One of the things that VC-mentors of mine recommended when we first started Hustle Fund was to start thinking about succession planning now. That sounded crazy at the time, because who thinks about generational planning when they’re first starting a company?
But having now seen a lot of longstanding VC firms go through transitions, I understand why. It just takes a really long time to find the perfect partner and convince said partner to join you and stay with you. It takes time to transition knowledge-sharing, culture, and in essence, the whole business to that set of new partners. That process can take a decade or more for each new partner.
So even as far back as day 1 – as an emerging fund manager – we have actually been looking for our first non-co-founder Partner. And 8 years later, I am so excited to announce the promotion of my colleague Haley Bryant!
Haley has somewhat of an unusual background, which is what I think is a strength of hers in coming to Hustle Fund. Like everyone else on the team, she has entrepreneurial experience – this is a requirement at Hustle Fund. However, her beginnings were not in software. She initially thought she wanted to be a journalist upon graduating from UVA, and she ended up starting her career in a retail store at Apple. From there, she rose very quickly to senior management, running stores that were generating $100 million or more per year in revenue. She later parlayed that management experience into software startups. Most recently, she was the COO of Animalz, which is a SaaS marketing agency and helped them get from near zero to 8-figures of revenue per year. Her operational experience has been extremely helpful to our startups who are going through a growth phase and are struggling with reigning in chaos. Haley has the unique ability to quickly make things more efficient with a combination of tech, people, and processes.
I first met Haley years ago on Flow Club. (Flow Club is a great platform to get work done and is a portfolio company.) She was leading a Flow Club session I attended and she kept everyone on track with their goals. I was wondering, who is this awesome executive? I have to meet her!
Fast forward, she joined our Angel Squad, and I knew that we absolutely needed to work with her. We managed to somehow convince her to get involved with us part-time on the side with our Angel Squad. She and Brian Nichols (GM of Angel Squad) worked so well together in growing Angel Squad in those early days.
Eventually we convinced her to join the investment team. Fast forward to today – Haley has proven to have tremendous taste in deals and already has a number of fast growth companies that she has invested in. She is probably one of the most “value-add” investors I know – she is always willing to roll up her sleeves anytime. She not only helps troubleshoot her own companies, but also hops in and helps the entire portfolio. She truly is a founder-friendly VC. She is such a go-getter and has so much energy. Even after burning the midnight oil, she’s up early the next day to either teach or cycle fast in a spin class. She’s that kind of person. She’s helped us with our fundraises – even from day one when most principals typically do not want to get involved in these types of processes. She is so eager to learn, so fast to learn, and is one of the most efficient people I know in getting work done. Lest you think Haley is a robot, she is also incredibly kind and thoughtful.
TeamLab with the investment team
With this promotion, Haley has set the bar high. I could not be more excited about Haley’s leadership and the future of Hustle Fund.
Please join me in congratulating Haley Bryant, and I hope you get to know her as well!
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Four years ago, we launched our global angel investor community called Angel Squad. It was a bit of an experiment. When we first started, our goal was simple: break down the barriers that have traditionally kept most people out of angel investing – education, check size, dealflow, and networks. Our ambitious goal was to mint 10,000 new angel investors over the course of Angel Squad’s life.
That sounded like a tough goal back then, but today I’m incredibly excited to announce we’ve officially crossed 10,000 Angel Squad applications across 50+ countries!
Beyond Silicon Valley’s Model
Our journey to 10,000 applications reveals there’s an enormous appetite for angel investing globally. We’ve seen Squad applications from engineers in Bangalore, teachers in Buenos Aires, and entrepreneurs in Lagos — proving that great investment potential isn’t confined to Sand Hill Road.
You don’t need to be in a traditional tech hub to be a meaningful startup investor. Our 10,000 applications have come from every point in the globe — small towns in Latin America, the emerging MENA market, and regions historically left out of the startup funding conversation.
One of our members, a professional chef in Turkey, joined the Squad after attending one of our online workshops. Another, a commercial pilot based in Australia, saw our community’s global presence as a way to meet and support local entrepreneurs in the cities he flies to. These stories of global impact aren’t exceptions; they’re becoming the new norm.
Small Checks, Big Impact
When I wrote about our last major milestone of reaching 2,000 Angel Squad members, I highlighted how impactful micro-checks can be for founders. Just a few months later, more and more data points are coming in on how these small investments combined with their networks can be the lifeline for early-stage startups. Recently, a Squad member that works at Nike offered to introduce a portfolio company in the clothing space to one of their execs. One discussion led to the next, and Nike has since become that startup’s biggest client yet. People joke about how VCs try to be “value-add”, but angels who work in specific industries or domains can truly be valuable in opening doors for relevant companies in those spaces. Angel investors catalyze entire startup ecosystems. This is what has made Silicon Valley thrive – its robust angel investing community.
Our Vision Continues
Reaching 10,000 Angel Squad applications is incredible, but it’s just the beginning. Our goal remains to grow to 10,000 Squad members and now we’re moving the target to 100,000 angel investors who can support entrepreneurs globally, regardless of their background or location.
But, for us, each application represents more than just a potential investor. It represents a dream of supporting innovation and of believing that great founders can look like anyone and come from anywhere. We’re not just building an investment community; we’re creating a global network that breaks down economic barriers.
Let’s go!
To everyone who has applied, supported, and believed in our mission — thank you. The future of startup investing is global, accessible, and more exciting than ever before.
To mark this 10,000 application milestone, we’re going to go crazy and give away 30-day Guest Passes over the next 10 days.
To apply for a Guest Pass, simply fill out this Typeform. If selected, you’ll get the full Angel Squad experience to attend our weekly workshops, network with the community, and even invest in startups alongside Hustle Fund.
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At Hustle Fund, we just announced that Dunky AI, our cute, lovable, purple hippo-esque friend has taken our the company and has gone rogue today on April 1, 2025. Hopefully we can wrestle back the company tomorrow!
In the meantime, Dunky AI has chosen to write a strange comic book, set in a mythical place called Hippoland…a world that exists to teach entrepreneurial education. Talk about hallucinations!
While this is all in fun for the day, I’m going to give you a serious behind-the-scenes look at the creation of said comic book and some learnings. This project ended up being a ton of fun and didn’t take long.
If you have imagination, you can be an artist and creator — even if you have zero talent
This is a bold statement and was not possible prior to the last couple of years. I started this project in early 2024 and put very little time into this throughout the year – probably a total of 1-2 full working weeks. But, throughout that year, the technology has only gotten better. This comic book is a reflection of last year’s tech.
Midjourney generated almost all of the images. Adobe Photoshop’s AI tools aided as well. Cartoon people in this book were created based on seeding these AI tools with real photos. In some cases the cartoon representations of my team members were fairly on-target:
These drawings are based on real photos of my colleagues Haley Bryant and Kera DeMars and arguably look pretty similar to their actual likeness.
But, Midjourney didn’t get it right for others on our team, so precision in drawing has a lot to be desired still. I think a lot of generative AI software is good at drawing generic people but not specific people you may have in mind.
In addition, this cartoon of me is based on a real photo of me wearing a grey shirt that reads Hustle Fund. You can see Midjourney takes some artistic liberties in changing the shirt 🙂 :
Generative AI is good at drawing people and bad at drawing hippocorns
This may seem like a silly learning, but extrapolated, this is a big shortcoming of generative AI tools these days. If you want to draw generic people, there are MANY tools that can do this well. If you want to draw a mythical creature that doesn’t exist in the exact form that you are envisioning, this is near impossible. This makes sense, because there is limited to no data for these models to train on. Afterall, as much as my inner voices in my head may disagree, hippocorns do not exist.
But, when you think about blockbuster characters that have done well over history, they are ALL mythical. They are Mickey Mouse and Elmo. They are Pokemon and Yoshi. These characters are all figments of people’s imaginations, and it is really hard to go from your head to paper.
I struggled to get our hippocorn to be close enough to what we envisioned. You can see that it’s not quite right. Our mascot Dunky is not as wide and is not as old. It has buck teeth, which AI often misinterprets as a shirt or an underbelly of white. I did the best that I could in cartoonifying our plushie.
Consistent characters are still a problem
Midjourney (and others) launched a consistent character feature in their software during the creation of this comic book. But, this feature is not actually that accurate, especially when it comes to specific objects (especially made up creatures like hippocorns). This is probably the top problem that still needs solving in generative AI. Once this is solved, we should see independent Disney-competitor brands started by 1-person design shops (who may not even be artists)!
Much like how we now have vibe coding and 25% of YC companies in the latest cohort have codebases largely written by AI, we will see the same for design and art. Along the way in doing this project, I met a kid who is in a university but spends almost all of his time consulting for companies who want to generate images and need his help with AI prompting. I don’t think this skill or job stays forever, as it will become easier and easier to prompt images and videos without a consultant, but I do think it represents a shift in a how people will do design. It won’t be by hand anymore. Maybe it will be 80% by AI and 20% by hand (editing the parts that need help that AI can’t get right).
When Disney came out with the original Snow White and the Seven Dwarfs, it cost $1m+, which was a crazy amount of money back then! They maintained edge in this world of character creation, because they established a large capital moat and could employ the best artists and storytellers to create hit after hit. Even when they didn’t hit, it was ok, because they had more shots on goal coming soon. Even when they ran into a wall and ended up buying Pixar to invigorate the brand, stories, and technology, money was the moat. Very few studios could even afford that.
Now, there is no moat for anyone, because the cost to create blockbuster movies and cartoons is so close to dropping to near zero cost. I’m excited to see the next generation of characters and worlds that will influence the world.
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What happens when we fast-forward a few years and think about the rapid advancements in artificial intelligence (AI)? That’s the question that sparked an invigorating conversation between my fellow founder friends Adam Spector, Eric Bahn, and myself.
The tl;dr? Few jobs are safe and what made you successful before will not make you successful in the future. In the long run, humans will adapt and will create other jobs, but I’m worried the transition period will be brutal and that is just around the corner.
The AI Takeover: No ones jobs are safe
For years, the conversation around AI’s impact on jobs has largely focused on automation replacing blue-collar workers. But in reality, technology is coming just as hard for white-collar professions. It’s coming for everyone. We’re already seeing so many legal, financial-related, marketing, sales, operations, developer, and design focused AI tools that can do a lot and can take over a lot of workflow. (Note: my AI writing tool overlords are biased in writing this post as well. 🙂 )
AI can and will have the ability to analyze, generate, and execute at a scale humans can’t match. If your job involves anything operational, analytical, factual, etc, AI can do it better.
At Hustle Fund and in my personal life, for example, AI is already embedded in our workflow. Off-the-shelf tools help us with everything from writing, emailing, marketing, research, portfolio operations, and more. We even use AI to make investment recommendations (note: this is still very much in training mode). And we are just scratching the surface.
I don’t think most people fully realize just how much AI is going to take over their jobs, in part, because right now, these tools probably only absorb 25-50% of the work currently. A human is still in the loop. So it feels like people are still needed — AI doesn’t feel that significant. But that’s 25-50% of the work that I used to do myself that I no longer do. So as that becomes a higher percentage overtime, it means that you will only need 1 person to do a handful of people’s jobs. This is going to hit people all at once.
This doesn’t mean humans will be completely out of a job. There will still be a need for oversight, whether it’s to fact-check AI-generated legal documents, ensure compliance in financial decisions, or safeguard against AI hallucinations. A lot of jobs will still require a human-in-the-loop. But the number of people required to complete so many projects will shrink dramatically.
Fewer Workers, More AI
Entire business functions that once required large teams will soon be streamlined with AI. Take operations and marketing, for example. Many companies already use AI-powered tools for content creation, customer engagement, outbound sales, and ad generation and targeting. These tools are only going to get better, reducing the need for many people. Agencies, which have long been powered by people, will need to adopt these tools aggressively to stay alive.
In engineering, AI is transforming how software gets built. Tools like Cursor got to $100m+ ARR just in the first few months! And there are many other tools now that enable non-technical users to develop apps with minimal to no coding knowledge. Fewer engineers will be needed to build most applications – except for those working on groundbreaking technology. This will both expand the market for developing software as well as shrink the number of people needed for projects.
Even design and creative fields aren’t immune. AI is already generating static images, videos, and even presentation designs. While designers will still play a role in reviewing and refining AI-generated work, the long hours they previously put into creating won’t be needed.
Here’s a teaser (stay tuned for the launch) of my upcoming comic book that I did myself with zero talent in my spare time. I can only imagine all the new Disney-challenger brands that can be built with small teams of people with artistic talent.
The Industries That Will Survive (For Now)
While AI will dominate many sectors, there are still areas where humans will continue to excel —at least in the short term.
Regulated Professions – AI can assist with diagnosis, documentation, billing codes, collections, and communications in medicine. But due to regulations, they will continue to require major human oversight – doctors, nurses, etc will still be very needed.
Human-Centric Jobs – The ability to persuade, lead, and emotionally connect with people is still a human advantage right now. Sales, leadership, and high-level strategy roles will continue to be valuable. But, ChatGPT is quite good at coming up with jokes to make me seem funnier than I actually am to impress my colleagues, so I may be fired at Hustle Fund soon.
Creative and Entrepreneurial Work – While AI can generate art, music, and writing, true originality and vision remain human traits. Those who can blend creativity with AI-powered tools will thrive. Also, all the generative AI tools are very bad at drawing hippocorns. This will need improvement. Humans FTW.
Energy and Infrastructure – AI requires massive computing power, and computing power depends on energy. This brings us to the next big shift: the return of energy dominance.
Distribution – Everyone will be forced to build a brand; when software becomes a commodity, those with large reach will win regardless of the field.
The Next Power Struggle: Energy
In the past, oil and energy ruled the world. Then came the software era, where companies like Google, Facebook, and Microsoft held the most power. Tech, for years now, has dominated the list of most valuable companies in the world. But now, as AI commoditizes the software world, the power is shifting back. The new kings and queens of industry will be those who control compute power and energy. If you believe AI will be everywhere, then the real question becomes who owns the compute power? Running AI models at scale requires vast amounts of energy. I do think the efficiency will get better, but we’ve barely scratched the surface on what AI models we want to run and where.
We will find new ways to use significantly more energy in the future than right now. For example, you can imagine wanting to build a holodeck of our memories or create virtual people who feel like live people, whom we want to talk to or consult. To build these systems, you could imagine we’d need a TON of data — more than we have now. This is where Justin Kan’s original vision for Justin.tv fits perfectly. Imagine recording your whole life in a multi-dimension video? You could record, query, and relive any moment. Moreover, other people could experience or interact with other people’s moments, knowledge, and thoughts. We would all be able to learn directly from the top teachers in the world. We would all be able to “meet” celebrities. Right now, there are websites where people can “meet” a digital celebrity or influencer through a chatbot. Fast forward, those chatbots will be much more “real” and sophisticated and can even act as digital virtual assistants to handle a lot of work for each person. These bots will be able to triage through so many more opportunities than busy famous people can handle today, which means that needing a warm introduction will become less important (or not important at all). The only reason warm introductions exist today is that famous people get bombarded with thousands of opportunities daily and cannot possibly go through them all. But that’s a problem that goes away with better digital triaging.
The cost to do this today would be tremendous and not feasible. But all of this is possible to do if you had unlimited compute power. And that’s pretty exciting for the world. Knowledge, access to people, will all be much more accessible and will level the playing field in many ways. Knowledge and connections will become much more commoditized in the future.
The future
Given the confluence of all of this, it’s both an exciting and worrisome time. On one hand, AI will be able to bring so much more to everyone — more knowledge and more access. On the other hand, in the short run, so many people will be out of a job. And that makes me worried.
Sometimes people ask me what would I have my kids study in this new world? I don’t have a great answer to that, but I can tell you that the jobs most people recommended to children during my youth – largely analytical jobs – are not the ones I would recommend. Given the next several years and decades will be very tumultuous, I think the best way that kids can prepare themselves for the future is to be entrepreneurial, creative, and be great with people. And it helps tremendously to build a brand. There’ll be a lot of change that people will need to constantly adapt to — it will be a tough time. And, like everything else, things – such as AI – start slowly and then hit you with a barrage and that barrage is coming.
When news of DeepSeek hit recently, friends and family came to me asking: What does this mean? Is this the end of NVIDIA? Is AI taking over? Should I be worried about my job? The stock market, predictably, went into a frenzy.
But taking a step back, the real story behind this isn’t about the “fall of NVIDIA” or some existential AI threat. The real story is that AI development just got a lot more accessible which is great for consumers and developers —and that changes everything.
DeepSeek is an AI model that came about as a side project from a company in China. It competes with the likes of OpenAI and Anthropi, and it is open source. But two things made DeepSeek particularly interesting:
It claimed to train its final model at a fraction of the cost that OpenAI and Anthropic have spent training their models. Whether that’s entirely true is debatable, and many people on the internet think they’re lying or that they’re hiding something, but whether they’re right or wrong actually doesn’t matter IMO.
It was built with NVIDIA’s H800 GPU chips – not their most powerful chips.
This second point is where things get interesting. For years, NVIDIA’s A100 and H100 GPUs have been considered gold and necessary for AI training—so much so that their availability (or lack thereof) has shaped the AI industry. I have portfolio companies who had been clamoring for chips and couldn’t get any. But DeepSeek proved that they didn’t need NVIDIA’s most powerful chips (they chips they used had the same level of computer power but less bandwidth). In fact, because they are based in China, where it’s impossible to get access to A100 and H100 GPUs, they were able to train their model on less powerful computer chips, which was considered near-impossible. This is why NVIDIA’s stock price is down – no longer do AI companies need their most powerful chips if you can just take a page out of Deepseek’s playbook.
I think, for NVIDIA, though, this doesn’t mean extinction. Powerful chips will always be in demand, and people will just use them to do more. (This is not investment advice!) But DeepSeek’s success opens up a whole new market. It was previously thought that if you want to develop expensive AI models, you would not only need tech talent but also a lot of money to buy compute power. No longer is that true, and NVIDIA is no longer the gatekeeper.
The Real Winners: Developers and Entrepreneurs
For the first time, any developer can, in theory, develop new AI models. This is a game available to anyone—not just deep-pocketed tech giants. Open-source combined with less expensive infrastructure means that a new wave of developers and startups can build AI-models without requiring hundreds of millions in funding.
But the broader trend of decreasing costs has been happening for decades already. In the 90s, launching a tech company required massive capital. Startups were building their own servers in closets. But when cloud computing came along, AWS made infrastructure cheap and accessible. No longer did you need to raise $5m to own and run your own infrastructure. Now, AI is hitting a similar inflection point.Developers can develop AI models without NVIDIA’s chips, and in many cases, without raising millions in VC money. That means startups can bootstrap or seed-strap in ways they never could before.
In fact, we’ve been seeing this trend for a while now. Many of today’s AI entrepreneurs aren’t raising huge rounds of funding. Instead, they’re launching lean, capital-efficient businesses that can reach $1M-$2M in revenue without taking on significant outside investment. This is a fundamental shift. AI isn’t just for the big players anymore.
The Real Losers: Venture Capitalists
Ironically, the group that should be most worried isn’t NVIDIA, other big tech companies, AI startups, or independent developers—it’s VCs.
For decades, venture capital thrived on the high cost of starting a company. In the early internet days, founders needed millions to build and scale — those servers were not cheap.
But the cost to build a business has been coming down over the years. But VCs were still needed, because tech became a huge roaring industry, and there were not enough engineers to support the industry. The cost to hire engineers in Silicon Valley zoomed up. There was more demand for engineering talent than supply. And this is what has kept venture capitalists in business.
But then a decade of coding bootcamps, a new generation of students entering computer science in droves, and the proliferation of no-code tools have brought that cost down again. These days, many of my founders are using AI tools to write code for them. For most software companies, you don’t need specialized computer software knowledge to build a multi-million dollar business.
The initial wave of AI put a momentary blip in that trend, because so much capital was required to train AI models. But now, when it no longer takes a ton of money to build a viable AI startup, what happens to the venture capital industry?
Startups don’t need as much money. AI tools make it easier for small teams (sometimes just one or two people) to launch and scale products. People are using AI tools to write code and increase productivity.
The infrastructure costs have now decreased. We saw this with server costs in the early internet wave, and now we’re seeing this with AI training costs.
You don’t even need to be an engineer. Many of these tools are so user-friendly these days that you don’t even need to be an engineer by training to build and run a software company.
So what ends up happening with the confluence of these trends?
Markets are more crowded. With lower barriers to entry, there’s more competition. If 200 startups are building the same AI-powered tool, it’s hard for one to achieve dominance—and hard for a VC to get a 100x return. But, founders can still make money. You can still have 200 companies in a busy space, where even if you’re in the long tail, you can make millions of dollars per year and do well for yourself. Moreover, these outcomes for founders would probably be similar to building a billion dollar business with venture capital money and taking a small portion of that exit home. That’s great for entrepreneurs! Just not great for VCs.
Companies struggle to find moats. If anyone can spin up an AI-powered product in a weekend, it’s difficult to build a defensible business. This can actually be ok if you’re a 1-2 person shop. You’ll still have business even if retention isn’t perfect. But again, this isn’t a good situation for a VC to invest in.
Founders can still make great money—but VCs are finding it harder to generate the outsized returns they depend on.
Where Investors Can Still Win
So, if venture capital is struggling in this new landscape, where does investment still make sense in software?
Super-early-stage bets: While it’s getting cheaper to launch a startup, some founders still need pre-seed capital—particularly those who haven’t yet reached revenue yet. Many founders will need some level of capital to survive and experiment with before they get to ramen profitability. (I’m obviously talking my own book here.)
Big, capital-intensive ideas: While small AI startups are thriving, some ambitious projects that go beyond software still require massive funding. Think AI hardware, biotech, space, or deep-tech startups where money itself is one lever of a competitive advantage. This is a great place for large VCs to play. Very few competitors can go after these opportunities and they can be defensible because of the capital and knowledge moat.
Uniquely defensible businesses that have deep ties into workflow. There are going to be software businesses that are so entrenched in workflow that even if they are copied, the sheer distribution edge is enough to win. However, many of these opportunities will likely reside with existing large software incumbents.
International opportunities. US investors have long shied away from global markets, because they don’t understand them. But ironically, this is where the greenfield opportunity lies. You can find great companies that have limited competition and favorable valuations. And, now that companies require less capital for software companies, the lack of capital in these regions is a much much lower risk.
The Future: AI Everywhere
DeepSeek is just the beginning. AI is about to become pervasive.
The cost of building AI-powered products is dropping fast, and that means AI isn’t just something that happens in big tech labs—it’s something that happens everywhere.
Developers will integrate AI into everyday applications, making businesses and workflows dramatically more efficient.
AI-powered startups will proliferate globally. This has already been happening for a while.
There’ll be a lot of 1-2 person startups, and some of them will become massive with very limited capital raised. This is where we’ll see the billion dollar single-founder startups emerge.
Yes, NVIDIA will continue to sell chips. Yes, OpenAI and Anthropic will continue improving their models and will lose pricing power, because they will have serious competition. But, they will all be fine. Consumers will be great. AI development is no longer restricted to the elite few. We’re just at the beginning and that’s pretty exciting.
I’m super psyched! Our global angel club called Angel Squad, led by Brian Nichols, has reached 2000+ members this past summer across 40 countries! To me, this isn’t just a vanity metric. Angel investors play a crucial role in nurturing startup ecosystems — much more than VCs, so growing and nurturing angel investor communities worldwide is really important to me.
Silicon Valley’s Secret Sauce
Silicon Valley’s long-standing success as a startup hub is often attributed to its weather, schools, and legacy of tech companies. However, I disagree. There are plenty of places in the world with permutations similar to this that don’t have anywhere near the startup density that the San Francisco Bay Area has.
I think, a less obvious, yet critical factor for Silicon Valley’s success is its vibrant Angel investor community. Unlike the common perception that Silicon Valley’s Angels are wealthy individuals writing $25,000 checks at a time, many people invest much smaller amounts here.
For instance, early Uber investors included people who invested as little as $5,000, which became worth $25 million by the time of the IPO! What this illustrates is that angel investors don’t have to invest a lot of money in one go, and finding winners can be life-changing for small angel investors.
This culture of numerous small-scale investments enables a large pool of resources and support for many startups in the Bay Area. Early-stage companies benefit not only from financial backing but also from the introductions and advice that these investors also provide. Such a supportive environment allows startups to thrive and grow.
The Ripple Effect of Angel Investments
A robust Angel investor community can significantly impact a startup’s trajectory. With small checks, startups can secure essential early funding that institutional investors often hesitate to provide. This early support is crucial for the initial phases of a startup, where risk is high, and traditional funding is scarce. In addition, small check investors can often lead to larger checks later by opening doors. One of our portfolio founders at Hustle Fund named Steven Fitzsimmons (Fitz) broke down the anatomy of his seed round a few years ago. His smallest investor (who invested $5k) was the most helpful of all. Small checks lead to both introductions and more checks.
In contrast, many other cities outside of Silicon Valley, despite having either good tech ecosystems or wealthy individuals, lack such a vibrant Angel network. Wealthy individuals in these areas often do not reinvest their money and time back into their local startup ecosystems, which stunts the growth of potential startups in the area. Places like Boston, for example, despite its tech prowess, academic strength, and successful individuals, has lacked for decades a strong Angel community of hundreds of active individuals until more recently with the emergence of active angels from newer successful companies like HubSpot and more. (And I’m sure many of my Boston friends will disagree and say they’ve been actively investing for a long time now, but they are the exception not the rule to the geography :))
Growing Angel Communities Globally
The rise of Angel investor communities in cities like New York and Boulder also illustrate the transformative power of these networks. By fostering a culture where successful individuals reinvest in new startups, these cities have developed robust startup ecosystems. Neither of these cities were previously known for being tech hubs. This model shows that there is no special formula exclusive to Silicon Valley; any city can replicate this success by building a strong, active Angel community.
Angel Squad’s Vision
Hustle Fund’s Angel Squad aims to replicate and expand this model globally. With 2,000 members already on board, the goal is to grow to 10,000 and eventually 100,000 Angel investors. We want to empower entrepreneurs everywhere — not just in the US.
Let’s go!
The journey of Angel Squad is just beginning, but I’m so proud of Brian and team for the progress they’ve made. If we can continue to help great startups globally get access to more capital — to truly have free markets — that would be the dream. Let’s go!
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