Kashish Gupta

2009: The financial crisis had crushed fundraising. Barely any new capital went into venture funds. Yet the vintages from those years went on to deliver some of the strongest returns in history. Fast forward to today (2024/2025): Venture capital fundraising is at its lowest point in more than a decade. What does that mean? - ⁠Less money will be available to startups over the next years - The bar for raising capital goes up again: quality matters - ⁠Entry valuations will reset to saner levels --> Funds raised now are likely to outperform, just as history shows The paradox of venture: the best time to commit capital is exactly when most people hesitate. Investors (Limited Partners) should lean in now, not when the next boom makes it easy.

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Product-market fit genuinely feels different...and it'll show up in the data Demo to close rates are the easiest thing to look at for product-market fit right now. Vertical AI startups in our portfolio are seeing 50%+ demo to close rates, even with brand new account executives selling the product. It's happening in every market from AI takeoffs to AI CSR/Voice software to AI procurement solutions. When you see a demo to close rate over 50% chances are you have a jaw dropping customer experience and you should put your foot on the gas. If you're seeing something dramatically lower in mid-market or SMB ACV categories, it's worth revisiting your product and/or your pitch.

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Fundraising isn’t just about capital — it’s about thinking beyond money. Cap Table | Capital | Control And non-negotiable benchmarks for early-stage fundraise 1. CAP TABLE → “Where do you stand today?”. - How much do founders collectively own? Goal:  Standard: End up with at least ~60% founder(s) stake (excl. ESOPs) at Series A Non-negotiable: Stay above 50% founder ownership post Series A (if possible). - Are ESOPs created or planned? (10% industry standard & higher than 15% is non-negotiable) - Any early angels or advisors already on the cap table? Thumb Rules (standard): - Pre-seed / Seed: Dilute ~10–20% - Series A: ~15–25% - Series B+: Varies, but total dilution across rounds shouldn’t cross ~40–50% by Series B/C if possible 2. CAPITAL → “How much do you need?” Raise only for next milestone with “high conviction.” - Model 18–24 months of runway. - Optimize according to your industry, not vanity round sizes. - Factor ~20% buffer for hiring, product, and GTM scale. Goal: De-risk vs time — to get to the next inflection point in the business. Mental Model: “Default Alive vs. Default Dilutive” Always ask: “Will this round put us on a stronger path to optionality—or does it lock us into future dilution cycles?” 3. CONTROL → “What are you giving away?” Not just dilution —but the rights - Who’s on the board post-round? Non-negotiable: No board seat below 5% ownership Non-negotiable: Retain decision-making control (board control) at early-stages. - Double check on veto / affirmative voting rights only agree to those which are for protecting adverse cases of investors. Goal: Maintain operating control and avoid misaligned governance. #Fundraising #VentureCapital #Startups

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Three kinds of AI startups I’m especially excited to invest in and work with these days: 1. The Surprisingly Valuable Niche Workflow — small enough for OpenAI not to care about; big enough to make $100M per year. Sooo so many opportunities out there, from logistics to finance to healthcare to construction to manufacturing and on and on. 2. The Full-Stack Software Company — founders are realizing they can move up the value chain, to not just sell software to other businesses, but use their own software to provide end solutions to customers. Our own portfolio has inspired us here, from industrial solutions to life science to agrochemical to admin services and more. 3. The Bold Consumer Bet — it’s time for a new generation of consumer mainstays that are AI-native and fit the way people use software today. We don’t often invest in consumer apps, but we have seen great examples of this in language learning, personal finance, fashion, dating, social, messaging, etc. All three are great examples of building at new frontiers of the software-addressable economy, where advances in AI have opened up new opportunities for software founders. A good litmus test for this thesis: “If I had this idea 5 years ago, could I build it?” If the answer is no or maybe, you’re on the frontier. If you’re building something cool in one of these areas — or anywhere else on frontiers of the software-addressable economy — please get in touch with us at character.vc We’d love to learn from you. And we’d love to share how we help founders bridge the gap from possible to PMF in these categories.

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YC is a behavioral training camp for high-agency founders… disguised as a funding program. The real output of YC is founders who operate on compulsion (not permission)   • The funding = It’s enough to survive, not succeed.   • The advice = Great, but a lot available in startup school vids.   • The brand = Powerful - but only if you do something with it. (plenty of static YC startups) So what does YC actually do? It rewires founders to act without waiting.   • Launch before it’s perfect.   • Email partners before you’re “ready.”   • Ask investors for intros before you feel credible.   • Charge customers before you finish the product. This is not just building a startup but learning to move before the world says yes. imo this is the sauce that most accelerators miss… They coach you to build a startup. YC trains you to become the kind of person who builds startups no matter what. It’s founder behavioral rewiring - YC turns people who ask for permission into people who build like it’s already theirs. That’s the asset. The company is just the vessel. PG says it similarly… “𝘞𝘩𝘢𝘵 𝘥𝘰 𝘐 𝘮𝘦𝘢𝘯 𝘣𝘺 𝘨𝘰𝘰𝘥 𝘧𝘰𝘶𝘯𝘥𝘦𝘳? 𝘔𝘢𝘪𝘯𝘭𝘺 𝘐 𝘮𝘦𝘢𝘯 𝘴𝘰𝘮𝘦𝘰𝘯𝘦 𝘸𝘩𝘰 𝘪𝘴 𝘳𝘦𝘭𝘦𝘯𝘵𝘭𝘦𝘴𝘴𝘭𝘺 𝘳𝘦𝘴𝘰𝘶𝘳𝘤𝘦𝘧𝘶𝘭. 𝘕𝘰𝘵 𝘮𝘦𝘳𝘦𝘭𝘺 𝘥𝘦𝘵𝘦𝘳𝘮𝘪𝘯𝘦𝘥 - 𝘵𝘩𝘢𝘵’𝘴 𝘯𝘰𝘵 𝘦𝘯𝘰𝘶𝘨𝘩 - 𝘣𝘶𝘵 𝘳𝘦𝘭𝘦𝘯𝘵𝘭𝘦𝘴𝘴𝘭𝘺 𝘳𝘦𝘴𝘰𝘶𝘳𝘤𝘦𝘧𝘶𝘭. 𝘛𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 𝘴𝘪𝘯𝘨𝘭𝘦 𝘮𝘰𝘴𝘵 𝘪𝘮𝘱𝘰𝘳𝘵𝘢𝘯𝘵 𝘲𝘶𝘢𝘭𝘪𝘵𝘺 𝘪𝘯 𝘢 𝘴𝘵𝘢𝘳𝘵𝘶𝘱 𝘧𝘰𝘶𝘯𝘥𝘦𝘳.”

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GPT-5 isn’t the leap many expected and that’s good for startups. When every release feels like a step change, model providers tend to absorb more of the value chain. Slower jumps mean more room for startups to build durable products, own distribution, and differentiate through workflow, UX, data, and domain expertise. Instead of being displaced by the next API call from the frontier, founders can double down on deep integrations and compounding advantages knowing the ground beneath them won’t shift overnight.

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