Sherman L.

How do investors price pre-seed rounds?  This is perhaps one of the most misunderstood aspects of fundraising.  Oftentimes, founders want some framework to better understand what market value is when raising capital into their business.  Public equities and later stage privates have a well defined matrix of revenue/margin profiles that dictate valuation, surely there must be some framework for arriving at a pre-seed valuation. So how do investors price startups that are pre-revenue, or have maybe one of two early customers? In reality, pricing is more a byproduct of a VC fund’s portfolio construction model than any metric of the underlying business.  VCs model out portfolios to include a certain number of companies with an ownership target in each startup.  There are variations to portfolio construction, and the chosen strategy will have a direct impact on the types of rounds a fund will participate in. For example, an early stage fund might raise a $60M fund to lead investments in 30 companies and target 12.5% ownership.   After management fees, there is ~$48M in investable capital.  Assuming a fund holds back ~30% for reserves(this number varies across funds) that leaves ~$30M to invest in initial checks.   In this case a fund must average $1M checks at $8M valuations to reach their intended ownership target of 12.5%.   When you are in diligence with a fund, they are first and foremost trying to get to a yes on the investment opportunity.  When arriving at a valuation though, the math outlined above is the determining factor, more so than any multiple of revenue on the business, or the stated desires of where a founder wants to raise capital.  At the end of the day, a VC is trying to arrive at a valuation that works within their portfolio strategy. This means they are very unlikely to price a deal at $15M cap given the aforementioned portfolio construction, as they would either not own enough($1M = 6.67% ownership) or have to cut too large a check( $1.875M = 12.5%). The thing that is most likely to move an investor off their target valuation is another investor in the picture that is driving the price higher, but even then there are upward bound limits of how high an investor is willing to price a deal. I always advise our port cos to ask an investor early in conversations what their ideal check size/valuation is to make sure there is alignment with the founder's objectives.    

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Many assumed that the industry would be well on its way to AGI or superintelligence before AI model builders’ efforts to take advantage of scaling laws might hit a wall. Recent headlines are chipping away at that assumption. One question I've been getting in my inbox: is this the era of diminishing returns for AI? We don't think so. Even if an avalanche of new clusters and synthetic data fail to deliver significantly better model performance, there are good reasons to believe that AI is still going to become orders of magnitude more powerful in the coming years — powering a new generation of startups and ultimately productivity growth and positive benefits for mankind. In fact, with agents and reasoning just beginning to scale and thousands of industry-specific models coming online, it's about to get really exciting. Read our latest blog post on the topic: https://lnkd.in/gFhniNX8

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At Forum we look at thousands of deals each year across our Accelerator and Pre-Seed funds but only end up investing in a little over 1% of those startups.  As an early stage VC, I am in the business of saying no to nearly every startup I meet, and while there is nuanced rationale for many of the startups I pass on, a vast majority of businesses that don’t meet the qualification to get funded typically fall into one of two buckets. ▪ First time founders have a tendency to go out to market too early to raise pre-seed capital ▪   I’m sure most founders have heard some iteration of this from VCs that ultimately pass on their business.  In some cases it's a blanket excuse covering up for other pass reasons- perhaps a VC doesn’t believe in a team or isn’t bullish on the market opportunity - but in many cases founders simply haven't proven enough to the market to warrant an investment. I meet many teams with an articulate vision for the product that they want to build, but they either haven't performed enough customer discovery to prove demand for their initial wedge product, or need to raise pre-seed capital to build out an MVP.  In those cases, pre-seed investors are unwilling to underwrite those risks.  To be default fundable, teams need to be able to keep costs low, perform extensive customer discovery, and ship some version of an early product - pilots and early paid customers are key. A huge piece of this is having founding engineering talent on the team. ▪Not every startup is a venture opportunity ▪ By definition, a venture backed business is solving a problem within a market opportunity so massive and so desperately needed, that its growth rate is off the charts.   It spreads like a weed, absorbing almost unlimited amounts of capital to fulfill demand within its customer base.   Each year there are maybe 20 companies launched that ultimately have venture scale outcomes. The bar to reach this rarified air is unfathomably high and the reality is the vast majority of founders simply aren’t building for opportunities that have the potential to be one of these generational companies. Many startup founders view VC as the only viable option for capitalizing their business, but not every great business is a venture business, and most successful founders never take VC dollars.  In order to reach an IPO/acquisition large enough to generate venture returns, a startup needs a credible path to $100s of millions in revenue. This is the standard by which early stage opportunities are evaluated. The flip side to this, and I share this feedback often with founders I meet that are building interesting business in non venture markets, if you are able to scale to $10- $20M in revenue that can be a massively successful outcome for a founder.  There are investors who focus on these type outcomes, namely lower middle market PE shops, and the typical path to those deals is a bootstrapped business or a friends/family capital raise.

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Insightful look into bioplatform strategy, and what it takes to raise a Series A from my partner, Omri Amirav-Drory: https://lnkd.in/dFv7GbF6

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Let the wave begin! Pioneer Fund company Recall.ai *grew their revenue 10x* in the past year, has 300 enterprise customers, and just raised a $10M Series A led by Ridge Ventures. David Gu and Amanda Zhu dropped out of college at age 19 to start the company. They've grown it exponentially with a tiny team. They make it easy to build meeting bots that are cross-platform. They're aggregating all these different APIs into one unified API, the way Twilio did with cell phones. At first it "sounds" easy to build a meeting bot -- just integrate with the Zoom API. But in fact there's a huge long tail of things you need to build, security and privacy pitfalls, automations, transcription complexities, integrations, the calendar invites where someone is using Google Meet or Teams, staying up-to-date with the libraries, etc etc. Recall takes care of all of that. It's WAY easier to build on top of Recall.ai and focus on the features that make you unique. Congratulations to the Recall team!

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And my second investment at defy is in 🐶 zeroETL puppies 🐶... I mean PuppyGraph, which is all the beauty of a graph database, none of the data migration or continuous upkeep of a graph database. Sounds like magic? So are puppies 🐶 . Puppygraph is NOT a graph or a database. It is graph analytics engine that answers graph questions on your existing data warehouses, whether that is a Databricks datalake, Google BigQuery or postgres. Compared to SQL, it's faster, handles way more complexity, scales and has almost no upkeep. How did I get to conviction? 1. Tailwinds - 🌊 Lakehouses 🌊 have helped enterprises put all their data in one place, enabling Puppygraph to unlock insights previously unavailable. - 📚 LLMs! 📚AI and RAG cannot easily traverse fragmented data. Puppygraph's Graph RAG unlocks insights with their Knowledge Graph and spoonfeeds to the LLMs. 2. 👯 Team 👯 We have graph experts from Google, LinkedIn, Databricks, Tigergraph, and Instacart who are uniquely able to build this solution. 3. 💸 Customers 💸 . My alma mater Coinbase is a proud user. The feedback from my former colleagues was off the charts! A blockchain is very much a graph database and Puppygraph tracks down fraudulent transactions that go through mixers and helps identify patterns. Huge congrats to Weimo Liu Danfeng Xu Lei Huang Zhenni Wu Gary Hagmueller, defy.vc is proud to be an investor!!

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I’m thrilled to be announcing that Notion Capital is leading the $15m Series A investment in Cogna today. In the industry, we like to think that software has been eating the world. But when you look at the data a better description would be more of a nibble. Depending on what source you look at the software industry represents between 5-8% of global GDP. Contrast that with the services industry that represents between 60-70% of GDP and worth around $25 trillion on a global basis. Most services have been out of reach for the software industry. They have either been too complex or too specialized for off the shelf software to access in any economically viable way. But that’s beginnning to change with GenAI leading to the emergence of ‘service as a software.’ Cogna is at the forefront of this opportunity - building precision software at scale and delivering huge productivity gains for traditional industries. We know Ben Peters & Lars Mennen well having backed their previous company Five AI that was acquired by Bosch in 2022. And we’re very excited to be backing them again together with Hoxton Ventures & Chalfen Ventures Read my full blog post on why we invested here. Radu Bozga Ben Peters Lars Mennen Bryan G. Mike Chalfen Hussein Kanji Kirsten Connell https://lnkd.in/eh8mhcJb

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Have you heard of #CapVC? It’s an application platform designed specifically for the use of #VC firms. Essentially, it’s a robust #AI-powered tool made to simplify the daily operations of managing a #fund. Isn’t that something, a VC funded start-up designed to help improve the productivity of VC funding! According to this article from TechCrunch, Cap VC is looking to become much more than just an ‘operating system’ — the company aims to be a simplified and extremely efficient way to run a VC firm: reducing digital clutter by turning PDF files, income statements and balance sheets into readable data, automating company suggestions based on the context of a VC’s portfolio, and more. Cap VC is currently developing native apps on Mac and Windows, alongside releasing an API so that developers can build on top of their foundations. So, are any of my fellow VCs interested in using this software? If not Cap VC, is there any interest for similar software to be created down the line? Are there downsides to using a third-party application like this? I want to know what you all think.

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Sharing a sanitized version of the mu ventures Q2 q'ly LP update. Included musings: 👉 SEOs shrinking impact, and the rise of LLMO (large language model optimization) 👉 examples of the Commerce AI application layer coming to life 👉 a modern fund strategy that accepts companies require less capital, time, and people to trigger the power law 👉 Mu's guide to investing in AI 👉 all 30 companies in the Mu-niverse (and several others we admire) Founders, VCs, LPs - if you like how we think and suspect we can partner, hit us up! https://lnkd.in/dTJ2zjav

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Organizing an intimate meetup for high-growth founders building dev tool / Infra / b2b SaaS, together with Bain Capital Ventures this Friday in SF. If you've either: - Raised at least $2M or achieved at least $250k ARR for your current company - Or, you’re a repeat founder who has raised at least $10M or achieved at least $1M ARR in a previous company - Or, had a previous exit for at least $5M Please comment/DM to get tickets - 5 more spots left

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Advice to founders: Your AI strategy needs to evolve beyond workflow automation. Here's why. The enterprise AI market is evolving from path 1 to path 2: Path 1: Automated workflows aka traditional automation → Rule-based processes → Manual data inputs → Human oversight at every step → Limited to structured data Path 2: Systems of Agents (the future) → Networks of specialized AI workers → Real-time data capture and analysis → Continuous learning from each interaction → End-to-end business capabilities Repetitive, rule-based tasks were the low-hanging fruit 🍎 Meaningful breakthroughs happen when we build systems that enhance human teams' capabilities. This human < > AI collaboration opens up completely new categories of work—things we couldn't even attempt before. Agree? LMK in comments.

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GPTZero has skyrocketed to profitability within 18 months, raking in millions. With 500% ARR growth in six months and user growth from 1 million to 4 million in a year. While many AI-detection companies struggle with accuracy, GPTZero excels, leveraging vast data and advanced LLM models using the latest open-source tools. Initially celebrated for helping teachers spot AI-generated student work, GPTZero's clientele now includes government agencies, grant writers, hiring managers, and AI training data labelers. One founder noted, "We have a big data advantage with millions of examples of human versus AI-generated text," proving the quality of data fed into AI models is crucial. https://lnkd.in/gREnQ2ps #ai #sustainabledevelopmenttechnology #emergingtechnology

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So many burnt out founders. But also: So many surplus elites. And also: A new paradigm for low-risk idea-stage innovation in founder/startup/community/vc formation. That's Slyk IO We level up together: https://lnkd.in/grEmV-R6

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Startup decks vs Business plans. It's accepted that a startup needs a deck. Dax Dasilva of Lightspeed Commerce made an important point on 20VC. Writing a business plan - including financial projections - is an important step. It requires discipline. It provides a rigorous framework for thinking deeply about the problem you're trying to solve. Harry Stebbings countered that he doesn't even want to see a deck since it's all dreams. We spent a lot of time and energy on our business plan with the expectation that we would show it to no one ever. The business plan was part of our roadmap for the company. We researched customers - including having 50+ conversations. We wanted to understand them: their background, their interests, their presence on social media. We also wanted to understand how they were evaluated by leadership and how integrated they were with the business of the company they were protecting. We researched pricing both with potential customers and other products in our industry to find out if OpEx or CapEx was a better fit. How did they buy today? How would they like to buy? We did market research to understand the verticals and map the right entry point - we were wrong but that doesn't reduce the value of the research. We looked at competitors in depth to understand what they were seeing that we weren't. Dax is right. This is an invaluable document that should be updated every year - the company is changing, the market is changing, there's more feedback about price and ICP. It's not for sharing with the outside world. It's a map for driving forward. Decks won't get you investment - VCs invest in people. We make decks but we know they don't tell our story. The deck is a calling card. Dax and Harry are both right. https://lnkd.in/e25M82xY

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🚀 Ready to launch your VC fund? VC Lab Cohort 17 has a new AI-powered mission control, LP mixers, new tracks, and more. Learn how we can help... 🛠️ AI-Powered Launch Suite + Decile Base: Your AI co-pilot + Smart LP targeting & network analysis + AI-powered thesis builder + Personalized outreach tools 🤝 Enhanced Support + Regional Demo Days + Global GP-LP mixers + Premium mentoring + Institutional-grade resources 🌌 Specialized Tracks + Space Technology + Later-Stage (Series A/B) + Family Office Funds + Enhanced Emerging Manager Program 👉 Perfect Timing + Exceptional deals at reasonable valuations + Billions in LP capital seeking emerging managers + Unique window as established firms face challenges The Early Admissions Deadline for Cohort 17 is Monday, November 18th. Join the 50+% of new VC firms we've launched in the last two years. 🚀

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Greed and Fear, AI (adoption) style. In investments we're used to talking about greed vs fear, now we're seeing this same pendulum applies when it comes to consumer sentiment towards AI adoption. Concern is fear, that's obvious, and if you think about it a bit excitement comes from a form of greed in this case: the excitement for AI is because people hope it will help them do more with less time and effort invested - a greed for precious resources (which can be translated to money as well). Consumers need to invest some time, effort, as well as money in order to come up the AI learning curve (learning the right tools and how to prompt them). Playing around with AI is one thing, seriously using it professionally or personally is a bigger step that will be affected by the greed vs fear. It's too bad Pew Research Center didn't separate out professionals' opinions in a professional capacity (link to findings in the first comment), but still they find that for the first time the majority of Americans are concerned. The increase in concern (fear) happens just as research is starting to demonstrate that AI is making people more productive, which should have fueled excitement (greed). According to Ipsos, two thirds of people think AI will profoundly change their daily life in 3-5 years. Almost half say it already has (link in second comment). Interesting... And now this entire post rewritten by LI's AI: Greed and fear are familiar concepts in the world of investments, but did you know that they also apply to AI adoption? Consumer sentiment towards AI is swinging back and forth between concern and excitement. Concern is fear, and excitement is a form of greed. People hope that AI will help them do more with less time and effort invested, a greed for precious resources. However, investing in AI requires time, effort, and money to learn the right tools and how to use them. Playing around with AI is one thing, but seriously using it professionally or personally is a bigger step that will be affected by the greed vs fear pendulum. According to Pew Research Center, for the first time, the majority of Americans are concerned about AI. This increase in concern happens just as research is starting to demonstrate that AI is making people more productive, which should have fueled excitement. Ipsos reports that two-thirds of people think AI will profoundly change their daily life in 3-5 years, and almost half say it already has. What are your thoughts on the fear vs greed of AI adoption? Share your opinions in the comments. #AI #fear_greed #investment #genAI

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"If we’re measuring velocity in days or weeks, it might seem obvious to directly tie a startup’s velocity to the number of hours you work each day. But startup velocity is far more than just hours worked (a nuance that many adherents to startup “hustle” culture get wrong). Velocity is not only about how hard you work, it’s about how you work. At a fundamental level, startup velocity is a measure of a company’s sense of urgency." https://lnkd.in/gV9Z_ift

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Here are 5 founders who have leveraged writing to amplify their voice. Paul Graham, co-founder of YC Joel Spolsky, co-founder of Stack Overflow Tom Preston-Werner, co-founder of GitHub Patrick Collison, CEO and co-founder of Stripe David Heinemeier Hansson - Creator of Ruby on Rails and co-founder of Basecamp Why would a founder ignore the immense power of words? Discover the art of storytelling to captivate your audience. Here's the secret. The craft of storytelling goes beyond just sharing facts; it builds emotional connections. Human beings are wired to respond to stories. They evoke emotions, create a sense of belonging, and make abstract concepts relatable. Storytelling isn't just an option; it's a necessity. By weaving storytelling into your personal brand, you can make your message more memorable and impactful. It gives people a reason to care about what you're doing, to root for your success, and to be part of your journey. So, how do you transform your message into a captivating narrative? It starts with authenticity. Speak from the heart. Share your challenges, your victories, and the lessons you've learned along the way. Show the human side of your brand. Want to dive deeper and elevate your personal brand? DM me "Grow" and see if we are a fit to help you.

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