Gil Dibner

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Ross Haleliuk posted the fantastic article below. This is the world where I live day-to-day. At TechOperators, we invest mostly in early-stage cyber, but we do things a little differently, and we believe there are ways to invest successfully outside of pure Power Law math. The article argues that many security problems are too small for VC. I agree. I often try to convince bootstrapped founders not to raise venture because doing so can turn a successful, slow-growing bootstrapped company into a failed venture-backed company because, despite a large infusion of capital, it couldn't double every year. VC is not monolithic--not by stage, strategy, or style. Venture is often equated with "Tier 1 Venture". Ross argues that VC is not always great for early-stage cyber--and he is right. Bootstrapping AND VC work when incentives are aligned. Does it work for an early-stage VC with a <$200M fund to invest in several early companies at reasonable valuations, setting up the conditions for reasonable exits that pay off for both investors and founders? Yes. Does it work for $800M funds investing in seed stage at $100M+ valuations? Well, that depends! Power law says it does (for VC), but the unfortunate externality is that these rounds destroy companies and founder equity more often than not. There is a role for patient capital in this ecosystem to fuel successful companies that retain exit optionality as they scale--driving exit value for both founders and investors.

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Here’s a question investors are often asked: When evaluating early stage companies, how much time do you spend on due diligence around future exits? It’s not surprising we hear this question a lot. Also not surprising: it’s got a wide range of answers depending on the firm. Some don’t spend much time here at all. Others make it a point to put meaningful time in as part of their process. Our current thinking: take the time to do the work on public market comps. At Alpaca VC, we spend significant time understanding how public market investors will  realistically value a business based on margin profile, product, business model & TAM. In short, we want to know: how will this company be valued at scale when we get taken out? Yes, we can acknowledge that the journey toward exit is a windy road and that there may be pivots along the way, but there are still public market companies that have a business model similar to the early stage company you're evaluating. And you can always look at gross profit multiples if you think the margin profile will change over time. So we still do the work on the comps. Quantitative metrics we look at when making the comparison to public market comps include EBITDA multiple, revenue multiple, Gross Profit multiple or all of the above. As part of this process, it’s also important to factor in the public market company’s year-over-year revenue growth as this will also significantly impact the multiple it trades at. Simple example: if you have two public market companies with similar business models and similar margin profiles, but one's growing 100% year over year, and one's growing 50% year over year, then obviously the DCF (discounted cash flow) analysis is going to spit out a very different valuation for the one that's growing faster. Why this matters: When you take all of that information into account as you evaluate an early stage business, you can begin to create a realistic picture of how this company will be valued in the public markets at exit - or how an acquirer will value the company for an acquisition. Strategic acquirers may, of course, pay a premium, but we won’t underwrite for that. This allows us, for example, to form conviction around valuation based on revenue and gross profit predictions. If we think they can do $100M of revenue five years from now, we use this diligence process to form a thesis about whether the characteristics above (product, margin, business model, etc.) will cause the company to be valued at $200M vs. $500M vs. $1B at exit. Curious how other early stage investors think about underwriting an exit and how much time they’re spending on public market comps even though these companies are in their infancy.

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Elevate your networking game with our #SiliconValley VC contact list. Access 200+ #VC firms and 1800+ professionals, along with 1500 emails to help you make valuable connections. Learn more: https://payhip.com/b/eUIyc #venturecapital #startups #funding #startupfunding #startupinvestors #privateequity #founders #entrepreneurs

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What do you do when a radical new technology puts your main product right in the crosshairs of disruption? Listen to David Okuniev — co-founder of Typeform | Ask awesomely — discuss the challenges of innovation within existing structures. David shared a game-changing insight: Radical innovation is really, really difficult to do inside your own product. He emphasized the need to break free from the constraints of familiarity and embrace change from outside the box. Henrik Werdelin and I have both seen our fair share of this in our respective careers. What struck us most was how David leveraged structure to overcome the innovator’s dilemma. By creating a culture of experimentation and providing space for bold ideas, he propelled Typeform beyond incremental improvements. What other hacks have you seen or employed to help your organization overcome the innovator’s dilemma? Share your stories below! 👇 And if you want to dive deeper into our conversation, click the link in the comments to catch the full podcast episode!

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Today, we’re announcing our second fund of $450m to support our mission of partnering with early stage software companies that leverage technology discontinuities into go-to-market advantages. This marks the next chapter in our firm’s evolution. Since we launched Theory Ventures in 2023, we’ve gathered a wonderful team : Lauren DeMeuse, Spencer Farrar, Andy Triedman, Rafa Jara Simkin, Amber (., Arjun Mishra, & Kristin Beach. We have partnered with 8 marvelous founding teams, all using data to power the next wave of innovation across the Modern Data Stack, Artificial Intelligence, & Web3. We’ve grown our fund size to match the needs of founders in this market : average Series A rounds have increased 42% since our launch, a reflection of the growth potential of these software categories. I’m grateful to our team, our founders, & our limited partners for the continued support, & to Allie Garfinkle for sharing more about Theory (https://lnkd.in/gmD7zjSP).

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Key takeaways from VC Goat - Vinod Khosla podcast. - The firm cares more about working on interesting problems with large technical solutions rather than just maximizing IRR. The team is there because they believe in the mission. - Khosla assumes they've lost the money the day they invest, and then maximizes for the upside opportunity. He calls it "option value investing" rather than IRR investing. - Khosla has contrarian bets in AI (neuro-symbolic computing, probabilistic approaches), biotech, robotics, crypto, and more. - He believes aviation fuels, fusion energy, new transit systems, and other contrarian areas ignored by most investors will be huge opportunities. - Most large innovations come from outsiders, not industry insiders. Khosla looks for founders who can learn a business rapidly rather than have deep domain expertise. The Future Impact of AI - AI will be deflationary and increase productivity growth to 4% annually vs the typical 2% forecast. This will cause great abundance but also increasing income inequality. - Bipedal robots will take over most manufacturing and manual labor jobs within 20-25 years. This will free humans to be more creative and pursue their passions. - Education will shift from job training to creativity. Uniquely human elements like taste and curation will be most valued in an AI-enabled world. https://lnkd.in/gqBsmbks

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The future of VC is here: Scorecard.vc has relaunched with a TON of new updates! Free sign-up: http://scorecard.vc From automated matching and anonymous navigation to automatic deal syndication, KPI growth requests, and more, raising and deploying capital has become more efficient than ever. The result is a more powerful yet simplified experience, allowing Scorecard to act more like your VC virtual assistant. 🔥 🔥 🔥 Scorecard AutoPilot = Automated Matching 🔥 🔥 🔥 Our AutoPilot system will now find Investor thesis matches based for Startups, Funds, and SPVs raising capital, emailing you the results with quick actions to submit your review request. ✅✅✅ Anonymous + Verified Users = More Freedom & Trust ✅✅✅ All members on Scorecard are now fully anonymized, offering more freedom for Investors to review deals and engage with Startups, Funds, or SPVS raising capital. 👏👏👏 No More Profiles; Posts Only = Easier Navigation! 👏👏👏 Posts are free to create and used to run our scoring tech, and you only have to create your post once to start our automated matching. 🏁🏁🏁 Additional Investor Actions = More Updates 🏁🏁🏁 Investors can now anonymously view docs, request growth KPIs, soft-circle and syndicate deals, and message members raising capital ahead of requesting an introduction, and users will be anonymously updated with each Investor action. 🤝🤝🤝 Automated Deal Interest & Syndication = More Co-Investors! 🤝🤝🤝 For opportunities where Investors verify their interest, commit to invest, or deploy capital, Scorecard will automatically search for potential Co-Investors with a matching thesis to engage. ⚡⚡⚡ Credit System = More Value ⚡⚡⚡ Scorecard will now leverage a credit system for Startups, Funds, and SPVs raising capital. You will be given several free credits per month, and you can earn credits when new users sign up with your referral code. Members can also subscribe to an unlimited credit plan for an even more seamless experience. 📣📣📣 Scorecard Network = More Connections 📣📣📣 We will have some exciting updates soon, but our network of Investors, Startups, and Strategic Partners is growing quickly, with a “Source” tag to let you know where a member originated. We are even offering discounts and commissions to groups representing anyone in the VC space. We could not be more excited to launch Scorecard’s next stage of evolution. Know that we are continually focused on helping you succeed in VC, individually and as a community. Even more updates coming soon! Major thank you to our amazing team and community: Roger Derby Summer Crenshaw Navin Goyal MD Matt D.M. Watson, Ph.D., PMP Mike Torres LOUD Capital Buffy Alegria Ryan Retcher Darshan Vyas Nishad Parmar Marshall Kuremsky Blake Overlock Wolf Starr Jenny D, MD PhD Joey Glowacki Chad Warner Rory Billing Connor Billing Rivermint Capital Jesse Elliott LoudX

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In vertical SaaS, the very best companies landed with a product solving a specific, burning pain point that horizontal solutions solved badly and then became broad product suites over time (ServiceTitan, Veeva Systems, Doximity, etc). My partner Gordon Ritter calls this “layering the cake”. In vertical AI, the landing wedges are much more brittle. While the painpoints they solve are very real (and often unaddressable by SaaS alone), they’re also much more likely to commodotize in the near term as the tech advances. 👀 Therefore, the need to layer the cake in vertical AI is much more urgent than in vertical SaaS. 👀 The best vertical AI CEOs not only recognize the dynamic, but talk about it openly. Helps those around them keep up the speed of innovation and their eyes on the bigger prize.

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ex Google CEO Eric Schmidt spoke at Stanford this week. Lots of nuggets here, but most interesting for the near term, Schmidt believes in the next year AI is set to make a big leap forward. He predicts AI will combine three important features: 1. Vast knowledge retention (1 million token models) 2. Text-to-action capability 3. Personal AI agent fleets While the full impact is unknown, everyone may soon command their own AI teams. Here's an example: Imagine you're developing new quantum computing algorithms. Your AI assistants could: - Continuously scan and synthesize global quantum research papers - Generate novel algorithm ideas based on this knowledge - Simulate and test these algorithms across various quantum architectures - Automatically document findings and prepare draft papers - Identify potential collaborators and draft outreach emails All initiated by a command like "Advance our quantum algorithm research." This could dramatically accelerate R&D cycles and scientific breakthroughs.. https://lnkd.in/eJbg6cnD #frontiertech #AI #futurefrontier

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For a young software company, what does a dream end-market look like? A few great signals off the top of my head: ▶️ Low NPS of incumbent solutions ▶️ Lots of manual / lightly-digitized processes ▶️ Many buyers (i.e. top 3 don't control the market) ▶️ High ability to pay (decent margins and trendlines) What else should be on the short list???

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This is quite interesting advice and also quite a non-consensus view in the B2B software world. Cross-border founders who are considering the US vs International incorporation question should consider this as valuable input.

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If you enjoyed our first blog on the metrics that matter for Verticalized SaaS then don't miss on the Part II of the series where my colleagues Devraj Hom Roy and Matt Schaar discuss the strategic and operational choices to improve these operational indicators. https://lnkd.in/g5QkCrcH

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Wonderful article about Emily Knight and the whole The Engine Accelerator team on the amazing work their doing changing the world with #ToughTech!

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I recently saw this metric from Carta’s 1Q24 VC Fund Report, which is very concerning. DPI... is nowhere to be found in earlier vintages that probably should start showing DPI. Funding early-stage projects is great, but ultimately, these venture dollars need to exit their investments and pay back their limited partners. That’s where the metric Distributed to Paid-In Capital (DPI) comes in. While managing a fund, we get interim measures during the life of the fund (e.g. IRR, MOIC), but ultimately, “you can’t eat IRR.” If you want to build a lasting venture capital organization, you need to start showing DPI for your fund. Keep in mind that this is traditional VC data from Carta, and is not strictly crypto venture. Crypto venture tends to get liquidity earlier (tokens) and things tend to go parabolic sooner (faster, more unicorns) - but I’d wager that the data here is somewhat similar for Crypto VCs… Not as much DPI as there should be from these earlier vintages. Read the full article, as well as a recap of all the crypto fundraising rounds for August, here: https://lnkd.in/g3eVJ-iF

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This is really exciting. If you are following the #TechnologyTransfer space, please subscribe to my partners’ new newsletter!

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