DVx Ventures

It used to be that deep domain expertise was the most valuable asset a founder could bring to the table. In the Web 1 era, if you wanted to disrupt an industry, you had to be a domain expert. You needed to know the ins and outs of the industry, to have suffered the pain that you were solving for,? and you had to have credibility within the industry. Your product was important, but your knowledge of the industry was paramount. Fast forward to the Web 2 era, where it became all about the tech. Founders and investors began to obsess over the product above all else. Oftentimes, this meant technologically proficient founders building companies in an industry or space where they had little expertise initially (e.g. the health tech boom of the late 2010s). Instead, founders obsessed over building a perfect product, including hiring a big team of engineers to win with product and tech.? Now, we’re entering a new phase. With the rise of Ai and automation, the tech itself is becoming easier to build. You don’t need a deep technological background - or a huge team of engineers - to build a good product. What you do need is insight (and you need to it be really good!) That’s why I think that we’re about to shift back towards the Web 1 mindset where the advantage goes to the founders who really understand the space they’re in and the problem they’re solving. At DVx Ventures this operator edge is what we’re betting on and we’re always looking for. We think winning requires to know more about the customer and to understand the problem we’re solving better than anyone else.

The internet supercycle started in 1997. We’re 27 years in, and there has not been a let-up. AI infrastructure is like the internet. We’re at the start of a supercycle that is going to go on for decades to come. For investors, this means there is a massive opportunity. Great to chat with Reed at Semafor about what we’re building with VistaShares. Adam Patti https://lnkd.in/eFYXHTtJ

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Nvidia is a headline, but it’s not the story. There’s so much more that goes into an AI data center. Cooling, racking, storage, and high-voltage electrical equipment all play a critical role in the unfolding AI supercycle. We created $AIS to include about 65 public stocks that reflect the full AI stack, giving investors exposure to the full value chain.? Some of these companies aren’t household names, and they reflect the parts of the supply chain that we rarely think of when we think of AI. Still, they are crucial to the success of this technology – and they represent a massive investment opportunity. Great to join Frank Holland on CNBC this morning to discuss $AIS and everything Adam Patti is doing with AI investing at VistaShares. https://lnkd.in/efaeT9te

AI is transforming VC funding, and not in the way you think. Of course, many VCs are investing big dollars into AI-related startups, with many VCs allocating huge portions of their capital solely to AI. But AI will also have a macro-impact on how VC funds are used within startups - whether or not they are an AI company. Until now, if you wanted to build a SaaS company you had to hire engineers to write your code. Engineers are notoriously expensive, which means that you have to spend a lot of money to build out that team. Scaling tech teams is one of the main reasons why early-stage startups raise VC money. Similarly, bringing the product to market requires expensive sales and marketing resources, and this requires even more capital. But as AI becomes more and more sophisticated, it will be able to write a lot of the code needed to create a product. Startups will still need engineers, but they won’t need to build out a big team just to build the product and start scaling. Similarly, a lot of sales and go-to-market activities are being dramatically accelerated and streamlined with AI. Thus the VC dollars and the time needed to achieve initial tech and sales milestones reduces significantly. There will still be a big need for VC funding, but. as AI becomes more and more ingrained on the tech side, startup differentiation (and spend) will shift from tech and sales to new activities, and the VC funding will shift accordingly. I’m already seeing this with several of our startups at DVx Ventures: our Tactix team built game-changing tools for restaurant owners in just a few weeks, that would have taken months and thousands of dollars in the pre-AI world. Our Atomic team is achieving exponential growth with a fraction of the sales and marketing budget it would have taken them a year ago. I’m curious if other VCs and founders are feeling this shift already, and whether the funding required to scale is reducing or is just shifting from tech-sales to other activities?

A while back, someone asked me which EV ETF to buy. I started looking into the options and was shocked to find that many EV ETFs looked a lot like the S&P 500, packed with stocks like Apple, Google, and Nvidia. No doubt those are great companies, but not exactly core to EVs. ?And investors deserve full exposure to the profit pools of Supercycles, not just a retread product of the S&P 500. That sent me on a journey that eventually became VistaShares, one of DVx’s newest portfolio companies that helps people invest in Supercycles – the massive technology-driven shifts reshaping industries, including electrification.? Our approach is different -- we take the build sheet of an industry (like everything that goes into an AI data center) and weight the stocks based on their % of that build sheet.? Not by market cap.? That gives balanced exposure to stocks represented by their profit pools and contributions to the Supercycle Under Adam Patti's leadership, we’ve launched $AIS, our first ETF designed to capture the full AI supply chain. Our investment approach is about unlocking the full value of every part of the AI value chain? – not just user-facing companies. Most AI investment strategies focus on the biggest, most well-known names. But the real value lies deeper in the ecosystem (the infrastructure, semiconductors, the fiber, the networking software, the data centers, and the cooling systems that power AI’s growth). Our approach makes this kind of investing available to retail investors, not just wealthy individuals who have access to sophisticated hedge fund strategies. Great discussion with Scarlet and Eric on Bloomberg about all things supercycles and AI investing. https://lnkd.in/efFS3kuq

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Successful businesses know how to adapt to competition, whether it’s from other companies or through policy changes. Still, weathering these challenges is never easy, and it can make it hard to know what the future holds. Great to chat with the Closing Bell team about tariffs and competition in the auto sector.?

Tariffs are a nightmare for businesses - and especially for planners They add uncertainty and risk in an environment where planners are already doing everything they can to manage both - taking the difficult problem of balancing supply and demand and making it exponentially worse. At Atomic, we know this firsthand. Our team led demand & supply planning at Tesla from 2017 to 2022, navigating trade wars, COVID, and relentless supply shocks. There seemingly wasn’t a single week without some external crisis—some unexpected risk that forced us to adapt on the fly. Our secret? We built a system that updated daily, always adjusting in real-time to keep us moving in the right direction. With a click, we could incorporate new data that impacted procurement, production, and delivery—allowing us to stay ahead in an unpredictable world. That’s why we started Atomic—to bring this level of agility to every brand. So, how do you survive (and thrive) in a world of growing uncertainty? - Plan constantly – Static plans fail. Dynamic ones win. - Reduce your exposure – Know your risks, diversify, and adapt. - Be ready to scenario plan – Run the numbers before the crisis hits. The good news? We can get you up and running on Atomic in weeks. If this resonates, let’s talk.