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Influential entrepreneurs like Paul Graham and Naval Ravikant always preach the need for startups to have founders-turned-investors on their cap table. As Ravikant puts it, “founders want to know that the people they are taking money from have first-hand experience.”
His platform AngelList has helped individual founders-cum-investors source and participate in deals via collectives. However, some venture firms have taken this up a notch by bringing founders to create a fund and invest together.
Today, one of such, MAGIC Fund, a global collective of founders, is announcing that it has raised a second fund of $30 million to continue backing early-stage startups across Africa, Europe, Latin America, North America, and Southeast Asia.
Since the firm’s first fund launched in 2017, MAGIC has invested in 70 companies at pre-seed and seed stages across these emerging markets. Some of these companies include Retool, Novo, Payfazz, and Mono.
MAGIC Fund has 12 founders who act as general partners. TechCrunch caught up with managing partner Adegoke Olubusi and operating partner Matt Greenleaf to learn more about the fund’s thesis and activities.
Olubusi, who had built and exited a couple of startups over the years, also dabbled with angel investing for some time. In 2017, Olubusi’s current startup Helium Health got accepted into Y Combinator. It was there he met more founders like him who were angel investors with impressive portfolios. The interesting bit? Each founder wanted to invest in other companies during YC’s Demo Day.
“So about three years ago, I was at YC, and I was going to invest in my own batch. I was pitching on the day, but I was also listening to other pitches. However, it wasn’t just me; there were many other founders as well,” Olubusi said.
After building and exiting multiple startups, some founders turn into angel investing to support startups and their ecosystems. However, most of them tend to go alone and are stuck with cutting checks in their local markets, which limits opportunities.
Some MAGIC portfolio companies
Here’s a scenario. In 2016, when unicorns Flutterwave and Kavak raised their seed rounds in Nigeria and Mexico respectively, an African biotech founder who knew about Kavak and a Latin American edtech founder interested in African fintech would not have had the capacity to evaluate those deals even if they wanted; the reason being a lack of reach and experience in both the industry or geography.
Olubusi and the other founders knew this would be a limitation in the long run if they went solo. Thus, they decided to create MAGIC. The idea was to bring global founders together with diverse skillsets in diverse industries and geographies to evaluate deals better and drive value for each other. Hence, they can participate in two unicorns instead of one.
“Instead of us investing individually because obviously, we have somewhat limited capacity in terms of how much time we have as founders because of our respective companies, why don’t we collaborate on a strategy together and co-invest together?”
“The way we thought of MAGIC was a fund of micro funds built by founders for founders,” Greenleaf continued.
In some of the personal conversations I’ve had with founders about their investors, a recurring theme has been that the most useful investors didn’t necessarily sign the biggest checks. It’s a theme Olubusi also relates to all too well.
“It was like every time we think about it, everyone who gave the most money rarely had time for us. It was so frequent that we all identified this as an actual thing. What actually drove value for us were other investors who were founders and operators, and other experienced people who were able to help us find product-market fit and fight regulators. These were actually the people in the trenches with us.”
Olubusi believes the early-stage part of investing, particularly in pre-seed and seed, is where VCs who are founder-operators find their sweet spot. They are precious when startups are trying to figure out product-market fit. And unlike traditional investors who are looking to get multiples on investments, Olubusi argues that for founders-investors, what matters is how much value they can drive for startups.
Image Credits: MAGIC Fund
MAGIC’s play is even more essential considering that it also plays in emerging markets where on-the-ground operational help is needed in industries with numerous unknowns and uncertainties.
“There is so much money in the market now and early-stage decision making at pre-seed and seed should be left in the hands of founders. Because think about it really, to make an evaluation of whether I should invest in a healthcare or fintech company in Africa, it makes sense to have those who’ve spent years battling through it in the trenches make those decisions. And what we’re trying to do with the fund is publish as much information as possible and keep performing at the 100 percentile and say this is still the best strategy and is very scalable.”
MAGIC Fund 1 was $1.5 million and Olubusi says the investments performed 5x over the period of three years. As some of these companies exited, their founders invested in MAGIC and came on board as Fund 2 partners.
MAGIC has also enlisted additional investors who, according to Olubusi, are respected for their investing abilities and ecosystem support. For instance, Olugbenga Agboola, Flutterwave CEO, is known across the African tech ecosystem as a founder who goes out of his way to help established and up-and-coming fintech companies. Hendra Kwik of Payfazz has such a reputation in Southeast Asia as well. They, alongside other founders, join MAGIC as limited partners.
Per the firm’s statement, one-third of the entire fund was contributed by the founder GPs. For its LPs, diversity play is considered as 50% of them are black while 33% are women. Some of them include Michael Seibel, Tim Draper, Rappi’s Andres Bilbao, Paystack’s Shola Akinlade, Katie Lewis, and Octopus Ventures’ Kirsten Connell. For its partners, MAGIC has brought on the likes of Stitchroom’s Tom Chen, Medumo’s Adeel Yang, Juice’s Michael Lisovetsky, and Troy Osinoff, and Evercare’s Temi Awogboro.

Magic Fund 2 will be writing $100,000 to 300,000 checks at pre-seed and seed stages focusing on fintech, healthcare, SaaS and enterprise, women’s health, developer tools.
What does the fund look for in founders? Olubusi gives two answers. One, MAGIC wants to back founders with incentives to stick through the hard times of a company.
“At pre-seed and seed, you don’t have enough data about a company to make an investment decision. Your bet is entirely on the founder and the founding team. What we know, having done this several times, is that things get harder. So when we’re looking at the founder, we’re evaluating whether or not the founder has the grit to stick through the toughest times which are going to come up.”
The second indicator factors if the founder has the willingness, openness, the flexibility to learn and use that knowledge to succeed. Greenleaf believes these strategies have incredibly helped the firm fund exceptional companies and maintain good relationships with founders.
“Most of these founders don’t view us as their investors. They view us as fellow founders who are helping them along their journey. I think that also ties into them keeping it real with us and allows us to see them as people, and not just founders. That’s one of the things that have worked in our favor,” he said.
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In the distant past, there was a proverbial “digital divide” that bifurcated workers into those who knew how to use computers and those who didn’t.[1] Young Gen Xers and their later millennial companions grew up with Power Macs and Wintel boxes, and that experience made them native users on how to make these technologies do productive work. Older generations were going to be wiped out by younger workers who were more adaptable to the needs of the modern digital economy, upending our routine notion that professional experience equals value.
Of course, that was just a narrative. Facility with using computers was determined by the ability to turn it on and log in, a bar so low that it can be shocking to the modern reader to think that a “divide” existed at all. Software engineering, computer science and statistics remained quite unpopular compared to other academic programs, even in universities, let alone in primary through secondary schools. Most Gen Xers and millennials never learned to code, or frankly, even to make a pivot table or calculate basic statistical averages.
There’s a sociological change underway though, and it’s going to make the first divide look quaint in hindsight.
Over the past two or so years, we have seen the rise of a whole class of software that has been broadly (and quite inaccurately) dubbed “no-code platforms.” These tools are designed to make it much easier for users to harness the power of computing in their daily work. That could be everything from calculating the most successful digital ad campaigns given some sort of objective function, or perhaps integrating a computer vision library into a workflow that calculates the number of people entering or exiting a building.
The success and notoriety of these tools comes from the feeling that they grant superpowers to their users. Projects that once took a team of engineers some hours to build can now be stitched together in a couple of clicks through a user interface. That’s why young startups like Retool can raise at nearly a $1 billion valuation and Airtable at $2.6 billion, while others like Bildr, Shogun, Bubble, Stacker and dozens more are getting traction among users.
Of course, no-code tools often require code, or at least, the sort of deductive logic that is intrinsic to coding. You have to know how to design a pivot table, or understand what machine learning capability is and what it might be useful for. You have to think in terms of data, and about inputs, transformations and outputs.
The key here is that no-code tools aren’t successful just because they are easier to use — they are successful because they are connecting with a new generation that understands precisely the sort of logic required by these platforms to function. Today’s students don’t just see their computers and mobile devices as consumption screens and have the ability to turn them on. They are widely using them as tools of self-expression, research and analysis.
Take the popularity of platforms like Roblox and Minecraft. Easily derided as just a generation’s obsession with gaming, both platforms teach kids how to build entire worlds using their devices. Even better, as kids push the frontiers of the toolsets offered by these games, they are inspired to build their own tools. There has been a proliferation of guides and online communities to teach kids how to build their own games and plugins for these platforms (Lua has never been so popular).
These aren’t tiny changes; 150 million play Roblox games across 40 million user-created experiences, and the platform has nearly 350,000 developers. Minecraft for its part has more than 130 million active users. These are generation-defining experiences for young people today.
That excitement to harness computers is also showing up in educational data. Advanced Placement tests for computer science have grown from around 20,000 in 2010 to more than 70,000 this year according to the College Board, which administers the high school proficiency exams. That’s the largest increase among all of the organization’s dozens of tests. Meanwhile at top universities, computer science has emerged as the top or among the top majors, pulling in hundreds of new students per campus per year.
The specialized, almost arcane knowledge of data analysis and engineering is being widely democratized for this new generation, and that’s precisely where a new digital divide is emerging.
In business today, it’s not enough to just open a spreadsheet and make some casual observations anymore. Today’s new workers know how to dive into systems, pipe different programs together using no-code platforms and answer problems with much more comprehensive — and real-time — answers.
It’s honestly striking to see the difference. Whereas just a few years ago, a store manager might (and strong emphasis on might) put their sales data into Excel and then let it linger there for the occasional perusal, this new generation is prepared to connect multiple online tools to build an online storefront (through no-code tools like Shopify or Squarespace), calculate basic LTV scores using a no-code data platform and prioritize their best customers with marketing outreach through basic email delivery services. And it’s all reproducible, as it is in technology and code and not produced by hand.
There are two important points here. First is to note the degree of fluency these new workers have for these technologies, and just how many members of this generation seem prepared to use them. They just don’t have the fear to try new programs, and they know they can always use search engines to find answers to problems they are having.
Second, the productivity difference between basic computer literacy and a bit more advanced expertise is profound. Even basic but accurate data analysis on a business can raise performance substantially compared to gut instinct and expired spreadsheets.
This second digital divide is only going to get more intense. Consider students today in school, who are forced by circumstance to use digital technologies in order to get their education. How many more students are going to become even more capable of using these technologies? How much more adept are they going to be at remote work? While the current educational environment is a travesty and deeply unequal, the upshot is that ever more students are going to be forced to become deeply fluent in computers.[2]
Progress in many ways is about raising the bar. This generation is raising the bar on how data is used in the workplace, in business and in entrepreneurship. They are better than ever at bringing together various individual services and cohering them into effective experiences for their customers, readers and users. The No-Code Generation has the potential to finally fill that missing productivity gap in the global economy, making our lives better, while saving time for everyone.
[1] Probably worth pointing out that the other “digital divide” at the time was describing households that had internet access and households that did not. That’s a divide that unfortunately still plagues America and many other rich, industrialized countries.
[2] Important to note that access to computing is still an issue for many students and represents one of the most easily fixable inequalities today in America. Providing equal access to computing should be an absolute imperative.
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