Eric Rosenblum

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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If we want to see more diverse top companies like NVIDIA, we need to pave the way at the earliest stages—venture capital is that on-ramp. It was a pleasure to join Emerging Manager Office Hours hosted by Venture Forward earlier this week. Thank you to Rhianon Anderson and Maryam Haque for organizing such a value add event! A few (other) big takeaways to share: 👉 Distinguish the Curious from the Serious: Focus your time on LPs who are truly engaged. There are many LPs out there still excited about and committed to the VC asset class. 👉 Showcase Portfolio Performance: With liquidity tight, highlight KPIs, revenue growth, and the value your companies are building now to position for success when markets rebound. 👉 Clearly Differentiate: Provide concrete examples of how your approach stands out and drives unique outcomes, i.e., case studies. It was a pleasure connecting with friends and meeting inspiring next-gen GPs shaping the future of venture capital: William Crowder (Aperture® Venture Capital), Joshua Weed (Veteran Ventures Capital), Sonam Velani (Streetlife Ventures), Marcos Gonzalez (VamosVentures), Erica Duignan Minnihan (Reign Ventures), and Jenny Xiao (Leonis Capital). Here’s to collaboration, innovation, and creating lasting impact together.

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Breaking down our latest newsletter section by section, starting with our expanded focus in Deep Tech: --- We have built expertise in the robotics sector, and will continue to double (and triple) down on investing in this category, but we have been increasingly finding that robotics is naturally steering us into two exploding adjacent areas: Aerospace, and Advanced Manufacturing (which we define as industrials, semiconductors, materials science, and energy production). Stepping back, this expansion makes perfect sense. Robotics is an inherently horizontal platform - meaning it can be applied productively across multiple industries. This quality, paired with the fact that robotics has long shown the highest TRLs of any deep tech technology, makes it a kind of “gateway” to other sectors in the hard sciences. Now with the recent breakthroughs in AI for robotics, growing semiconductor demand, and the resurgence of aerospace and defense tech, we are seeing a dramatic uptake of robotics and relevant technologies in both advanced manufacturing and aerospace. As an added bonus of the expansion, many of the founder (and funder) networks across these landscapes have natural overlaps and linkages. For AlleyCorp Deep Tech this means that we can be extremely helpful, knowledgeable, and engaged across all three sectors right away, and continue to be the best-in-class investing team across these categories.  --- More in our newsletter: https://lnkd.in/ewiTuYq6

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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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AI memory is fundamental for conversational AI and AI agents. It is critical for building personalized experiences and improving reasoning. Check out Letta’s course to understand how to use AI memory to enhance the customization and quality of your AI app.

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Reminder that the Unusual Ventures Fall 2024 Academy application is OPEN! Deadline for submissions is 9/9. Are you a Founder who wants to: 1. Learn from world class leaders the best practices of building from insight to product-market fit? 2. Receive up to $2M in a SAFE to accelerate company building? 3. Join an unmatched community of founders who are eager to support and learn with you? 4. Dive deeply into the latest pricing, go to market, and infrastructure choices founders are making for their AI-native startups? Unusual Academy is for you and your team. Each cohort consists of a small group of hand-picked Founders who are in the early stages of building Enterprise Software businesses. Over eight weeks Founders will participate in a highly personalized set of workshops that drive the building of the foundation of a successful startup. Founders will work very closely with our team on how best to execute Customer Discovery and validate the insight for your startup. We then explore the nitty gritty details of doing customer outreach and working through the Design Partner phase. We take you through proven tactics on how to navigate early customer engagements through to contract conversations. Throughout Unusual Academy we work closely with each team to align product strategy with the optimal go to market approach for their market segment and product. With the advent of AI, Founders are faced with new challenges with regard to pricing, ROI, data security, and managing infrastructure costs; we share best practices and the latest adaptations from the leading startups. Unusual Academy is a program for Founders who want to learn from exceptional teachers and get hands-on with specialized examples and tools. For those who want to maximize their probability of building a successful startup, this program is for you. https://academy.unusual.vc

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Tribe AI just raised our first external round of capital from Bryce Roberts at Indie, with significant participation from our customers, partners and network of top AI engineers. We’re excited to share this milestone in TechCrunch (thanks Rebecca Szkutak for sharing our story!) along with some long overdue updates:  💲 Raised $3.25M to keep up with demand and build the platform to enable service delivery at a tremendous scale 🚀 8 figure revenue run rate, more than doubling year over year (and accelerating) 🏛 Enterprise customers from the Fortune 20  🧠 500 top AI engineers from places like Google, Tesla, Meta and OpenAI As a refresher, Tribe is an AI-native services company that helps Enterprises build best in class AI products. Our team is augmented by a talent network of over 500 top AI engineers from places like Google, Tesla, Meta and OpenAI who bring both industry and deep technical specialization to our project deployments. These are the people who have built the infrastructure that is powering the AI wave and know it better than anyone. After bootstrapping Tribe AI since 2019, we decided to raise this capital because the market opportunity was simply too big. Even as we were reinvesting our profits back into the business, we still saw more demand than our capacity could support. We’re grateful to have met Bryce and have him believe in us and the opportunity we saw. We’re also extremely proud to have the major stakeholders in our business (our customers, partners and network of top AI engineers) invest in the round as well. We’re on a mission to help Enterprises realize the value of AI for their business, and we’re building a category defining AI company in the process. Read all about it 👇 https://lnkd.in/dYRDQDjp

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📰 Solo VCs are rising in popularity once again. This means only one General Partner is leading the firm, versus multiples. 💔 Why? There are GP breakups going on all around us after partnerships have been tested by the market for years now. The bar to co-found a venture firm with a partner is very high. Those GPs that thought they might graft another one on in the short term to share the load are stopping in their tracks to deeply consider those implications. 🌱 Many are opting to bring in more junior talent and grow them into Partner roles instead. It’ll take time and capital to be able to do that as the firm grows. Talked to 3 diff GPs about this at dinner last night and we’re all leaning toward that approach in our short and long term planning. 💡 FYI - this is just an observation of the moment we’re in. There are plenty of firms thriving with full partnerships as well as solo GPs. But it’s worth calling out that new partnerships are particularly risky right now, especially if the partners haven’t worked with each other for a long time.

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Looking beyond #VC funding for your #startup? Aakash Shah of Wyndly (YC W21) reveals how he built a multi-million dollar #healthtech company using creative capital strategies. Learn how he leveraged Y Combinator's network and alternative funding methods to revolutionize allergy treatment. In case you missed it, you can watch the #FundraisingDemystified #podcast here: https://lnkd.in/eZT63YS4

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I started Early Stage Labs because I kept seeing the problem over and over again - seed and series A startups need support in certain functions but don't have the budget/need to bring on somebody full time. We signed our first customer (Modicus Prime) 48 hours after meeting them on what was supposed to be a customer discovery call. Rebuilding their model and getting better visibility into the financial health of the company was a "top 3 problem" for them as they prepared to raise their seed round and as circumstances were demanding they become more disciplined operators. I'm incredibly thankful to Taylor - a brilliant founder (check her out!) - for trusting in a new (or at that time nonexistent!) company. That was a real lightbulb moment for me. We could really delight customers and be super valuable to them in their early days, probably up through their Series B. I kind of stumbled into building this business earlier this year, and I've slow played it a bit as I've wanted to stay very close to customers. "Do things that don't scale." We have learned so much. I'm so thankful. We have a legit chance (~30%) to close this year at $100k in MRR. It's a pure services business, so margins are much lower than the technology companies I've built before. But it would be really damn hard to build a technology business to $100k in MRR just 10 months from your first customer discovery call. I'm incredibly proud that that $100k MRR will represent the fact that we're making several startups better versions of themselves. The thing I'm most excited about on this business is that our customers are some of the people I admire most - founders of early stage companies. You have to be a little bit twisted to go start a company, and that's exactly the people I love spending my time with and serving. If you're on that winding journey and you feel like you need support around finance or growth, we're here for you. Cheers to founders. And cheers to boring services businesses.

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Insightful breakdown from my great Partner Omri Amirav-Drory on the simple factors that really separate the top 1% of investors from the rest, and how more operators should become investors! https://lnkd.in/gEiZdT2h

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There are two interesting and relatively new/emerging revenue models in hardware space. (1) Software Enabled Hardware Hardware is sold at lower but slowly improving gross margins (eg 20-40%), and software recurring revenues layered on top. Software sells at higher margins, enabling blended margins to appear in 50%+ category. These are applied in situations where hardware is not expected to be replaced or greatly improved upon in deployment for a significant number of years to come. Consider your car, or military equipment, or even infrastructure equipment. As always, there are often multiple business/revenue models utilized by different players in the same industry. (2) Hardware As A Service Hardware and software are bundled and sold with annually recurring revenues. Often multi-year contracts are signed to be able to amortize hardware over time, and enable blended gross margins over the length of the contract to be high (approaching 60-75%). This is more common in situations where vendor takes responsibility to upgrade hardware as needed along the way to provide maximum and highest functionality to the customer. Hardware inventory costs are, over time, passed on to suppliers or third party financing parties in lieu of few gross margin points. Consider robots as a service in factories (ala Formic), or AI-enabled equipment (eg Evolv, Lumafield etc). Hardware innovation will require deeper investigation, experimentation, and understanding of business/revenue models to fit customer needs as well as to maximize value for the innovating company. Strong and experienced management teams work hard to minimize sales friction, inventory costs etc, but also maximize gross margins, customer stickiness, and ability to upsell during the life of a contract.

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Similar to VC, there's a power law inherent in startup decision-making. One big success can more than make up for dozens of small failures. The key is to view these decisions as experiments and opportunities to learn. Over the years, Sanjit Biswas and his team at Samsara have made many feature bets that didn’t work out. Sanjit shares the example of how Samsara tried to apply computer vision to detect defects on manufacturing lines. It ended up being an extremely challenging problem due to the subtle differences between assembly lines and how frequently they change. Instead of being swayed by sunk costs, the team pivoted to a different use case: leveraging the same computer vision technology in their dash cams to detect risky driving behaviors. This bet turned out to be a massive success, and it’s become a cornerstone of their business. Our full conversation here: https://lnkd.in/gGxWpqB7

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Starting a new fun project with Victor Lee - an AMA series with early stage founders. There are many podcast shows featuring successful, famous entrepreneurs. But what about those who are still relatively early in their journey, perhaps just one step ahead? The zero-to-one founders who have recently cracked the product-market fit and raised Seed or Series A capital. They may not have figured out everything yet, but they have fresh, relatable tips and advice to share. We’ll invite early-stage founders for a one-hour AMA session. Afterwards, we’ll create a public webpage featuring each Q&A session with media clips and transcriptions. This will be 100% free and open to the public. Our first AMA (June 11 1pm PST) will feature Will Drewery, whose company (Diagon) recently raised $5.1 million in Seed funding. We’ll get to know Will better and cover topics such as tips on raising funding in this tough environment. It will be a fun AMA, and you can register for free using the link below. RSVP now!

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Impactful Biz, Ops & Investment Roles at Early Startups & VCs: • Chief of Staff to Ex. Head of Product at Google • Founding GTM at the most YC product used by other YC companies in the past four years • Chief of Staff to a Partner at a Top-Tier VC Fund • Head of Platform of a NY State Backed Accelerator • Investment Associate at a Seed Stage Fund Investing in Category-Defining Companies • Partner at a Defense-Focused VC Fund • Chief Revenue Officer of a New Space Company in El Segundo • Venture Capital Analyst at a fund investing in overlooked geographies • Investment Associate at a Spirit-Focused Fund • Strategy & Ops Lead at a Company Focused on Helping Improve Autism • Senior Product Manager at a Company Focused on Building Shopify for Content Creators • Program Manager for a Space Security Company • Open-ended Investment Position at a Top-Tier Accelerator • Biz & Ops Lead for One of the Most Loved Digital Consumer Products 💸 All companies are well-funded and backed by top-tier investors. ⬇ You can find links to the roles above, plus many more, in the comments.

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User feedback is always important. Tools like Amplitude and Mixpanel are excellent for capturing user experiences and improving products, ultimately boosting satisfaction and helping businesses stay user-centric. When it comes to AI, improving models is all about learning, and RLHF plays a big role in optimizing performance over time. With LLMs, traditional deterministic evaluations don’t work as well, and RLHF is typically applied only at the foundation model level. A good example is ChatGPT: its performance improved gradually as they collected data from real usage aka interactions. While users can give explicit feedback, most people don’t tend to do it. That’s why ChatGPT sometimes offers two response options to nudge users into providing feedback, which then helps fine-tune the model. However, traditional RLHF doesn’t apply well to the application layer of LLMs, such as in RAG, agents, or prompt engineering. But there’s potential to rethink this. Combining RLHF with tools like Mixpanel or Amplitude could create a more effective approach to improving LLM applications. Placing users at the center of evaluation and optimization is essential — they’re the ones who know their tasks and needs best.

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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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Go Gaurav Sharma and Capitalize! If you have a 401k from a previously employer, check out Capitalize.

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