. ◾️ Fred Wilson notes they've put as much as $140M to work in a $125M fund. Think about it: they called less capital than committed ($110M) yet deployed MORE than committed ($140M)! That's the magic of aggressive recycling + smart exit management. ◾️ The typical objections to recycling: - "LPs want distributions early". - "It complicates tax planning". - "It could extend the fund life". All valid, but addressable through smart provisions in your LPA that limit timing, amount, and source of recycling. ◾️ The best LPA recycling provisions include: - Cap of 20-25% of fund size for recycling. - Limited to investment period (first 5 years). - Only from exits within 2 years of initial investment. - Clear rules on what recycling can fund (new deals vs. follow-ons). ◾️ For LPs, the key question to ask GPs: "What's your recycling strategy and how does it maximize my capital efficiency?" The answer reveals whether a GP truly understands fund construction or is just collecting fees. ◾️ The bottom line: management fee recycling is the closest thing to "free money" in venture. It puts more capital to work, reduces the required multiple for success, and aligns GP-LP interests perfectly. What do you think about recycling?

If you’re building a mission-driven enterprise, chances are you’ve run into a dilemma: You need capital to grow. But traditional investors want fast returns. And grants alone won’t sustain you. Here’s the good news: Philanthropic capital can be structured to meet you where you are as strategic fuel for sustainable impact. Below are five common structures, each with real-world use cases, benefits, and caveats. Understanding these will help you speak the language of capital without compromising your mission. 1. Recoverable Grants These start as grants but are repaid only if success metrics (e.g., revenue, profitability) are met. Great for: early pilots, MVPs, and validating models Bonus: if repaid, funders can recycle the capital into other impact ventures Watch out for: unclear terms. Define milestones and triggers carefully to avoid misalignment. 2. Revenue-Based Financing You repay a percentage of your revenue until a cap is reached. No fixed monthly repayments, no dilution. Great for: social businesses with seasonal or recurring revenue Benefit: aligns investor return with your growth curve Caution: it’s easy to underestimate how long repayment takes. Structure fair caps and repayment windows. 3. Convertible Grants or Notes These begin as grants or zero-interest loans, but convert to equity if you raise future funding. Great for: ventures aiming to raise institutional or VC funding later Benefit: de-risks early-stage fundraising Consider: conversion terms, dilution protection, and timeline to next round 4. Blended Finance / First-Loss Capital Philanthropic funders take on more risk (often the “first loss”), making it safer for other investors to come in. Great for: attracting larger institutional or private funders Especially useful in education, health, climate, and rural markets Complexity: requires sophisticated legal structuring and strong accountability 5. Equity Investment from Philanthropic Capital Some foundations and high-net-worth individuals are now investing in equity, especially through donor-advised funds (DAFs) or program-related investment (PRI) vehicles. Great for: high-growth ventures with clear impact and long-term potential Benefit: aligned capital with patient expectations Legal note: this is still uncommon and regulated. Ensure your investors are legally set up for equity, and have an agreed mission lock to avoid drift. Bonus structures to explore: - Quasi-equity (profit sharing) - Patient capital (long-term, low-interest loans) - Catalytic grants for systems change - Hybrid capital stacks (mix of grant + debt + equity) If you’re a social entrepreneur: Capital isn’t just money. It’s relationship, structure, and timeline. Design your capital stack to reflect your values, your model, and the communities you serve. And don’t be afraid to educate funders. Many want to help, but don’t know how. Your enterprise deserves capital that works as hard, and as wisely, as you do.

Insights about diversified vs concentrated portfolios for LPs/GPs of pre-seed/seed funds from Stefano Bernardi – great analysis and table! Most LPs push for concentration (15-20 companies + follow-ons). But the math/logic of diversification may be more attractive for early-stage funds. 1. FoF concentration logic may be backwards. 10-15 concentrated funds of 15-20 companies = 150-300 total exposure. If the vintage winner isn't there, the entire FoF underperforms. Diversified funds (50-70 companies each) = 500-700 exposure. At pre-seed, several funds with 2-4% at $5-10M valuations might beat one fund with 15% at $20M. Don't optimize for look-through ownership – optimize for "don't miss the winner." 2. "Reason to win" is the most ignored variable. Concentrated: "Need to be chosen as lead, show ability to win." Diversified: "Friendly, fast, well-loved by co-investors." One requires winning 20+ competitive battles. Other requires being helpful capital. Which can you actually deliver? 3. Ownership is a result, not an input. Stop designing around the target %. Start with: what check sizes can you win, what valuations can you access, what's your reason to win. Ownership falls out of these. 4. The market won't supply 20 in-thesis companies. Even if you see great deals and could win them, the market might not produce 20 quality companies in your thesis during 2-3 years. Plus bandwidth to service them. 5. Follow-on reserves have hidden costs. $70M with 50% reserves vs $35M no reserves: 2x fundraising effort, predict winners early, win allocation, avoid squeeze-outs. Still only drops exit from $21.5B to $15B. 6. Solo GP bandwidth breaks by Fund III if leads 20 rounds in Fund I. By Fund III: servicing Fund I + Fund II portfolios + new investments. Diversified strategy – "essentially infinite capacity." 7. Entry valuation access matters. $1.5M checks → $20M rounds. $250K checks → $4-10M rounds. Multiple small positions at low valuations often beat one large position at a high valuation. 8. Top investors won by volume, not hit rate. They got there by the number of shots, not prediction accuracy. Even best can't consistently predict which pre-seed becomes $10B+ outcome. 9. Best seed funds were highly diversified. Lowercase I: ~80 investments. First Round: 20-25/year. SV Angel: hundreds. Power laws reward surface area, not magic. Full article: https://lnkd.in/dQd99amx

Venture capital is full of noise - narratives, anecdotes, and opinions. Over the past few years, I’ve worked to cut through that by doubling down on data: dissecting the structural traits of this asset class, from illiquidity and vintage diversification to the nuances of fund math. As an LP, digging into private and public datasets has given me a sharper view of how allocation decisions are made - and revealed how little of this analysis is shared for other GPs and LPs to learn from. That’s why I’ll be sharing these insights more consistently through "𝐒𝐢𝐠𝐧𝐚𝐥𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐍𝐨𝐢𝐬𝐞" - my data-driven lens on how LPs approach venture allocation, with a focus on uncovering the insights hidden in the data. Whether zooming in on Canadian venture or zooming out to global trends, my aim is to provide frameworks that GPs and LPs can apply to their own decision-making. So where to start? First post below 👇 𝐏𝐨𝐬𝐭 𝟏 – 𝐖𝐡𝐲 𝐝𝐨 𝐬𝐦𝐚𝐥𝐥𝐞𝐫 𝐕𝐂 𝐟𝐮𝐧𝐝𝐬 𝐨𝐟𝐭𝐞𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐞 𝐭𝐡𝐞 𝐬𝐭𝐫𝐨𝐧𝐠𝐞𝐬𝐭 𝐆𝐏–𝐋𝐏 𝐚𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭? 𝐓𝐡𝐞 𝐚𝐧𝐬𝐰𝐞𝐫 𝐢𝐬𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐨𝐮𝐭𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 - 𝐢𝐭’𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐞𝐜𝐨𝐧𝐨𝐦𝐢𝐜𝐬. In venture, we’ve all heard that “small funds outperform.” That deserves its own deep dive (coming later 👀), but the real strength of smaller funds often gets overlooked: 𝐭𝐡𝐞 𝐚𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭 𝐨𝐟 𝐢𝐧𝐜𝐞𝐧𝐭𝐢𝐯𝐞𝐬 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐆𝐏𝐬 𝐚𝐧𝐝 𝐋𝐏𝐬. With smaller funds, there’s only one path to wealth creation - carried interest. And that’s where alignment is sharpest. My analysis makes this clear. Looking across six real funds with different sizes and partner counts, I calculated the Net TVPI needed for each partner to generate $50M: • Fund A ($1.2B, 8 partners) → 𝟏.𝟓𝐱 Net TVPI • Fund F ($15M, 1 partner) → 𝟏𝟑.𝟓𝐱 Net TVPI - 𝟗𝐱 𝐡𝐢𝐠𝐡𝐞𝐫! This shows why smaller-fund GPs must chase outlier outcomes and bring a level of grit and hustle often absent at larger platforms. Even more telling is comp mix. For Fund A, 60% of the $50M comes from fees - guaranteed regardless of performance. For Fund F, 95% is entirely variable, fully tied to carry. And that’s the key. 𝐋𝐏𝐬 𝐨𝐧𝐥𝐲 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐰𝐞𝐚𝐥𝐭𝐡 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐜𝐚𝐫𝐫𝐢𝐞𝐝 𝐢𝐧𝐭𝐞𝐫𝐞𝐬𝐭 - and in smaller funds, that’s exactly where GPs focus. 𝐒𝐨, 𝐰𝐡𝐚𝐭 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬? 𝟏. 𝐑𝐮𝐧 𝐭𝐡𝐞 𝐍𝐮𝐦𝐛𝐞𝐫𝐬: LPs should model net fund performance needed for each partner to earn $10–50M. Low hurdles from large funds or oversized partnerships weaken incentives. 𝟐. 𝐁𝐢𝐠 𝐅𝐮𝐧𝐝𝐬 = 𝐁𝐢𝐠 𝐅𝐞𝐞𝐬, 𝐒𝐦𝐚𝐥𝐥 𝐅𝐮𝐧𝐝𝐬 = 𝐓𝐫𝐮𝐞 𝐀𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭: Large funds rely on fees, insulating partners from performance. In smaller funds, carry dominates — creating sharper GP–LP alignment. 𝟑. 𝐂𝐚𝐫𝐫𝐲 𝐢𝐬 𝐭𝐡𝐞 𝐎𝐧𝐥𝐲 𝐏𝐚𝐭𝐡: In small funds, GPs earn meaningful wealth only through carry — the same source of returns for LPs. This is just the start of Signals in the Noise 🤓

I built an interactive dashboard comparing VC fund performance across Thrive, a16z, Founders Fund, Lightspeed, Insight, Khosla, and Tiger Global. 49 funds. Net TVPI. DPI. IRR. After putting everything side by side, the pattern was hard to ignore: Scale compresses returns. When funds were smaller, multiples were meaningfully higher. As fund sizes increased, TVPI and IRR consistently trended down. This is not a critique of any one firm. These are some of the best investors of the last two decades. It is simply math. A $300M fund can generate a 4x outcome with a handful of breakout companies. A $5B+ fund needs multiple multi-billion dollar outcomes just to move the needle. That changes behavior. It changes entry price. It changes ownership targets. It changes risk tolerance. And most importantly, it changes the return profile. What stood out most: • Earlier vintages and smaller vehicles tended to show stronger TVPI • Larger, later-stage oriented funds showed tighter dispersion and lower multiples • DPI timing matters more than headline IRR • Unrealized markups can mask true performance until cycles turn The industry loves talking about AUM growth. LPs often anchor to brand, access, and scale. But scale comes with structural tradeoffs. If you are allocating capital, the real question is not “who is the biggest?” It is: Where is the strategy most structurally advantaged? Sometimes that means smaller funds with sharper focus. Sometimes it means early concentration over late diversification. Sometimes it means accepting volatility in exchange for true asymmetry. The dashboard makes one thing clear: Venture returns are not linear. They are capacity constrained. Curious what others see in the data. Full dashboard here: https://lnkd.in/eFV4MZn3

𝗪𝗲'𝘃𝗲 𝗰𝗼𝗺𝗽𝗮𝗿𝗲𝗱 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝘃𝗲𝗻𝘁𝘂𝗿𝗲 𝘀𝘁𝘂𝗱𝗶𝗼𝘀 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗩𝗲𝗻𝘁𝘂𝗿𝗲 𝗦𝘁𝘂𝗱𝗶𝗼 𝗖𝗼𝘀𝘁 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗠𝗼𝗱𝗲𝗹. When evaluating venture studios, capital allocation patterns provide a window into strategic focus and risk appetite. The VSCSM framework enables investors to decode these patterns by standardizing how different studios deploy capital across five key categories. Take the hypothetical, but directionally representative, capital allocation models for four distinct venture studio strategies below. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟰 𝗸𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗿𝗲𝘃𝗲𝗮𝗹𝗲𝗱 𝘁𝗵𝗮𝘁 𝗶𝗻𝘃𝗲𝘀𝘁𝗼𝗿𝘀 𝘀𝗵𝗼𝘂𝗹𝗱 𝗸𝗻𝗼𝘄: 1. 𝗖𝗼𝘀𝘁 𝗼𝗳 𝗕𝘂𝗶𝗹𝗱𝘀 𝘀𝗵𝗼𝘄𝘀 𝗵𝗼𝘄 𝗺𝘂𝗰𝗵 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗻𝗲𝗲𝗱𝗲𝗱 Deep tech studios allocate 45% of capital to building new companies which is nearly double PE-focused studios (25%). This reflects higher technical risk and more experimentation before reaching product-market fit. The percentage dedicated to builds directly correlates with the technical risk and innovation intensity. Frontier tech studios require more resources for validation and development. 2. 𝗘𝗾𝘂𝗶𝘁𝘆 𝗽𝗲𝗿 $𝟭𝗠 𝗶𝗻𝘃𝗲𝘀𝘁𝗲𝗱 𝘃𝗮𝗿𝗶𝗲𝘀 𝘄𝗶𝗱𝗲𝗹𝘆 Cashflow studios earn 110% equity per $1M, while deep tech studios get just 19.1%. This reflects different ways value is created and captured. Across studio types: Deep Tech: 19.1% ($52,307/pt) Traditional Venture: 21.8% ($45,918/pt) PE-Focused: 37.5% ($26,666/pt) Cashflow: 110% ($9,090/pt) 3. 𝗙𝗼𝗹𝗹𝗼𝘄-𝗼𝗻 𝗮𝗹𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗽𝗼𝗶𝗻𝘁 𝘁𝗼 𝗲𝘅𝗶𝘁 𝘁𝗶𝗺𝗶𝗻𝗴 Traditional venture studios allocate up to 25% to follow-ons, anticipating future raises. Others allocate less, implying shorter holds or earlier exits. Follow-on reserves signal assumptions around exit timelines and capital needs. PE and cashflow studios often hold 0% follow-on, given clearer acquirer paths or early cash generation. 4. 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 𝘀𝗶𝘇𝗲 𝗿𝗲𝗳𝗹𝗲𝗰𝘁𝘀 𝗿𝗶𝘀𝗸 𝗽𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲 With similar fund sizes, PE-focused studios built up to 25 companies vs. 14 for venture studios. More companies reduce single-asset risk but increase dilution and stretch resources (a strategic tradeoff.) 𝗪𝗵𝗮𝘁 𝘁𝗵𝗶𝘀 𝗺𝗲𝗮𝗻𝘀 𝗳𝗼𝗿 𝗶𝗻𝘃𝗲𝘀𝘁𝗼𝗿𝘀: Capital allocation patterns reveal the studio's true strategy, beyond marketing language. Deep tech studios with high build costs and substantial follow-on reserves have fundamentally different risk profiles than cashflow studios with minimal follow-on and higher company counts. If you're evaluating a studio (on fee structure or upside) this framework can reveal how aligned their operating model is with outcomes you're hoping for. A venture studio might say "we build companies" in their deck. But the way a studio spends its money tells you "how."

Point72's 19% 2024 return isn't luck—it's organizational design solving a math problem. Most quants optimize signals. Point72 optimized the portfolio construction layer itself: 190+ independent pods, each running 6-12% gross per name, factor-paired to isolate alpha from systematic risk. The edge? Portfolio Sharpe amplification through low-correlation aggregation. If 10 pods each deliver Sharpe 1.5 with 0.2 avg correlation: Portfolio Sharpe ≈ 1.5 × √(10/(1+9×0.2)) ≈ 2.9 (Illustrative framework—actual portfolio Sharpe depends on additional factors) Apply 2-3x leverage → consistent 15-20% targets at institutional scale ($41.5B AUM). 📊 What actually matters: → Cubist (45% allocation): 500+ employees running discrete PM teams + centralized research infra. Recent hires from Tower, WorldQuant, Pattern Research. → Risk architecture: Dynamic capital reallocation on rolling Sharpe + factor-neutral constraints. Mid-single-digit drawdown = 50% allocation cut. 10% loss = pod termination. → The 2026 play: Dual-brand split (Point72 Equities + Valist) while sharing risk infrastructure. Relationship arbitrage at scale—banks limit insight sharing with dominant players. ⚡ Key insight: They're returning $3-5B to investors despite strong performance. Why? Market impact scales nonlinearly. Even pod architecture hits physical limits at $40B+. This isn't portfolio construction—it's solving capacity constraints through structural innovation. Full breakdown: mathematical frameworks, talent moves, Q3 13F positioning, private credit economics, and why multi-strategy funds are an organizational design problem disguised as trading. Link: https://lnkd.in/gfcSG72U #QuantFinance #HedgeFunds #SystematicTrading #AlphaGeneration #PortfolioManagement #RiskManagement #MultiStrategy #QuantitativeResearch #AlgorithmicTrading #FinancialEngineering #Finance #Investing

Private equity (+ credit) is drowning in AI noise. Every PE partner I talk to has the same problem: 100+ cold emails about AI tools, occasional ChatGPT use, but 𝗻𝗼 𝗰𝗹𝗲𝗮𝗿 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 for where AI actually moves the needle for their fund. Our niche is data & AI transformation for PE. I've found it comes down to focusing on 4 critical areas (in no particular order): 𝟭. 𝗙𝘂𝗻𝗱𝗿𝗮𝗶𝘀𝗶𝗻𝗴 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Stop spraying and praying with LPs. AI can systematically identify and score potential LPs based on investment patterns, portfolio fit, and timing signals. Your team should be spending time on high-conversion conversations, not cold outreach. 𝟮. 𝗢𝗿𝗶𝗴𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗮𝘁 𝗦𝗰𝗮𝗹𝗲 The best deals aren't on everyone's radar. AI can surface off-market opportunities by analyzing alternative data sources and pattern-matching against your investment thesis. Screen 10x more deals in the same time, but only dig deep on the ones that fit your platform or add-on strategy. 𝟯. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗗𝘂𝗲 𝗗𝗶𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Yes, every deal feels unique. But 80% of your diligence process follows repeatable patterns. Map out your "special sauce" diligence framework once, then let AI handle the routine analysis while your team focuses on the truly deal-specific insights. 𝟰. 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 If your monthly reporting cycle is a fire drill of Excel gymnastics and last-minute adjustments, you're leaving value on the table. Clean data pipelines from portCo's → fund → LP reporting should be table stakes. If I were a PE CTO today, I would 𝘀𝘁𝗼𝗽 𝗳𝗼𝗰𝘂𝘀𝗶𝗻𝗴 𝗼𝗻 𝗔𝗜 𝘁𝗼𝗼𝗹 𝘀𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻. Instead, I would start by picking one of these four areas and 𝗴𝗼𝗶𝗻𝗴 𝗱𝗲𝗲𝗽. The compound effect of getting even one of these right will transform how my fund firm operates.

Your peer just raised $1 million from one foundation, while you raised the same amount from 20 funders. Your peer is spending this month planning the year's strategy, mapping long-term impact, and building meaningful partnerships. You're drowning in waves of application deadlines, 20 different portals, and dozens of relationships you struggle to deepen. The revenue looks identical on your balance sheet. Grant seekers are burning out, even compared to just a couple of years ago. It’s harder to get funders’ attention. It’s harder to write applications that stand out. It’s harder to understand what it takes to succeed. This is the volume trap. It's costing organizations more than they realize. Rather than dwelling on it, you can offset these challenges with the knowledge that you can take action: Foundations are writing larger checks. They're issuing more unrestricted awards. They're seeking partnerships over transactional relationships. They’re cultivating deeper rapport with fewer grantees. That’s a better use of their time than reviewing hundreds of applications from organizations they'll never fund. If your organization has won some private awards, this is your moment to shift your focus toward major grants. Start by identifying 5-7 foundations whose missions align with yours at the DNA level. It must be a strategic fit where your work advances their most central priorities. Build real relationships with program officers built on insight, not updates. Share what you're learning from the field. Discuss emerging trends. Ask thoughtful questions about their strategy. Position yourself as the organization they can't afford to overlook when transformational opportunities arise. When I worked in-house, foundation staff called me for a range of reasons. They asked for advice, recommendations, and yes, to ask whether we could talk about an investment. That didn’t happen by accident. It might feel tempting to go after every potential opportunity that comes across your screen. You might even spend your days scouring databases or your AI provider for new investors. Before you do, ask yourself whether you’ve maximized the relationships already in your portfolio. The long-time funders. The lapsed ones. Those where you might have received some promising signals. My clients hear regularly from funders because we’ve worked to make them a resource, not just a grantee. Their experience reflects what we mean by “partnership” when we talk about foundations. When you make time to show a foundation the mutual gains when you work together, benefits emerge on both sides. When you see your peers winning major grants, it’s unlikely they’re the ones submitting the most applications. They're the ones foundations call first.