Precursor Ventures' Charles Hudson, & How The ML Toolchain Creates Big Opportunities For CEOs & Lead Zeppelin's Complete Client List - D.F.A. #10:
Lead Zeppelin's Customers and How They've Raised Real Capital With AI-Enabled Lead Generation
I met Charles Hudson for the first time nearly 15 years ago at the Interplay social gaming conference, which I put on with Vanessa Camones in 2008. It was a pioneering social gaming conference, and Charles, Mark Pincus, Bret Taylor and a few other folks helped me put it on. I don’t think anyone there quite understood how big social gaming or social media would become.
Shortly after that, Charles began his career in venture capital, forming Percursor Ventures in 2015. To learn the basics on Charles Hudson and Precursor Ventures as well as any upcoming funds, you can check out the Precursor Ventures Investment Criteria.
One of the main reasons Charles was on my shortlist for an interview was because nearly every time he’s written a blog post, I’ve thought, “Man, I wish Charles was blogging *way* more often.” In recent months, his posts have covered consumer investing, the decoupling of small and large VC firms, the rebundling cycle in B2B SaaS and much more. I figured the way to get Charles to share as many of his best takes and as much of his story about how he got into VC, and his first 4 funds, would be by doing an in-depth interview.
I remember when you began raising your first fund. What was it that made you want to get into venture capital specifically, rather than some other kind of investing?
When l was in high school, I actually worked in a local brokerage office. In exchange for helping the person who ran that office and the brokers with some simple administrative tasks, I had access to the firm’s equity research. I also got to hear what stocks clients were buying and selling. It piqued my interest in the world of investing. I didn’t actually know anything about venture capital at that time, but I started a small personal account and started trading stocks.
When I was in college, I was pretty involved in our student-managed investment fund and I was pretty sure I was going to pursue a career investing in public equities. However, during the summer of my junior year I worked at a web 1.0 company called Excite@Home. While I was there, I met someone who introduced me to Gilman Louie, who was then running In-Q-Tel (the CIA’s venture capital arm). I didn’t know much, if anything, about venture capital. But the job sounded really interesting and it was a way to combine some of the analytical work that I enjoyed when it came to evaluating publicly traded companies with the opportunity to learn more about cutting edge tech companies. My plan was to do it for a little while and then try something else. In the end, it was a great fit for my interests and I have spent the majority of my career investing in private companies.
There’s been a lot of hype around AI being very insulated or safe as an investment class in venture (40%+ CAGR, etc.) in the last 3-6 months; what’s your take on this?
I continue to wrestle with how to invest in AI companies. I don’t have the technical background to go super deep on some of the more infrastructure-related areas of AI. Given recent fundraising announcements, there is clearly an opportunity in that category. And on the application side, I still have these lingering questions about defensibility and what it means to build a really big scalable business using AI when so many companies are using the same core tech in very similar ways. I am not sure that there is any such thing as a “safe category” when you are investing at the stage where I play, but the dollars rushing into AI-related companies certainly suggest that investors believe that the category will create some massive winners.
Any advice for emerging fund managers raising their first fund right now, in terms of how they work with LPs and family offices?
When I was first getting started, someone told me there’s never a good time to raise your first fund. If you start out when times are good, there’s lots of money in the system and hard to get LPs to pay attention to your fund. If you start out when times are bad, there are fewer other firms raising but you’re launching into market headwinds. So I don’t think it’s ever easy to raise a first time fund for most emerging fund managers I’ve met.
My one piece of advice for folks is to be clear about the minimum fund size needed to prove out your strategy. In 2020 and 2021, we saw a lot of debut funds that were much larger than typical first funds. I think that time was an anomaly and there’s a lot of good work and proof you can generate with a smaller debut fund that still allows you to execute your strategy. Trying to raise a first-time fund with a really big target is harder to do today than it was a few years ago and likely isn’t necessary for most managers.
What are concrete steps that non-BIPOC investors can take, especially in the current funding environment, to be an ally? I often think of the fact that Black founders are over-advised and under-resourced
I would agree that BIPOC founders are overmentored and underfunded. As Tiffani Bell said a few years ago, “hire or wire”, and I still think that’s true. There are many firms in our industry that don’t have a single BIPOC person on their investment team, and I think those firms are missing out. There is a lot of great BIPOC talent looking to break into venture capital, and I think the industry could do more to give those folks opportunities. The other thing is to find BIPOC-led companies and invest in them. Hiring talent and wiring for investment are the two strongest ways to support BIPOC talent.
What are the top 3 music albums or playlists that power you through the workday (or your workout if you don’t listen to music while you work)?
Great question! I listen to a lot Drake on Spotify and I tend to get a lot of music inspiration from a few Peloton instructors whose taste I like.
Lead Zeppelin Investment Firm Client List & Pricing
Over the next few weeks, you may see a bit more via email about Lead Zeppelin’s investment firm clients. At this point, there’s eight of them, and these clients have now raised a total of $38.5M with them. The way it works is simple. Clients choose a plan, and then every day they receive somewhere between .6 and 1.8 leads. These leads are typically LPs or family offices. The investment firms typically do a brief intake call to get to know the potential investor, and if it’s a good mutual fit, they continue the conversation.
To learn more, feel free to check out Lead Zeppelin’s pricing page or book an intake call.
I’m The CEO, Why Should I Give A Sh*t About The ML Toolchain? How CEOs Can Address the GPU Shortage and Leverage Emerging Business Opportunities
[This post comes from the Lead Zeppelin blog here. To read more posts on how to get LPs, AI and other cool stuff like that, check it out.]
Introduction
Being a CEO ain't for the faint of heart, especially in the tech era we find ourselves in. And if you're at the steering wheel of a decently large organization, say between 250 and 5,000 employees, you're juggling a whole other level of complexity. Now, throw in a rapidly shifting AI landscape and a global GPU shortage [those are the chips that power AI machines], and you've got yourself a bit of a rollercoaster ride in front of you. This blog post is going to explain why.
Good news: I've been diving into this stuff headfirst and I'm here to share some insights. In fact, I recently tuned into episode 135 of the All-In Podcast ([link]), and let me tell you, it was a bit of a wake-up call. So, in this piece, we're gonna unpack these developments, make sense of the whole M&A hype cycle, and explain how all this might play out for businesses like yours. [Sometimes the All-In Pod briefly touches on subjects that really deserve a much bigger “unpacking” and this is one of them. Thanks to Sacks, Calacanis and the gang for bringing this one up!]
Understanding the AI End-to-End Toolchain and the GPU Shortage
A toolchain is like a recipe for building something. Just like how a recipe tells you the steps to make a cake - from gathering the ingredients, to mixing them, to baking the cake, and then decorating it - a toolchain tells you the steps to build a program or system. Each step in the toolchain uses a different tool, just like each step in a recipe uses different ingredients or kitchen utensils. So, it's basically a set of tools and steps that you use to create something.
For any CEO leading a company of 250 to 5000 employees, understanding the AI toolchain is no longer optional – it's a necessity. This process, involving data collection and preparation, model development and training, and model deployment and management, is becoming a fundamental part of many business strategies. The quality of your data directly influences the accuracy of your models.
I’m The CEO, Why Should I Give A Sh*t About The ML Toolchain?
1. Competitive Advantage: Understanding the ML toolchain is essential for staying competitive in today's data-driven economy. From improving business operations to delivering personalized customer experiences, ML capabilities can help CEOs drive growth, increase efficiencies, and create unique value propositions. With the rise of AI startups and the M&A activity in this sector, it's clear that businesses which effectively utilize ML stand to gain a significant edge over those that don't.
2. Operational Efficiency and Cost Savings: Knowledge of the ML toolchain can help CEOs strategically allocate resources and manage costs. For instance, being aware of the ongoing GPU shortage can help them plan for hardware investments and potentially explore alternatives such as cloud-based AI solutions or optimizing existing resources for better performance. Similarly, understanding how tools like those offered by AI Squared or similar firms can integrate AI into existing applications can save significant time and money compared to building new applications from scratch.
3. Future-Proofing the Business: The ML toolchain is not just about the present; it's also about preparing for the future. As AI and ML become more pervasive, businesses that do not adapt risk becoming obsolete. By understanding the ML toolchain, CEOs can lead the charge in implementing AI and ML strategies in their organizations, ensuring that they stay relevant and sustainable in the long term. This includes keeping abreast of emerging AI trends, investing in the right technologies, and fostering a culture of continuous learning and innovation within their companies.
[To read the rest of this post, go here.]