Rob Pankow

Y-Combinator Guide To Seed Fundraising Every Founder Needs to Read This Guide Includes: 1. Why Raise Money? 2. When to Raise Money How Much to Raise? 3. Financing Options Convertible Debt Safe Equity 4. Valuation: What is my company worth? 5. Investors: Angels & Venture Capitalists 6. Crowdfunding 7. Meeting Investors 8. Negotiating and Closing the Deal 9. Negotiations 10. Documents You Need 11. How Does VC Fundraising Work? 12. A Brief Glossary of Key Terms ~~~~~ ♻️ Found this helpful? Repost it so your network can learn from it, too. And follow me, Fazlur Shah for more content like this. #startups #entrepreneurship #venturecapital #investing

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🤑 How to raise VC without wasting 6 months 🤑 Most founders drag out fundraising for months when it should take 6-10 weeks. Why? Because they treat it like an open-ended process instead of a structured sprint. Here’s how to raise faster, get better terms, and avoid fundraising purgatory: ✅ Before You Start: Set Yourself Up for Success -> If you have great metrics & momentum, start building investor relationships months in advance. -> If you don’t have great metrics, don’t pre-sell your raise—it may work against you. -> Get in as many practice reps as you can before pitching top investors. You will get better each time. -> Be careful teasing an upcoming product milestone—investors may just wait to see if it works. ✅ Control the Timeline -> Schedule meetings in a tight 3-4 week window. Rolling, one-off meetings = death. -> Set deadlines. “We’re aiming to finalize commitments by X date.” -> Series A rounds are taking 5-7 months now—so running a tight process is more important than ever. ✅ Engineer Momentum (Don’t wait for It!) -> Use phrases like “We’re seeing a lot of excitement from investors” (even if it’s early). -> Let funds in your pipeline know when you advance to each next stage: diligence, partner meeting, term sheet. It will accelerate them if they want to stay in the game. -> If an investor isn’t chasing you, they’re probably not interested. Still close the loop—a thoughtful “no” and feedback is invaluable. -> Founder-to-founder intros are gold. The best way to get fast-tracked into a fund. ✅ Know When to Walk Away 🚩 Investors dragging their feet? Asking for endless follow-ups? Saying “we like it, but need more time”? Move on. If you structure your raise instead of letting it drag, you can close a round in weeks, not months. What’s your best fundraising hack? 👇

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It’s sometimes said that European VC doesn't have the firepower to compete with US VC, which regularly raises billion-dollar+ funds. Berlin's Cherry Ventures has closed its latest fund at $500m to back what it calls "trillion-dollar startups - although evidence that European startups are currently on the trillion-dollar path remains thin on the ground.

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Get genius at the snap of your fingers. Hiring full-time has never been more expensive for early-stage startups. But there’s a 10x cheaper arbitrage hiding in plain sight: SWE and GTM interns. Most founders try to hire an army of full-time talent 🚫 No guarantee they’ll execute 🚫 No flexibility if they don’t 🚫 Burn rate that kills runway Meanwhile, the smartest teams are building lean, high-impact intern pipelines. The math is simple: $10K/mo for a full-time hire vs. $1k/mo for a top student. That’s 10 shots on goal for the cost of one “maybe.” And if they’re a 10x candidate? You hire them full-time, with zero downside risk. And here’s the bigger picture: AI is commoditizing code. Playbooks exist for every GTM motion. The real competitive edge isn’t just talent It’s how fast you can test, iterate, and scale. We started with interns plugging engineering + GTM gaps. Now we’re powering growth for: ✅ YC-backed startups ✅ Series A/B scaleups ✅ Founders without HR teams ✅ Ecosystems launching talent at scale Every month, new use cases expand this market by 10x. The $100B vision is clear: Rounds.so becomes the “AWS of talent” for startups. On-demand. Flexible. Guaranteed. Startups don’t need bloated teams. They need velocity. And interns, are the ultimate growth hack.

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An ex-Deutsche Bank executive recently asked me: "We already can automate processes in finance. So why do we need crypto and programmable money?" He’s right, automation does exist. But the way it works today has limits. The key issue is that the infrastructure that moves money today is disconnected from the layer that lets money "do things", like reacting to events, trigger payments, or enforce conditions. As a result, automation in TradFi requires stitching together multiple systems, APIs, and middleware, which makes it quite complex and costly. In Web3, that's different. On blockchains (more specifically smart contract platforms like Solana or Ethereum), money isn’t just a database entry as it is in traditional finance – it’s code. It can carry conditions, permissions, and triggers, and it can natively interact with computer programs. In other words: money itself becomes part of the software. This unlocks capabilities that traditional rails simply cannot offer: ▶️ 𝗕𝘂𝗶𝗹𝘁-𝗶𝗻 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲: Tokens that only move between pre-approved, whitelisted addresses, with the rules enforced directly by the asset. ▶️ 𝗖𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗽𝗮𝘆𝗺𝗲𝗻𝘁𝘀: Funds are released automatically when predefined events occur, for example when a shipment is confirmed as delivered. ▶️ 𝗬𝗶𝗲𝗹𝗱 𝗿𝗲𝗱𝗶𝗿𝗲𝗰𝘁𝗶𝗼𝗻: Interest generated by a token can be routed instantly into loan repayment or split across multiple wallets. ▶️ 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗮𝗯𝗹𝗲 𝘀𝗽𝗲𝗻𝗱𝗶𝗻𝗴: Tokens can be restricted to certain purchases or set to expire after a specific date, encouraging certain use. Another key unlock is composability. In Web3, rules and automations can plug into each other directly and seamlessly, because they all live on one layer. The result is infrastructure that is faster, leaner, and more flexible than anything we can patch together on today's rails. And this is why it's needed.

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Vibe VC #01 Locked Token Discount Calculator We looked into bunch of OTC deals recently. Lock-up discounts is sth always bother us. How much discount for 6 month lock? Everyone has their own mental math, but there’s no baseline. So I pull Deribit implied vol, ran it through Black-Scholes, and built a simple frontend. Suddenly that vague back-and-forth over discounts becomes a number you can point to. Which also gives us a floor to negotiate from. ⸻ I started with Claude in plan mode. First we looked at how traditional finance prices restricted stock. Then I had it summarize academic work on crypto discounts. After a few iterations, we landed on using Deribit and Binance data as inputs. Added a frontend so teammates could just type in variables and see the discount rate. BTC and ETH set the baseline. They have real options markets, so we pulled the nearest two expiries, interpolated or extrapolated to the lock-up horizon, then priced with Black-Scholes. That number reflects both the upside you’re giving up and the downside protection cost. Other tokens usually don’t have that depth of market data. Two ways around it: use historical vol, or proxy off BTC and adjust by correlation. The output shows both discount rate and annualized figure, along with the source data, so everyone sees the same reference point. Makes it harder to argue. There’s a link in the comments if you want to play with it. Any feedback—on how it looks or how the numbers are calculated—would be great. ⸻ A few take: - This was really just connecting a data pipeline. Scripts did the math, frontend displayed the result. No LLM text generation, no context issues, no hallucinations. Still, watching it run live as a web app was a nice dopamine hit. - Claude Code is powerful. Fun to use, but expensive. I blew through the $200 plan way too fast. Token efficiency is something I’ll need to manage better—maybe mix Claude Code, Codex, Gemini CLI depending on the task. - Writing the scripts forced me to internalize the math. From pulling IV on Deribit, to pricing with Black-Scholes, to interpolation, to picking a risk-free rate. Each step matters, and once you see it, it’s easier to explain. It also raises the question: should VC conviction get priced in? Right now the formula is neutral on future prices. But if you expect a token to outperform, there’s probably a way to reflect that. Funny how wanting to “just talk” actually makes you dig deeper into the workflow. - Debugging pain points were almost never local. Claude handled local bugs fine with enough context. The tricky part was deployment—cloud configs, env params, external settings. You had to paste in the whole picture before it could actually solve it. - Commits were smooth too. Claude wrote them clearly. I even had OpenAI agent mode read through commit history, flag where I got stuck the most, and log the patterns into a Claude.md file. Basically a feedback loop to move faster next round.

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American retirees are profiting from German innovation 50x more than Germans themselves. US pension funds indirectly own 10% of German start-ups. That’s €4.7 billion in value created for US retirees. German pension funds own just 0.2%, or €94 million. Germany is not an exception, this is the case for most of European pension funds. So, European workers are paying into a system that refuses to back their own innovators. Meanwhile, America happily compounds the upside of Europe’s future. We need to change the incentives for European pension funds to bringing the allocation for venture capital up from 0.007% to at least 1% (1.6% in the US). This tiny change would be a total gamechanger for Europes technology ecosystem and global competitiveness.

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Anti-VC posts love to paint founders as victims. “The board will control you.” No, they hold you accountable and challenge your thinking. The good ones bring pattern recognition from other portfolio cos and bring perspectives you don’t yet have. “You’ll be underpaid. No liquidity." True at the start. But comp usually catches up fast if you’re performing well. And equity is the real payday, whether through an exit or a growing secondary market. If you build something people want, you’ll get yours. The real issue isn’t any of those. It’s that most founders sign up for a game they don’t fully understand. Let’s run the numbers. You raise 20 million. Investors expect at a 3x return. That’s 60 million back to them. To understand the challenge of that: Imagine paying that back that through profits alone. You’d need 20 million a year in net profit for three years straight. At 40% margins, that’s 50 million ARR. At venture-style return expectations, you’re suddenly building for a 100 million plus ARR company. Most founders don’t do this math when they celebrate their raise. It’s a problem for later. The minute you raise, you set something in motion. I’ve rarely seen a founder do a seed and just stop there. Closing one round almost immediately puts you on track to start preparing for the next. That’s what raising VC really is: the Olympics of business. The bar is higher, the odds are lower, and the effort required is extraordinary. Bootstrapping is a different game and is gaining popularity. Because: You get instant market feedback. You have a year, maybe less, to find out if people care. You live inside cashflow constraints, which is brutal but keeps you honest. VC gives you 3 to 5 years of oxygen, which is incredible, but it can also postpone the moment of truth about whether you’ve built something people really want. And that comes with a massive opportunity cost: prime career-building years, often in your 20s, 30s, and 40s. When we started Sarwa, we weren’t thinking about ARR milestones or exit math. We just wanted to build something great. I’m grateful we’re now well past 10 million ARR and working toward our first 100 million ARR. But we had no idea what we were signing up for, how big it would need to get to clear the bar. Don’t get me wrong, I wouldn’t have it any other way if we were to start over. But I’m conscious that we’ve been incredibly lucky to cross these milestones. If you raise, raise with eyes open. That’s why I’m often of the opposite view of “take every dollar,” because a dollar taken today needs to be repaid in multiples tomorrow. You don’t get to play for a 2 million business anymore. You’re playing for a 200m million exit. And according to VentureBeat, only 4% of startups ever reach 1 million ARR, and just 0.4% make it to 10 million ARR. We all think we’re the exception to those numbers. Raising VC isn’t bad. It’s a wild ride. Just know what you’re signing up for.

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Forget Sequoia, is Greenoaks the New King of VC? Their Anti-Diversification Masterclass -------- Consider their recent wins since 2021: Windsurf: $60M invested -> $600M returned Wiz: $300M invested -> $2B returned A staggering $2.6 Billion in combined value generated from only two investments in four years. This isn't new for them. Since Neil Mehta founded the firm in 2012, Greenoaks have racked up over $13 billion in gross profits at a staggering 33% Net IRR. Henry Kravis, the founder of KRR who's also a LP in Greenoaks, said "Greenoaks probably returned more money to investors than anyone else" between 2020-2022." Perhaps most emblematic of their strategy was their early bet on Coupang, the "Amazon of Korea". Neil and his team invested 40% of their first fund into Coupang. No diversification, pure conviction. That single bet translated to $14 Billion when Coupang IPO'd in 2021. When most VCs zig towards spreading risks, Greenoak consistently zags with deep concentration. So far, this approach has been immensely profitable. -------- As we head into a decade dominated by AI, countless startups will be born to hyper-segment markets. Will that strategy continue to deliver this kind of outlier returns?

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