Michael Skok

Boards are supposed to help founders. Over the past 19 years, I've watched many trap them instead. As companies scale, many boards turn from insight to oversight and stop doing what founders actually need: Help making big, hard decisions. Early boards tend to be small, the board members are close to the business and highly invested in it. They argue from first principles. They help founders think. Later-stage boards often look more impressive on paper - they have more independent directors, committees and process. Somewhere along the way, collective problem solving gets replaced with oversight. The board shifts from helping the CEO make better decisions to monitoring decisions that have already been made. Strategy discussions get safer, real debate gets rarer and meetings become more about risk management than judgment. This usually coincides with the introduction of more professional board members. For better or worse, they often optimize for governance, optics, and liability management. That’s their job. But it’s not always what the company needs in moments of real uncertainty. Then, CEOs stop using them as thought partners. That’s a problem. So what should founders do? A few principles that help: • Keep the board as small as you can for as long as you can • Add directors for new insight they bring, not what boxes they check • Treat board seats like senior hires, not trophies • Design meetings for debate rather than reporting • Be explicit about when you want input vs approval Good boards should improve decision-making. If your board isn’t making you think harder, it’s probably not doing its job.

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Which is the best LLM for Venture Capital / Private Equity use cases? I've heard this question from more GPs and Operating Partners than I can count. And on the surface, it sounds like the right question to ask. But here's the reality: 𝗧𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗶𝘀𝗻'𝘁 "𝘄𝗵𝗶𝗰𝗵 𝗺𝗼𝗱𝗲𝗹." It's "𝗵𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝘄𝗵𝗶𝗰𝗵 𝗼𝗻𝗲 𝗶𝘀 𝗿𝗶𝗴𝗵𝘁 𝗳𝗼𝗿 𝘁𝗵𝗶𝘀 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻?" Most firms pick one LLM and hope it works across every use case: → Due diligence reports → Market analysis → Integration planning → Risk assessment Then they're surprised when responses vary wildly in quality. Or when the model that's great for financial analysis fails at strategic synthesis. 𝗧𝗵𝗲 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝘁𝗿𝘂𝘁𝗵? Different models excel at different tasks. Even within PE workflows. So instead of picking one LLM and crossing your fingers... What if you could let the models evaluate each other? That's exactly what our LLM Council does. Here's how it works: Stage 1: First Opinions → Your question goes to multiple LLMs simultaneously → Each responds independently → You see all answers in a tab view Stage 2: Anonymous Review → Each LLM reviews the other responses (identities hidden) → They rank them on accuracy and insight → No model favoritism - just quality assessment Stage 3: Final Synthesis → A designated Chairman LLM compiles everything → Takes the best insights from each response → Delivers one comprehensive answer The result? Not just one model's perspective. A deliberated, cross-validated response backed by multiple AI systems evaluating each other. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝘆𝗼𝘂𝗿 𝗠𝘂𝗹𝘁𝗶-𝗠𝗼𝗱𝗲𝗹 𝗔𝗜 𝗔𝗱𝘃𝗶𝘀𝗼𝗿𝘆 𝗕𝗼𝗮𝗿𝗱. The question isn't which LLM is best. It's whether you're using the right methodology to find out. You are now or will be making critical decisions based in AI outputs, the question is how will you hire the right LLM for the job?

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🚨NEW EPISODE: Recorded live at FUTURE TITANS 2026 - Jeff Perry of Carta sat down with the iconic Seth Levine, co-founder of Foundry. Seth has been in venture for 25 years, built Foundry from scratch as an emerging manager himself, and has backed about 50 emerging manager funds through his fund of funds. He has genuinely seen every side of this table. They went deep on building Foundry, why VCs are in the influence business, not the decision business, and why the concentration problem in venture is not only bad for LPs, but also for the innovation ecosystem overall. And why Seth's new book, Capital Evolution, is so important for the future of America. 🎧 Links to listen... Apple: https://lnkd.in/ehQUQ2EM Spotify: https://lnkd.in/eU4FExpg

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For all founders, especially tech founders, here are a few key insights on how to elevate your pitch. Definitely worth a read and some thought... Treeo VC https://lnkd.in/emM8RK_4

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SF VC Takeaway #2: Pricing expectations, performance bars, and what’s actually getting funded. One theme that came up repeatedly in SF was how far pricing expectations and performance bars have shifted, even compared to just a few years ago. A few things investors kept anchoring to: 1️⃣ Median Series A valuations are higher than their 2021 peaks, but fewer of them are getting done. 2️⃣ Capital is being concentrated into fewer and fewer companies (and lots of capital!) 3️⃣ “Good” progress is no longer enough and the bar for standout performance has moved in an AI-native world So what does “top performance” mean right now? One investor told me that top quartile seed companies in their portfolio are going from $0 to $2M in ARR in <12 months. Outside of pure traction numbers, a few other themes that came up to describe "top performance": 📈 Explosive early revenue ramps (or a very credible path to them) 📊 Strong velocity and momentum for 2 quarters in a row, even if the baseline is small. 🚀 Clear signals of category leadership, not just product-market fit. Sometimes shown by either domain expertise, speed of product optimization, or by lack of competition in the category. This creates a counterintuitive dynamic where it can be easier to fund a company with strong pedigrees in a hot space and no traction yet than a company that went from 0 to $1M ARR at what used to be considered a rapid pace. Pricing today is driven by trajectories, not moments in time. We used to say investors invest in lines not points; I think that's more true than ever now because crossing certain milestones doesn't carry as much influence as it once did. Finally, investors still say that valuation matters, but many of them are acting differently. Pace and belief in category-defining companies really sets the price; while slower growth gets scrutinized rather than discounted. One silver lining in the camp of durable growth: Series A rounds are happening so fast that many companies don’t yet have meaningful history of retention data. Large bets are being made on velocity before the durability is proven. Several investors told me the same thing: we may soon swing back to a market where retention, not growth, becomes the defining metric. Let's hope so. I'll share my third SF VC takeaway tomorrow!

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