Susan Athey

Want a front-row seat to the frontier of tech? We’ve got the role (or two) for you! We’re expanding our frontier-tech team at Blackbird by hiring a Frontier Tech Investments Associate and Foundry Fellows! Got questions? We've got answers... 1️⃣ What are the roles? 🧪 Associate = a full-time VC investment gig in our Blackbird Investments team, working directly with me. We’re looking for someone with a science and/or engineering background and more curiosity than they can handle. You’ll grow your own investment brand and practice, support our portfolio founders, and will help build Foundry, our early-stage frontier-tech accelerator. ✨ Foundry Fellow = a casual/contract gig in our Blackbird Investments team, ~15h per week for 3 months. The Fellowship is ideal for PhD students and ECRs who want to learn more about startups and VC. You’ll go deep on emerging areas relevant to your expertise (or curiosity!), get a front-row seat to groundbreaking companies in those areas, build out your non-academic network, and develop a solid writing practice. 2️⃣ Why are you hiring? We love frontier tech, and we’re ready to grow our team. 3️⃣ Wow, it’s so great that you’re starting to look at deep tech! Look, we get it: we don’t make a lot of noise about our frontier tech investing. Buuuut we’ve been deep-tech investors since we backed Tim Kentley-Klay to found Zoox back in 2014—we’ve been on incredible journeys with PsiQuantum (building the world's first utility-scale quantum computer right here in Australia!), Inventia Life Science (transforming drug discovery with high-fidelity cell models), Remedy Robotics (surgical robots for remote endovascular procedures), Opto Biosystems (minimally-invasive neural implants to treat cancer), and more. We believe that frontier technologies, and great frontier-tech investing, will be part of the solutions to the greatest problems humanity faces today. 4️⃣ When do applications close? May 31st at 11:59pm AEST. 5️⃣ I have more questions! I’m sure you do! Clare Birch and I are hosting an AMA to answer any and all questions about these roles. Want to know what a week in the life of our team looks like? What’s keeping us up at night? What our ideal candidate looks like? Come along and find out - registration link in the comments 👇 Apply for these roles: Associate - https://lnkd.in/gCfj4EUJ Foundry Fellowships - https://lnkd.in/gj6ATZVZ If you know anyone that we should meet, send me their details! Cameron Elise Ben Andrew Robin Joseph Adelaide James Olivia Lucinda Raghav Jesse Christie Mohamed Tom Amee Pablo Haya Loong Hon Joshua Benjamin Megan Harry Denzil Matthew Diana Daniel Tom Deanna Justin Amar Lilly Stone Thomas

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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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Super helpful article and accompanying doc with a #Startup #Equity Calculator to determine the equity for early hires, thanks to Pear VC head of talent Matt Birnbaum! Thanks for sharing Pejman Nozad! 🙏🏼 You can read more here How to structure startup equity for early hires: https://lnkd.in/ggmpT5-Y Google Doc: https://lnkd.in/gjsvths6

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I'm really intrigued by this idea (not mine) that some bitcoin mining companies (Iris, Cleanspark, etc) have successfully built low-cost power shells that can now be leveraged by AI compute needs -- where power itself is becoming the gating factor in the continuing growth of AI. I think this will become a real 2025 story -- as the gating factor of "chip shortage" lessens, and the gating factor of "cheap power" rises in significance. There's not really a venture capital angle here, but there is a public market one. Perhaps more importantly, it becomes a touchpoint between "crypto" and AI. Something to ponder and keep an eye on (full disc: I own a bunch of bitcoin miner stocks, including those mentioned above).

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"Editors note: Welcome to issue #2 of Transcriptions. Today, we’d like to present a conversation between Qasar Younis of Applied Intuition, and Bilal Zuberi of Lux Capital. We discovered Qasar recently, and find his focus and clarity of thinking to be admirable. What follows is a lightly edited transcript of their talk, first held at the Paklaunch forum." Link to transcipt: https://lnkd.in/gH4uBmPE

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Thrilled to announce the launch of our inaugural edition of Beyond Benchmarks at Emergence Capital. This comprehensive report dives deep into the metrics and trends shaping the early-stage enterprise cloud market. A huge thank you to our VC partners and contributors for making this possible! Here's a sneak peek of our findings: --> 60% of companies have already integrated GenAI into their service offerings, with another 20% planning to do so this year. --> While most companies use OpenAI as their primary LLM, many are experimenting with multiple models. We’re seeing a trend toward intelligently routing GenAI inference requests based on cost, performance, and security. --> Companies that have implemented GenAI are showing promising results, with a 7% higher NDR compared to those that haven’t. Beyond Benchmarks goes further with more GenAI trends, insights on the current fundraising environment, and key performance metrics. Our goal is to provide founders and their teams with valuable benchmarks to help them make better-informed decisions. At Emergence Capital, we're committed to helping founders build iconic companies. Dive into the full report here: https://lnkd.in/g6bnvAZM

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As someone who played competitive tennis growing up, Roger Federer’s message at Dartmouth's commencement resonated with me and should inspire startup founders everywhere. As one of the greatest tennis players of all time, Federer pointed out that, despite his huge success in matches, he actually only won 54% of all the points he ever played. He went on to share: "When you’re playing a point, it is the most important thing in the world. But when it’s behind you, it’s behind you... This mindset is really crucial, because it frees you to fully commit to the next point… and the next one after that… with intensity, clarity and focus. The truth is, whatever game you play in life... sometimes you’re going to lose. A point, a match, a season, a job... it’s a roller coaster, with many ups and downs. And it’s natural, when you’re down, to doubt yourself. To feel sorry for yourself. And by the way, your opponents have self-doubt, too. Don’t ever forget that. But negative energy is wasted energy. You want to become a master at overcoming hard moments. That to me is the sign of a champion." When you're a founder, you're in a fierce battle every day - sometimes against competitors, sometimes against markets, and sometimes against yourself. The most successful founders accept that they'll get a lot wrong but have a mindset to adapt and bounce back from setbacks as quickly as possible. It's not about winning every point. It's about winning the most important points. Because often the victory comes down to a slim margin. https://lnkd.in/g6JRcSee

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In our latest episode on the Practical Nerds podcast, Patric and I talk about our earned learnings on how founders (and other VCs) should choose the right (Co)Investors for their startup (Construction-tech or otherwise). Which of these do you agree with ? What did we miss ?

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I had a lot of fun recording a podcast episode with Shiva Singh Sangwan. We discussed the evolution of Humba Ventures & Susa Ventures; tips for raising and building a fund; how to improve investment sourcing & picking; the role of luck in investing, and so on. https://lnkd.in/eiqsStej

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Let's finally get rid off the "VC alphabet song" and redo the system to become more founder friendly. "The benchmarks set by funding stages are often arbitrary and not necessarily aligned with the actual development needs of individual startups." #vc #venturecapital #founder #fundraising #startups #fundingstages #funding #fundingrounds #pitchbook

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During yesterday's LibreQoS APNIC webinar, I posed the question: won't more bandwidth solve these problems? As Herbert Wolverson said, yes, more bandwidth is good, but, still these problems remain if queueing is done incorrectly. Here's my take on why bandwidth alone is not as good as bandwidth + good queueing policies: Generally it was believed that 'data is important, so don't throw it away; hang on to it and send it later'. In practice, this has proven to be suboptimal as two issues may emerge: 1) latency increases for some flows due to heavy demand from other flows using the same bottleneck link, 2) even a single flow can have excessive latency due to aspects of typical TCP behavior (referred to bufferbloat) when the buffers grew large enough that the data being buffered was retransmitted anyway. It turns out that not all data is equally important. Active Queue Management is the art of deciding priorities, both in deciding what data to throw away, but also in allowing some later arriving data to be transmitted ahead of data in another connection that arrived before it. These problems have been studied, and good solutions have been found by using certain queueing policies in routers and switches, referred to as “fq_codel’ and “cake”. These track the different flows not by classifying the data, but by watching the behavior. Flows that send relatively little data (DNS lookups), or at a measured pace (video chat) have priority over flows that send a lot of data as quickly as possible (App and System updates, Video and ISO downloads).

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See this chart? 💰 This is the San Fran Bay Area versus the rest of the world in #AI funding. Last year, more than 50% of ALL global venture funding for AI-related startups went to companies headquartered in the Bay Area. And, the Bay Area alone had more AI-related startup funding deals than ALL COUNTRIES outside of the U.S. Let that sink in... This is a major problem for #ecosystems across the US, who are pinning their hopes on VC-backed companies in this AI startup renaissance moment. AI is a race to see who can come out the winner. 🏆 And the way you win in startupland is you pick the company you want to bet on and you back it with a lot of capital. With the Bay Area dominating the AI funding game, it's going to be increasingly difficult for other ecosystems to compete. chart via Crunchbase

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Instacart is a market leader when it comes to leveraging AI tools to boost productivity at work. I had an amazing conversation with JJ Zhuang, Instacart’s Chief Architect, who has shepherded over 50 AI-driven initiatives to market across the org. We explored what catapulted Instacart to the forefront of AI integration, supporting radically diverse use cases across various functional areas. One striking insight (echoed by Ethan Mollick and others elsewhere) is that you often don't need specialized tools for specialized work. Frontier models like GPT-4 can seamlessly adapt to a wide range of functions and use cases. They're not just for engineers; they're incredibly versatile tools used by marketing, comms, and legal teams. From generating code to proofreading and ideation, GPT-4 empowers every department to leverage AI for enhanced productivity and innovation. By integrating LLM’s like GPT-4 into their workflows, teams can streamline processes, automate repetitive tasks, and unlock bandwidth for new creative possibilities. How can you harness the power of AI in your own work to boost productivity? Share your thoughts below 👇 Want to hear more insights from JJ? Check out the full podcast episode by clicking the link in the comments.

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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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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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Interesting concept to rename rounds by milestones. But "Series Client Expansion Extension" just doesn't have the same ring to it 😋 . Maybe we can start incorporating it into a descriptor to add context, "Series Seed Extension: client expansion." #startups #venturecapital

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Once you’re in it, you’re in it. #Startup #founders don’t just take financial risk - they invest years of their lives. For many, it’s absolutely worth it. To me, the first task is the most important one: to define your target and make absolutely sure it’s one worth that level of investment.

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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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I’m excited to publicly share something that has been in the works for a few months at the 9point8 Collective. We’ve launched our Virtual Studio! This is a program for early-stage companies that provides the coaching, development and venture-building tools they need to find traction and scale. The program is modeled off of the venture-building processes found inside #VentureStudios, which have delivered 2X IRR and exit 45% faster than traditional #VC-backed #startups over the last 10 years. Some of the secret sauce to this is that studios have found a way to validate strategies early on, de-risk execution, preserve and extend limited runway, and create efficient business models very fast. We at 9point8 are seasoned studio builders and are on a mission to bring this value to founding teams as they navigate their startup journeys. What we’ve done with the Virtual Studio is distill these key processes and techniques, add in our own expertise and best practices, and package them into a program which meets start-ups where they are. We are now opening up our Summer 2024 Cohort, slated to begin in July. Space is limited, so I’m sharing the opportunity with my network before we fill the cohort. Here are the details: -It’s a 3-month program which takes the founder through the key phases of venture-building and de-risking (refining target market, product-market fit, economics and financials, planning, and fundraising). -Founders can expect to achieve greater focus, improved operations and increased marketability to customers and investors. -The end results include collaboratively-drafted operational plans, commercial / investment pitch decks, and elevated management practices within the founding team. These draft off frameworks from 9point8's proprietary venture-building process: Targets Over Everything. -It’s built for founders facing (or approaching) a critical inflection point, where fresh perspectives and strategic management levers are critical. These might include fundraising preparation, new product launch, market expansion, and post-MVP scaling efforts. Why did we build this program? Because building a new company is really hard. 90(!) percent of startups fail, and even moderate risk reduction can create a huge lift to survival rate and eventual returns. The studio model is proven to drive greater venture success; our virtual program is extending that success to more and more teams. The program is highly collaborative and hands-on, so we only take on a few companies at a time. This is a great opportunity for founders who are looking to level-up their abilities when it comes to unlocking traction, growth, and an express lane to superior returns. If interested, please reach out immediately as we expect the program to be fully enrolled very soon! Blair Merlino Evan Allen Neal Ghosh

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