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Founders are used to dealing with scarcity. There’s always a lack of funding, a lack of time, or a lack of qualified employees. One thing there is no shortage of, is advice. Advice on how to build the team, how to listen to customer feedback, how to achieve perfect product-market fit, how to scale, how to structure your equity, how to build a mindset resilient to failure. And so on. Those things are, no doubt, important to every young and growing enterprise. For tech startups, however, there are three challenges on which success hinges even more than on anything else. In fact, those challenges apply for startups in the search for seed capital, just as much as to a tech giant looking to ride the next technological wave.

I have embarked on a two-and-a-half-year journey to pinpoint what separates hyper-successful tech companies – both incumbents and newcomers – from those that fail. For my new book Tech Money I have interviewed countless leading experts and practitioners, from Silicon Valley to the White House, from finance professors to some of the most successful venture capitalists. I have also crunched numbers on technological cycles and the history of progress, analyzing thousands of databases, studies, market reports, and scientific papers. The outcome? While things like innovative power, operational excellence, and corporate culture are important, outsized success always falls to the companies that nail technological cycles. Concretely, this means three things: First, building your company on an emerging technology that will be heavily adopted and profitable. Second, hitting the right timing of capitalizing on that technology (the trickiest). And third, getting not just the product, but the packaging right.

The absolute foundation: A successful technology

Great companies are defined by great products. But what is the difference between Ford’s Model T and Sega’s Dreamcast console? Between the iPhone and Google Glass? Hyper-successful products share many characteristics, but ultimately what makes them stand out is that they ride on the back of extremely successful technologies like the conveyor belt (Model T) or the smartphone (iPhone). The Sega Dreamcast, on the other hand, flopped after two years because it had ignored the nascent DVD-standard. Google Glass failed to convince customers they should wear displays in front of their eyes because wearables failed in their attempt to dethrone smartphones. So, the primary question is not which company can provide a great product, but which companies are banking on the winning technology of tomorrow.

Let me illustrate that with a personal example. Due to my background in blockchain and digital assets, I have been working with many Web3 startups in the past. Many had brilliant developers and savvy founders. Some of them had really solid technological fundamentals (you would be surprised how many even established blockchain companies don’t). Some displayed an insane speed at adding corporate customers. They were textbook examples of blitzscalers once Mark Zuckerberg pivoted to the metaverse idea. But when the metaverse hype collapsed, all of them were doomed. Some of those companies are still around, a few are even profitable, but none of them is of any relevance on a larger scale. So, how can you tell a successful technology? Adoption. Adoption. Adoption. And I am not just referring to users, but people (or enterprises) actually paying for it. This is the foundation. As an investor, I prefer to have a real need for a technology that’s unaffordable, rather than the other way around. If the incentive for usage is high enough, a way will be found to lower the costs. Costs to launch a spacecraft fell by more than 99% within 25 years. The cost of editing a genome sequence fell from around $100 million in 2002 to under $1,000 within just 18 years and is now pushing the $100 boundary.

The trickiest part: Timing

But how to make sure that you are not building your strategy on a tech that is 20 years away from its prime time? Even for investors, catching a technology at the sweet spot (i.e. the beginning of the steep growth curve) is a science in itself. For founders and managers, it is multiple times harder. The latter have to start working on a tech years before they see how and when adoption will play out. That doesn’t mean, however, that they have to build their business solely on pure hope. There are a number of early trend indicators that give a two-, sometimes three-year advantage over those waiting for the tipping point. Many VCs and innovators obviously watch funding trends, but in my research, I found that there are more subtle signs: Activity in terms of research papers, patent applications, talent trends, and Google search uptick. You have to know how to interpret these indicators, but even then, this kind of monitoring is not an exact science. None of the early trend indicators is. And none of those indicators should be the sole basis of an investment decision. Sometimes those metrics might even contradict each other. However, if you see multiple of them pointing in the same direction, something is going on.

Hitting that right time window means you are the first one to pick the low-hanging fruits in a market nobody saw coming. One of the conversations I had that still resonates with me was the one with Alex Lazarow, the Managing Partner Fluent Ventures. He summed it up perfectly:

“You have a hint that the timing might be right, when there is a big shift in the technology. For instance, it was really hard to have a digital bank without a mobile phone. And then all of a sudden, the mobile phone actually changed the economics of a branch bank and allowed you to do a lot of things like identity verification or fraud detection without the branch. We wouldn’t have neobank unicorns without it. At the same time, it is not so exciting today any more to build a neobank, because we have so many of them.”

In other words: You have to connect the dots before others do, but make sure that the dots are really there. That is why those early trend indicators are so critical.

The top of the pyramid: Packaging

But even if you nail the timing, it will be to no avail if the packaging of the product or service is not ideal. ChatGPT was certainly not the first powerful AI tool available to the public. Midjourney, an extremely potent software for image generation, was far earlier in the market. Up to this day Midjourney has one of the most robust models to create visuals. In fact, Midjourney even had quite some name recognition among graphic designers. The trouble with those earlier applications was that they lacked accessibility and user-friendliness. ChatGPT’s user interface is as simple as the Google search bar. You just type in your prompt or your question. It’s free. It’s versatile. If you wanted to create a Midjourney picture, on the other hand, you first had to sign up for Discord and then…Never mind. By now you have lost almost everybody.

The iPhone was truly visionary and perfectly timed, but it would have never become the most successful product in history if it weren’t for its design and branding, it’s stability, Apple’s golden handcuff approach, and a well-balanced double-sided platform strategy. Packaging won’t matter if you don’t get the technology and the timing right, but if you do, packaging makes the difference between performing solidly or exceptionally.

Igor Pejic is an author, keynote speaker, and banker. His latest book Tech Money uncovers the new rules of investing in the technology age and teaches investors and executives how to benefit from them. His previous title Blockchain Babel won the Independent Press Award and was profiled as a Financial Times book of the month. He was also a finalist in the Bracken Bower Prize awarded by McKinsey and the Financial Times. Pejic publishes the industry newsletter The New Frontier, and his articles and interviews regularly appear in media such as the New York Times, the American Banker, and Bloomberg. Pejic has held different management positions in banking and tech, currently at one of the largest banking groups in Europe.

Most startup prizes celebrate those that have reached the highest peaks.

At Fluent, we believe the best ideas come from anywhere, and scale everywhere. We would like to celebrate those that have not only reached massive heights but also inspired others to scale the same mountain.

William Gibson once said: “The future is already here. It’s just not evenly distributed”.

We are excited to announce the Fluent Geo Alpha Prize.

The Fluent Geo Alpha Prize is an annual recognition created by Fluent Ventures to honor the companies that have not only become globally relevant technology companies, but have gone on to inspire replication across geographies.

These companies become blueprints: once proven in one market, they catalyze locally adapted versions around the world. The prize formalizes a pattern that has quietly defined the last decade of global technology: geographic alpha.

What the Prize Recognizes

The Geo Alpha Prize recognizes companies that originated or proved a new category or operating model in their local context, reached durable scale, and demonstrated global relevance through independent replication in other regions.

These companies are distinguished not only by outcome, but by path: they succeeded despite distinct regulatory, infrastructural, or consumer constraints, and in doing so, created a blueprint others could adapt.

In many cases, their impact extends beyond the company itself: contributing to second-order ecosystem formation, including talent spin-outs and follow-on founders.

These are not simply successful companies. They are category progenitors.

Eligibility Criteria

To be eligible for nomination, a company must:

• Have achieved a valuation of $1B+ in the last three years (and/or a successful exit, IPO or acquisition, that demonstrates category leadership and durable scale)

• Demonstrate evidence of international replication by independent companies.

• Have founders willing to engage publicly in reflective conversation about the journey.

Non-technology companies, or companies that scaled primarily through subsidiaries or centralized global roll-outs are not eligible.

Nominations

Nominations are open globally and may be submitted by founders, investors, operators, academics, or ecosystem leaders. Self-nominations are permitted but discouraged.

Each nomination must include a short written rationale focused on replication impact rather than absolute company size.

Nominations are open through April 20th, 2026. The inaugural winner will be announced at South Summit 2026, at la Nave, Madrid (June 3–5). The winner will be invited to join for a fireside chat keynote with Alex.

—> Nominations can be submitted here.

Winner Selection Process

Winners are selected by an independent committee convened by Fluent Ventures. The committee is designed to ensure credibility and neutrality and includes:

• Liz Fleming, Chief Ecosystem Officer at South Summit

• Mehran Gul, Author, The New Geography Of Innovation

• Allen Taylor, Managing Partner of Endeavor Catalyst

"Geographic replication is one of the most underappreciated dynamics in global technology," said Mehran Gul, author of The New Geography of Innovation. "The companies that originate these models do more than build successful businesses, they write a playbook the rest of the world reads. The Geo Alpha Prize is long overdue."

The Prize

The Geo Alpha Prize is intentionally not primarily financial. Instead, it offers status, signal, and platform:

• Formal recognition as a Geo Alpha Originator.

• A commissioned Geo Alpha case study published by Fluent Ventures. A featured long-form conversation (podcast, fireside, or keynote) and inclusion in the sequel of Out-Innovate if/when published.

• An invitation for a fireside keynote at South Summit in Madrid this summer

Illustrative Geo Alpha Winners

Example 1: Amazon (E-commerce)

What they did: Amazon pioneered the modern e-commerce and logistics stack, proving that large-scale online retail could work across an enormous SKU base while maintaining fast delivery, inventory discipline, and customer trust.

Replication impact: Inspired independent regional leaders including MercadoLibre (LatAm), Flipkart (India), and Shopee (SEA), each of which became dominant local platforms rather than extensions of a global parent.

Example 2: Uber (Mobility)

What they did: Uber defined the modern ride-hailing category by combining mobile GPS, dynamic pricing, and flexible labor supply into a seamless consumer experience.

Replication impact: Uber proved the category, but local operators with deeper regulatory alignment and localized execution were often better positioned to win in specific regions. Independent regional champions such as Didi (China), Grab (SEA), and Careem (MENA) emerged.

Example 3: Tinkoff (Digital Banking)

What they did: Tinkoff pioneered a fully branchless, technology-first consumer banking model in Russia, proving that a digital-only bank could reach national scale, profitability, and strong customer trust without physical infrastructure.

Replication impact: Tinkoff demonstrated an early, repeatable blueprint for mobile-first banking that later emerged independently across regions, influencing the rise of digital banks such as Chime, Revolut, Nubank, etc, each adapting the core model to local regulatory and market conditions.

Example 4: Ant Financial / Alipay (Fintech Super-App)

What they did: Ant Financial built the world’s largest fintech ecosystem by embedding payments, lending, and financial services into everyday consumer workflows.

Replication impact: Inspired local fintech super-apps such as Paytm (India), Yape (Peru), Grab Financial (SEA), and others, each shaped by local regulation and consumer behavior.

Geo Alpha Prize Evaluation Rubric

Each nominee is evaluated across :

1. 1. Category Origination (40%)

   1. Did the company meaningfully define or prove a new category or operating model?

   2. Was this model non-obvious or unproven prior to their success?

2. Replication Signal (30%)

   1. Has the company inspired at least one independent, regionally adapted replication?

   2. Did replication occur despite different market conditions (regulation, infra, consumer behavior)?

3. Outcome Quality (20%)

   1. Has the company reached a durable scale (unicorn+ valuation, public listing, or major exit)?

   2. Is the business considered a reference point in its category?

4. Ecosystem Impact (10%)

   1. Has the company produced second-order effects (talent spin-outs, follow-on founders, ecosystem formation)

About Fluent Ventures

Fluent Ventures is a global early-stage venture capital firm founded by Alex Lazarow, investor and author of Out-Innovate (Harvard Business Press). Fluent backs founders who localize successful business models in high-potential regions across fintech, health, and commerce. The firm's portfolio spans North America, Latin America, the Middle East, Africa, Europe, and Asia. Fluent is backed by more than 75 unicorn founders, operators, and global investors.

Two MBA students asked me separately for career advice. I was on a plane, so wrote them a long answer. I figured I’d share my thoughts here.

Venture capital is one of the best jobs in the world. It offers a rare combination: a high-level view into where technology and society are heading, paired with very practical exposure to how companies are built. You get to work with founders who are unusually ambitious, opinionated, and thoughtful about the future. For many people, including me, it is a dream job.

But it is not a career in the traditional sense.

Unlike consulting, banking, or operating roles, venture has no standardized progression. Getting an associate role does not imply a path to partner. Most venture firms are small and bespoke. They are optimized for investing, not for training or long-term career development. In fact, venture is often a poor place to learn the fundamentals of working. Judgment compounds slowly, feedback arrives years later, and it is hard to disentangle luck from skill. I’m almost 15 years into this and still trying to figure out if I’m good, hopefully great, or perhaps neither.

At the same time, venture can be an excellent launching point even if it does not work out long term. Many investors eventually become founders or operators, and the reverse is also common. But because there are so few seats, and because most firms are not designed to develop talent systematically, the opportunity cost of entering too early can be high.

This is why I tend to frame the question less as “Should I do venture or operating?” and more as “How do I transform myself into a node for talent, with durable judgment and credibility?”

There are several proven paths into venture. Some come through a professional apprenticeship: investment banking, private equity, hedge funds, or consulting, followed by an associate role. This path works best early, when firms are hiring junior talent. Others arrive through operating experience, by founding a company or holding a senior role at a fast-growing startup where they develop real responsibility and credibility with founders. This is harder to pull off but often comes in at higher levels. A third path, increasingly common, is to start investing independently as an angel or through small syndicates, and to build a track record over time. None of these paths is inherently superior.

For someone in an MBA program, especially one with unusually high founder density, the more important question is how to test the work now rather than optimizing abstractly for a future role.

I usually suggest a simple set of experiments.

• Develop a point of view. Effective investors are not generalists in the vague sense. They have a perspective on what is investable and why. When you meet investors, try to teach them something they do not already know, whether about a market, a geography, or a pattern they have not yet seen.

• Start building relationships with funds you admire early. Funds are not hiring all the time. They hire when they have a need – either someone leaves or they raise a new fund and need to grow the team. Research which firms are in fundraising mode and focus your immediate application energy there. But don’t let this stop you from acting now on relationships. When it is time, you want them to call you first. Stay on it.

• Build deal flow anchored in real relationships with founders. Many of the strongest companies of the last decade emerged from MBA cohorts, not because of the credential, but because of proximity, trust, and shared context.

• Finally, try the work directly. Start investing, even in small amounts. Writing a first check is less about capital and more about learning, signaling intent, and building reference points. Platforms like AngelList let you build portfolios for fractions than it once cost. The goal is to build a track record and a unique perspective into the technology markets. Fellowships, part-time roles, or summer stints at venture firms are often the fastest way to understand whether the day-to-day reality matches the idea of the job.

Seek skills and experiences that compound regardless of whether you enter venture now or in the future. For most people, the best strategy is optionality: building skills and credibility that matter whether or not venture works out. The things that will make you a great young investor are the same as what might make you excellent in other professions – domain expertise, a unique network, strong work ethic, self-starting hustle, etc. Ironically, that approach is also what tends to make someone more attractive to venture firms in the first place.

I’m just back from Dubai for the World Government Summit. The event, one of the largest apolitical gatherings in the world, offers a rare vantage point on the global innovation economy. It sits at the intersection of policymakers, sovereign investors, founders, and venture capitalists, groups that often talk past one another, but increasingly shape one another’s outcomes.

This year’s conversations were animated by a shared unease – geopolitical tensions and major technological innovations were certainly at the forefront of everyone’s minds.

I spoke on three panels.

• Innovation and cross-border collaboration in Latin America, organized by Makhtar Diop and his team from IFC

• Geopolitical tensions and its impact on startups, moderated by Bloomberg, fireside chat with me and serial entrepreneur Div Turakhia

• Emerging economies roundtable, with the Presidents, Prime Ministers and leaders of a few African countries, as well as private sector leaders (including me on behalf of Fluent Ventures)

Across many of the panels, the underlying question was not whether innovation would continue despite geopolitical headwinds. It clearly will. The harder question is where it will happen, who will lead it, and under what constraints or opportunities.

Several themes stood out from these conversations.

Geopolitics and Startup Risk: A Matter of Timing

One of the most persistent misunderstandings in discussions about geopolitics and startups is the assumption that geopolitical risk is evenly distributed across a company’s life cycle. It is not.

At the earliest stages, startups are not companies at all. As I deep dive in Out-Innovate, startups are projects in search of a business model. Their primary risks are intensely human and operational. Do the founders stay aligned? Do they find a product that customers actually want? Do they discover a viable distribution channel before capital or morale runs out?

For a pre-seed or seed-stage company, tariffs, sanctions, and trade policy are usually second-order concerns at best (for the average technology company). A founding team falling apart or failing to reach product–market fit will end the journey long before geopolitics has a chance to intervene. Startups that are succeeding can usually build workarounds on key barriers.

That changes as companies scale. At later stages, geopolitics becomes material. Supply chains harden. Regulatory exposure grows. Exit environments narrow or widen depending on cross-border capital flows, public market sentiment, and strategic acquirer behavior. IPO windows are political as much as financial. Margin of error en route to exits narrow. M&A increasingly reflects national priorities, not just corporate ones.

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Tariffs and Trade Friction as Competitive Advantages

Trade tensions are typically framed as a tax on innovation. In practice, it is not black and white for all startups (as covered about our panel by Gulf News).

As global barriers rise, the advantage shifts toward local and regional startups. Regulatory complexity, tariffs, and industrial policy make it harder for global incumbents to operate everywhere with a single product and a single playbook. Local startups, by contrast, are born compliant. They understand domestic customers, pricing sensitivities, and institutional realities from day one.

This is a core thesis for Fluent Ventures, the VC fund I founded. We believe the best ideas are global, but the winners will be local. Tariffs, trade barriers and geopolitical fragmentation are part of this story. Rather than killing innovation, friction reshapes it.

Artificial intelligence accelerates this shift. AI dramatically lowers the cost of localization, from language and customer support to compliance workflows and product customization. What once required a global organization can now be achieved by a focused regional team with the right tools.

The result is not deglobalization, but regionalization. Instead of one winner taking all markets, proven models are replicated market by market. The future belongs less to companies that scale everywhere at once, and more to those that scale deeply somewhere first.

Global ideas remain porous. Execution becomes local.

Venture Capital and the Rise of the Camel

The venture capital model is evolving, but so are the companies it funds.

On the capital side, a barbell structure is becoming more pronounced. At one end sit mega-funds with scale, platforms, and the ability to underwrite geopolitical complexity. At the other end are smaller, specialist, and deeply local firms whose advantage comes from context rather than capital. The middle is thinning.

At the same time, founders are adapting to a more complicated geopolitical context, with higher interest rates, and constrained exits. They are reaching profitability earlier, managing burn more carefully, and building businesses that can survive without constant infusions of capital.

These are not unicorns optimized for a frictionless global market. They are camels built for uneven terrain.

Latin America Comes Into Focus

One of the more striking roundtable discussions focused on Latin America. The region is both a collection of isolated markets, but also home to some of the largest innovators around the world. In 2021, the largest IPO in the world was Nubank from Latam. A few years later, one of the largest M&As was also from Brazil (Pismo). I was joined in Dubai by Fluent portfolio CEO, Adal Flores, who leads Kueski, one of the largest BNPL providers in emerging markets.

Equally important is the rise of South–South collaboration. Conversations highlighted growing ties between Latin America and the Middle East, spanning capital, operating expertise, and market access. At the event, the President of Panama who joined our panel discussed the rising ties with Europe and Mercosur.

For founders, this opens opportunities to build with a broader emerging-market playbook. For investors, it creates a different kind of arbitrage: not just valuation gaps, but insight gaps.

Economic Development: Technology Is Not Enough

A recurring theme in economic development discussions was both optimistic and sobering.

Innovation and AI are seen as platforms for leapfrogging lagging infrastructure. South–south exchange offers real promise. Capital, knowledge, and talent moving between emerging regions can accelerate development in ways that traditional aid or extractive investment models cannot.

This is where geo-alpha is most durable.

But technology alone is insufficient. Digital tools cannot substitute for physical infrastructure, functional institutions, or credible regulatory frameworks. In the absence of these, technology risks amplifying inequality rather than reducing it.

The message from the private sector across panels was consistent that this groundwork was critical to scaling startups.

Playing the New Game

The global innovation system is not breaking. It is reorganizing.

The conversations at the World Government Summit pointed toward a clear conclusion. The future will not be won by those who assume a return to frictionless globalization. It will belong to those who can operate fluently across borders, stages, and systems, building companies that are grounded where they operate, but informed by the world beyond them.

In an age of fracture, local context is the new advantage.

This piece was first published on my Forbes column here.

Capital One announced that it’s acquiring Brex, the corporate card and spend management platform founded in 2017 by Brazilian entrepreneurs Henrique Dubugras and Pedro Franceschi. The deal reportedly values Brex at just over $5 billion. This is both a massive fintech outcome, and a significant step down from its $12 billion peak valuation in 2022.

Brex was a pioneer of corporate cards & spend management for startups, serving companies that traditional banks wouldn’t touch, and grew to power expense management for thousands of businesses.

A lot of ink has been spilled on the economics of the deal, who made money - sounds like employees were made whole and early investors did great, while later stage investors get their money back, which is good for this vintage deal.

This is not the focus of this piece. We will dive into three non-obvious second order lessons from Brex’s acquisition.

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1. Geographic Arbitrage Creates Categories, Not Just Companies

When I wrote my debut book Out-Innovate with HBR in 2018-2019, I interviewed the Brex founders, who were incidentally incubated by Andre Street the cofounder of Stone, a Brazilian fintech unicorn.

What struck me at the time, was the role of cross-pollination of ideas across geographies. The Brazilian founders, Henrique Dubugras and Pedro Franceschi, saw an opening that American bankers missed because they understood how different customer segments required entirely different underwriting models.

They did not copy a model from one market to another, but brought an outsider’s perspective to identify gaps incumbents can’t see, and combined it with global experience.

Ultimately, Brazilians building a U.S. technology company, catalyzed a global category.

At Fluent, we see this pattern repeating across our portfolio. Certain models – particularly with local network effects in regulated industries (notably fintech) create waves around the world. Companies like Float (Canada), Pleo (Europe), Jeeves & Clara (Latam), Conta Simple and Kamino (Brazil), Razorpay (India) or Aspire (South East Asia). Note, I am an investor in Clara and Kamino.

There are many examples of successful immigrant founders bringing global know-how to win in the US.

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2. Finding The Right Wedge Is A Secret Weapon

Brex used corporate cards to get in the door, then cross-sold treasury, bill pay, and expense management. The card was the hook. Ultimately, the broader platform was the business.

Some have argued convincingly this was where most of the value accrued.

Ramp is executing a similar playbook and scaling rapidly with an ever-growing (and self-reinforcing) product suite. Corporate cards get them in the door, but from there, they can flock everything from bank accounts, treasury management, bill payment, etc.

Mercury is executing a similar playbook, albeit, starting from a different place. Mercury started as a modern SMB neobank, and now expanding to overlapping products.

Rippling would call this the compound start-up. Finding a solid wedge, and adding other products together – where the whole is greater than the sum of its parts.

The wedge often has most value when it is a hair-on-fire problem (getting credit cards for unbankable startups qualifies). Bonus points if they are high-frequency, painful transactions, that keep the customer coming back. Corporate cards have one additional bonus – they are high up the decision making stack (often the CEO sets it up at founding), and touches multiple departments over time.

3. Timing the Wave Matters More Than We Admit

Brex launched in 2017 when fintech funding was accelerating. They raised their big rounds in 2021-2022 at peak valuations during the boom. While they are exiting in 2026 as the market normalizes, they caught most of the fintech wave and the best of the covid days (amassing a low-cost war chest).

Founders who started 2-3 years later (2020-2021) are now facing a much harder path: higher customer acquisition costs, more skeptical investors, mature competitors, and a tighter funding environment. Building a comparable war chest at an early stage would be comparatively rare today.

Yes, Brex is selling past the fintech peak. But they benefited from it too. Ultimately, being early to a good wave can be just as valuable as riding the peak.

While it is interesting to debate whether this was a good deal and for whom, ultimately, Brex is a company that inspired a global category, during a defining fintech wave, and expanded to build a true platform. Congrats to the team!

Last week, we held our annual LP meeting at Fluent Ventures.

The event included presentations from many of our founders but also our LP base. We are backed by 50+ unicorn founders and exited founders, 20 VC funds or their GPs, and a number of fund of funds, banks, family offices and corporates.

Rather than keep these insights to ourselves, I wanted to share five trends reshaping how we think about venture investing in 2026.

1. What’s old is new: geographic alpha playing out

Fluent’s geographic alpha thesis is simple: replicate proven business models in new markets or industries to create a derisked portfolio – each bet should have best-in-class upside (since we are investing in proven derisked models) and, at the same time, lower downside (since we are investing in proven derisked models).

This year, I had a big IPO in my historical portfolio at a previous firm. Chime’s decacorn IPO is the poster child. They serve 9 million users by eliminating overdraft fees—disrupting a $30 billion annual revenue stream for legacy banks. I was also an investor in Neon (another leading Neobank and unicorn out of Brazil).

The interesting thing about this model is that it does not emanate from either of these markets. Rather, the first (few) came from Europe.

As a moment of reflection, markets change and theses can also be wrong. Originally, I was skeptical about investing in European neobanks – the market was well banked (making CAC theoretically higher), interchange was lower (unlike US which is 100x higher) and credit costs are manageable (making Capital One / Nubank strategy less appealing).

That challenge turned into an opportunity. Players like Revolut became particularly astute at cross-selling products and creating a self-reinforcing ecosystem; and moat.

The result – even more geographic alpha in this category.

2. AI Makes Replication Faster and Cheaper

The playbook of replicating a proven model into a new geography used to take 2-3 years and $10-20 million to execute. Just look at Uber replicators around the world – like Grab, Go-Jek, Ola, DiDi, etc., who were particularly profligate with their spending.

With AI, founders are testing multiple business lines simultaneously for a fraction of that cost and time. And ideas are much more portable than ever.

AI lowers the barrier to MVP development, reduces technical debt (debatably), and accelerates product-market fit discovery. What used to require a full engineering team can now be prototyped by a solo founder with the right AI tools. This fundamentally changes the risk profile of geographic arbitrage – you can test more markets, more models, and more variations before committing serious capital. We may see more compound startup ideas – combining multiple proven models at once.

I also believe we’ll see a new type of model emerge: Camel Seed Strappers. Bootstrapping used to be an option for founders to scale with less VC. AI theoretically allows companies to raise a single round – after having even built some product and demonstrated market need – and never raise again. The result are much less capital intensive and diluted cap tables. I expect this will change venture math for small firms.

3. AI Must Change How VCs Invest

If founders are moving faster, investors need to as well. We’ve rebuilt our deal sourcing around LLM-based search tools that compress market mapping from weeks to minutes. Ask “who are the top 10 companies in X category across Southeast Asia” and get a researched answer in real-time.

But it goes beyond sourcing. We’re using AI to:

• Incubate smarter: Running parallel experiments on business model variations before committing to a geography

• Add value differently: Connecting portfolio companies to lookalikes globally, identifying playbook transferability in minutes rather than months

• Decisioning: This is earlier for us, but we are playing around with feedback mechanisms independent of the team on our ideas, based on our stated preferences

• Create content: like an Easter Egg Fluent theme song we created (with Suno) in the intro – DM me if you want a listen.

The firms that treat AI as a nice-to-have research tool will get outpaced by those rebuilding their entire operating model around it.

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4. New Waves Are Emerging Beyond Fintech

Fintech was a once-in-a-decade wave that created massive value, and I had the opportunity to ride as a full-time investor since 2013. We’re now seeing similar dynamics in three new categories:

Healthcare: Tech-enabled primary care, roll-ups and employee ownership are becoming big drivers across multiple markets. We recently announced our investment in Jutro. We have a few more coming soon.

Professional services: We are looking to new models of applying AI into professional services. We have a few replication ideas in legal and compliance (and already incubated one company in the category).

Generational Business Transfers: Across sectors, baby boomer retirements are creating liquidity events. The playbook: buy with debt, improve with technology, scale through roll-ups. It works in healthcare, professional services, and skilled trades. We invested in Baton and Iconic for example, which replicates some lessons from M&A Research Institute in Japan.

Each has the same characteristics that made fintech attractive: operational complexity, regulatory moats, local network effects, and structural inefficiencies ripe for disruption.

5. The Exit Environment Is Globalizing

The Midas List tells the story. In 2013 when I started investing only 4 cities had created a unicorn. 100% of the Midas list made it from investing in Silicon Valley.

Today, 30% of Midas members live and invest outside Silicon Valley. Even in the U.S. the return outcomes are more dispersed. One thing is clear; venture returns are no longer concentrated in Silicon Valley.

Furthermore, the notable deals highlighted — one per investor using Forbes’ methodology — are also more global than ever, including Coupang (South Korea), Flipkart (India) and UiPath (originally from Romania). In fact, the company mentioned more than any other this year — ahead of OpenAI, Coinbase, DoorDash and other Silicon Valley all-stars — is Brazil’s Nubank, responsible for landing six different investors on this year’s list.

Liquidity paths are diversifying too. Regional exchanges like Saudi Arabia’s Tadul are offering viable exit routes for local champions. Multiples are sometimes even higher abroad than they are domestically.

M&A appetite is growing for companies with proven models and regional dominance. Brex just got acquired by Capital One for $5b – a model we’ve backed elsewhere.

And secondaries are becoming a legitimate option earlier in the lifecycle.

This piece was first published on my Forbes column here.

Venture capitalists seem to always relish a debate. What’s better: Solo GPs versus partnerships? Small funds versus platforms? Large portfolios versus concentrated bets? Specialists versus generalists?

These questions resurface regularly on X — particularly when capital tightens and outcomes diverge.

A few weeks ago, the Wall Street Journal posed a familiar version of this question: are solo general partners uniquely positioned to land explosive investments because they can move without the friction of consensus-driven partnerships?

My take, which I shared in the piece, is that it conflates a few dimensions. Partner count by itself is not the sole driver. What matters more is where an investor’s edge comes from, and whether that edge compounds over time.

The venture industry is evolving. I believe the next generation of outperformers - solo or otherwise - will not be defined by partner count, but how they deliberately play the game. Solo GPs have a few structural advantages for the new rules of the game.

Therefore, the question for today’s post: if there is a new game, then how does a VC win, and what strategies are most likely to be successful?

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What Does It Mean to “Win” in Venture?

At its core, venture capital has a single scoreboard: distributed returns back to LPs (DPI). Everything else is a proxy, a leading indicator, or just noise.

The problem is that in venture capital, timelines are long, and getting to DPI can take a decade or more. Therefore, figuring out who is truly outperforming – over multiple vintages – is a challenging task in the short or medium term.

That’s why many performance metrics are leading indicators. They don’t correlate to DPI perfectly, and sometimes conflate success with noise. For example:

1. Fast mark-ups, which show genuine fundraising momentum, which is often associated with underlying revenue traction. But more rounds also means more dilution, and thus return compression.

2. Winning access or allocation into rounds is a proxy for competitive position in the moment. But if funds are winning access to hot rounds, the upside is often at least partially baked in with higher prices, which lowers the potential for multiples (just look at your favorite 100x revenue AI deal!)

3. Reputation and brand, which shape future access and founder perception. But if the reputation is relevant to the wrong audience, then it won’t drive returns, and worse divert fund resources and attention.

Return proxies matter, but they are not the same thing as performance. Many venture debates are really arguments about such proxies, not outcomes.

Four Strategies That Drive Venture Outperformance

Across market cycles, geographies, and fund sizes, my and Fluent Ventures’ (the firm I founded) view is that only four strategies consistently explain venture outcomes. They are slightly orthogonal. Though in some cases they can be combined.

1. Unique Insight: The Foundational Edge

A durable source of venture alpha is insight—the ability to see something before others do, or to understand it more deeply.

This can come from industry or thematic focus, sector specialization, geographic immersion, or lived operating experience. It shows up as pattern recognition, speed of conviction, and comfort acting before consensus forms. “Non-consensus but right” is not a slogan; it is the economic engine of power-law returns. These VCs offer their LPs differentiated and often uncorrelated returns to the market.

2. Unique Access: A Supporting, Not Primary, Advantage

Access plays an important role in venture and can come from founder networks, LP ecosystems, proprietary data, corporate partnerships, or embedded positions in specific markets.

Only 1% of companies ultimately become unicorns, and the best investors bat better on average.

Being in the room for as many of the 1% of companies as possible is critical.

Of course, and critically, access alone doesn’t drive returns. Selection and winning matter almost as much and in some cases even more.

A useful question for LPs and founders alike is not “who has access?” but “access to what?” Access to a narrow set of hot rounds is very different from access to broad, underexplored opportunity sets—particularly outside traditional innovation hubs.

3. Value-Add and Platform Capability

Over the past decade, value-add has evolved from a marketing claim into a genuine competitive dimension.

Talent networks, go-to-market support, executive recruiting, corporate development, and commercialization partnerships now shape how founders choose investors. Large platforms and some specialized firms have built impressive operating capabilities that can bend a portfolio’s company into a powerlaw.

Corporates and non traditional investors have an edge here too, by driving commercial success, increasing the company’s value (and presumably earning access).

4. Reputation (often tied to larger, storied, multi-stage firms)

Venture capital is one of the few financial products with returns persistence. One reason is that brand and reputation remain powerful forces in venture capital, begetting future access (and thus insights) into the changing technology landscape.

Yet reputation has a hidden cost. As firms scale and defend franchise value, strategies often migrate toward lower volatility and higher predictability. Or for sector specialists, get stuck into a strategy that used to work, but where the alpha has disappeared.

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Where Solo GPs Fit, and Where They Don’t

Viewed through this lens, solo GPs are neither a panacea nor a liability.

The best solo GPs tend to excel at #1 and #2. Some bring deep, market-specific understanding. Others emerge from highly networked ecosystems and can tap into them quickly. Their defining advantage is decisiveness: the ability to act with conviction before a consensus forms.

And in a power-law game, this gives them the chance to find power-law returns.

From an LP perspective, solo GPs offer a different proposition: clarity. When an LP invests in a standard VC fund, they are picking the team. But, solo GPs allow LPs to create their own fantasy football team – choosing a few stars and building their own “dream” portfolio construction.

Imagine every VC portfolio didn’t have to be the Bulls vs. the Raptors. You could just build your own Team USA of superstars.

There’s always a but

Having worked within larger franchises for a decade before launching a solo-GP firm, there are structural advantages to larger firms, particularly around #3 & #4. Solo-GPs are just not set-up to offer the same level of platform benefits, and like any new firm, require a long time to build reputation. And of course, larger franchises can excel at #1 & #2 as well.

Another key nuance in my view, is that access alone is not enough. This is only proxy VC performance. The best solo GPs must have unique insights, to ultimately drive DPI performance that exceeds investing in a more generalist standard firm.

Strategy Over Structure

There clearly is not a single winning model. The venture firms that succeed over the next decade will not all look alike. But they will share one trait: a clear understanding of why they exist, where their edge comes from, and how that edge compounds.

This post was previously published on my Forbes column.

Happy New Year!

It is prediction season again. Most forecasts focus on what will grow fastest or attract the most capital. This one takes a different approach.

These are predictions about where I think expectations are wrong. Looking ahead to 2026, here are six uncomfortable shifts I believe will matter most.

1. Cross-border expansion may slow, but cross-border replication will accelerate

AI has created the illusion that international expansion has become easier. Yes, you can easily translate your app into Mongolian.

In practice, the opposite is true.

The era of “launch everywhere” is facing more headwinds. For most business models: regulatory friction, capital discipline, and operational complexity are not bugs; they are features.

For AI companies in particular, durable moats will come not speed to launch in new markets, but ultimately from unique data or unique distribution. Thin application layers without either a unique distribution advantage (e.g. local partnerships, trustworthy brand etc) or data (e.g. on the local economics, relationships etc) will struggle to defend themselves as larger foundational models move up the stack.

Conversely, replication of proven business models will accelerate dramatically. There are now hundreds of cities with unicorn founders and effectively no barriers to launching new companies. If Uber took a decade to be replicated globally, AI-enabled business models may follow the same arc in three years.

A critical skill for both founders and investors will be saying no to shiny international expansion. Depth in a home market will often be greater than breadth across markets. Context, local execution, and restraint will become real sources of competitive advantage.

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2. AI will enable “camel seed-strapping” and distort the early-stage market

AI is allowing small teams to get much farther with much less capital. Many companies will reach real revenue, real customers, and operational maturity before they ever raise a traditional Seed or Series A. I wrote about the “camel seed strapping” phenomenon recently.

Early-stage benchmarks will become harder to interpret. Later-stage investors will encounter companies that look “too early” culturally but “too late” operationally. Some will already be profitable. Others will be highly capital-efficient but mismatched to traditional venture expectations.

As a result, two phenomenon may take place in tandem: early-stage businesses will skip seed funding, but also many good businesses may never need to raise a Series B. Durability and capital efficiency may change the venture business model.

3. AI churn is coming, and those with valuation discipline will be rewarded

Yes, a small number of AI companies will continue to reach for the stratosphere.

But for many, pilot revenue won’t convert as fast as expected to long-term contracts. Switching costs may be lower than expected as competitors emerge. Foundational models will continue to converge in functionality. Customers will start to reassess AI investments and real ROI post experimentation

Many business models will work. But in the short-term, churn may increase. The companies may need more time to mature the product or the sales cycle to create enduring customer relationships.

At the next raise, if the story is not perfect, a previous round at 100x revenue may come back to bite startups with more challenging round dynamics.

In that environment, companies that managed valuation will be better positioned. Those that reach profitability and raise on their own terms will have the most leverage.

4. Venture returns and recognition are continuing to shift outside Silicon Valley

In 2026, the Midas List will continue going global. Returns, talent density, and category-defining companies are emerging outside traditional tech hubs.

What continues to lag is recognition. League tables will adjust slowly. Geography is no longer a proxy for quality, and in many cases it has become a source of edge. The next generation of enduring venture firms will be built around where insight is deepest, not where consensus is loudest.

5. M&A is returning

M&A is coming back as a deliberate strategic tool.

Companies will play offense and defense at the same time: acquiring distribution rather than users, buying teams instead of tools, and consolidating fragmented categories before pricing power erodes.

We may have seen the first such deal with Nvidia’s $20 billion dollar ‘licensing deal’ of Groq.

I expect a diverse range of active acquirers. Foundational models looking to grow vertical capabilities. Scaled technology companies looking to grow capabilities. And incumbents fearful of being left behind.

For founders, M&A may increasingly be a feature of exit strategy, and certainly not an admission of defeat.

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6. The line between tech and services is blurring

The software-only ideal for startups will become more blurry.

We already see this shift in practice: forward-deployed engineers at companies like Palantir and OpenAI.

One theme I wrote about recently are AI roll-ups, which merge an M&A playbook (per above) with a technology platform. AI-enabled roll-ups borrowing from private equity playbooks, and vertical software companies embedding operations to deliver outcomes rather than tools. Some successful models are already emerging: Teamshares, a company that combines SMB M&A with employee ownership and various fintech products, will be going public via SPAC next year.

Elsewhere, some valuable AI businesses will look in part service-enabled at first. The winners will be those that use services as a wedge, not a crutch, on the path to scalable advantage.

As capital, talent, and technology rebalance, the biggest opportunities will belong to founders and investors willing to trade noise for nuance, and speed for depth. That’s where the 99% lives.

Happy New Year.

For decades, roll-ups sat squarely in the domain of private equity and search funds. These strategies depended on predictable cash flows, margin expansion, and the disciplined application of an operating playbook—none of which fit neatly into the traditional venture toolbox. But a quiet shift is underway. AI is collapsing the cost structure of integration and making once-specialized operational capabilities accessible to lighter, faster teams.

This change opens a narrow—but meaningful—window for something new: venture-style roll-ups. The model isn’t for everyone. Most attempts will struggle under the weight of integration complexity and shifting incentives – and won’t turn out to be venture sized outcomes. Yet for the 1% that get the structure, timing, and strategy right, the return profile can be extraordinary.

At Fluent Ventures, we’re excited to announce our recent investment in Jutro Medical, an AI-first primary care operator in Europe applying this model in one of the most operationally complex sectors. Founded in 2020, Jutro operates 20 clinics across Poland, serves over 120,000 patients, and has built its own end-to-end EHR and AI layer to standardize and automate clinical operations at scale. They just announced a EUR36m round led by Warsaw Equity Group, alongside local VC funds like Inovo and Kaya. Read about the Series A here.

In this piece, we wanted to share more about our thesis about this category, and our thinking behind the investment. At the core, an AI roll-up requires the possibility for meaningful margin expansion and plentiful affordable targets.

Margin Improvement: The Irreducible Starting Point

Every successful AI roll-up begins with margin improvement driven by a technology platform.

If this lever isn’t available, it isn’t a venture roll-up at all—it’s a standard PE or search fund strategy. Historically, deploying margin-expansion playbooks required sizable teams, heavy operational investment, and the patience that private equity is built to deliver.

AI is now rewriting this constraint. Workflow automation can replace large portions of back-office labor. Shared infrastructure reduces SG&A. Integration that once required armies of operators can be achieved with lean teams. The cost barrier that kept sophisticated operational playbooks out of the hands of venture investors is eroding.

Without this shift, the rest of the model doesn’t work.

In the case of Jutro, over the last year they have completed nine acquisitions. Jutro has automated large portions of intake, documentation, and administrative workflows using AI agents embedded directly into its proprietary EHR. This allows doctors to focus on clinical decisions while materially reducing per-visit operational cost. As Jan Szumuda, of WEG explained: ““Jutro Medical nearly quadrupled its revenue year over year while keeping EBITDA around break-even – a rare combination in this market.” Largely driven by this playbook.

A Market Full of Under-Optimized Assets

Across markets, particularly in tech-enabled services and digital infrastructure, there is a long tail of subscale businesses with recognizable brands, sticky customer relationships, and recurring revenue.

Many were built by entrepreneurs who were not building for venture-sized outcomes. These are traditional businesses. Their products are fine (and often excellent at small scale), but many parts of their business, like pricing and operations are under-optimized.

As a result, they tend to have low EBITDA margins and slow growth. And in today’s market, low valuations for traditional assets create additional leverage: buyers can acquire durable revenue for less than 1× ARR. These are often profitable businesses. Net of leverage, it may not even take much equity.

In Europe, for Jutro’s example, there are over 100,000 small clinics, many of which will go through generational transfer over the next decade. Primary care spend exceeds Eur200 billion annually in Europe (EUR 9 billion in Poland alone) yet, as Jutro explains it: “many clinics still rely on manual, paper-based processes that slow access to care and strain an already limited capacity”.

Acquisitions as a Growth Hack (Sometimes)

Traditionally, acquiring revenue was more expensive and more complex than building it. AI roll-ups are a tool to hack growth.

Buy revenue for less than low ARR multiples (ideally <1.5x)

In today’s environment, founders can purchase distribution, customers, and cash flow for a fraction of replacement cost. It is unprecedented in the venture cycle. Note that revenue is clearly not the end metric here, and ultimately it will be EBITDA or FCF. BUT, since the bet in AI roll-ups is a traditional business can be transformed into one with more software like gross margins, revenue multiples are easier comparable metric for the purposes of this blog.

Accelerate the growth arc

Each acquisition adds customers, cash flow, and data: the inputs that compound fastest when stitched together. If the acquirer has a growth playbook to scale faster all the better. What once required years of grinding for organic scale can now be achieved in a handful of transactions.

A strategic shortcut

Instead of expanding product breadth slowly, founders can assemble complementary offerings into a platform. Instead of fighting for distribution, they can buy it. Some of the best roll-up plays figure out ways to cross-pollinate customers across offerings, increasing LTV, and further improving unit economics.

Jutro is among the first operators in Europe to apply an AI-enabled roll-up strategy in healthcare. The company acquires small primary care practices and rapidly integrates them onto a unified platform, standardizing workflows, quality of care, and economics across locations. Jutro is accelerating its acquisition pace from 9 over the last year to 20 annually going forward.

The Four Levers of Venture-Scale Roll-Ups

When they work, venture roll-ups can drive three simultaneous levers of value creation, and sometimes a fourth.

1. Grow the Top Line

Venture teams bring product velocity, brand building, and go-to-market sophistication to subscale assets. Often targets have not built customer acquisition playbooks. Taking best in class startup approaches and applying it to the chosen category can unlock meaningful growth.

2. Automate the Back End

AI and shared systems standardize processes and reduce the operational burden. SG&A falls. Margins expand. Integration becomes repeatable. As noted above, this is what separates AI roll-ups from other platforms.

3. Cross-Sell and Integrate

Every acquired asset widens the platform to sell other products within the family or ecosystem.

4. Align incentives

Retaining key talent is often key in roll-ups. A fourth lever we are interested in at Fluent is employee ownership. Companies like Teamshares (announcing they will go public via SPAC next year) have demonstrated that many business owners are looking for alternatives to selling to traditional buyers, and empowering their employees. They often transact at similar or lower prices PE would offer. Employee ownership can be both a competitive advantage to the platforms for close rate and pricing.

Alex Barrett and Yoni Rechtman frame it nicely as an entirely different vector for impact.

Ultimately, combining some or all of these levers helps the flywheel begin: more acquisitions → more data and revenue → better automation → higher EBITDA. When executed well, these systems can expand EBITDA 3–5× within a few years on existing assets.

Where Venture Roll-Ups Fail

Most roll-ups fail, often for predictable reasons.

First, while ever deal looks to prove margin expansion, the goal posts of scaling the business with venture capital change over time (like they do in any preseed startup evolving to Series A). The first few deals are to show operational improvement. Over time, companies need to demonstrate repeatable deal making and integration processes.

Second, venture roll-ups work today in certain industries where competition is limited. If many competitors get funded in the same category (which we’re increasingly seeing in the U.S. in certain “hot” categories (looking at you HVAC), the alpha will disappear. This happened to the Amazon aggregators a few years ago.

Third, alignment with investors and the acquired teams need to be managed. This model requires patience, price discipline, and clear incentives across founders, investors, and operators. If investors push for aggressive valuations or misaligned off-ramps, the strategy can break. The employees of the acquisition need to be aligned – from the founders (if they stay on) to the full team. The best operators design against these risks from day one.

Why we backed Jutro?

At Fluent Ventures, we focus on geographic arbitrage: backing teams that execute proven global models in markets where structural conditions create an asymmetric advantage. Jutro fits this strategy precisely.

While primary care roll-ups in the U.S. have been constrained by high labor costs and high multiples, markets like Poland combine publicly funded healthcare, extreme practice fragmentation, and an aging physician base. This creates a compelling opportunity for consolidation — if integration costs can be dramatically reduced.

What differentiated Jutro was its order of operations. The team built a proprietary EHR and operational stack first, then layered AI directly into live clinical workflows before scaling acquisitions. This makes integration faster, quality more consistent, and margin expansion real from day one.

We also believe Europe is under-appreciated as a market for AI-enabled services businesses. Labor constraints are more acute, digitization lags the U.S., and competitive intensity remains low. Jutro operates at the intersection of these dynamics, applying an AI-first playbook in a region where the ROI on automation is structurally higher.

Why This Window Exists Now

The opportunity is not structural; it is temporal. Several forces have converged at once.

We have written about generational transfer. Millions of profitable, founder-run SMBs will change hands this decade. Many of these owners want scaled successors, not just financial buyers.

A roll-up strategy benefits from much lower transactional and integration costs with a shared customizable platform. What took PE firms a decade—process standardization, system integration, workflow redesign—can now be done in months.

There is also a honeypot of capital: There are numerous large VC funds who have allocated big portions of their funds (or raised dedicated vehicles) to fund the venture AI roll-up space. A new category of players will have access to play here

Conclusion: The Emerging Playbook

AI is redrawing the boundary between PE and venture. Roll-ups—previously too operationally heavy for venture timelines—now sit on the frontier of what is possible. The opportunity is narrow and demands precision. But the teams that get it right may define a new generation of venture-backed winners: durable, cash-generative platforms built through the marriage of technology, integration, and disciplined acquisition.

A new playbook is forming. And it is arriving just in time for the next era of innovation investing.

I’ve recently returned from Southeast Asia.

For more than a decade, the region has been framed as “the next frontier” for tech: a young, mobile-first population, rapid GDP growth, and a wave of high-profile unicorns. But on the ground last month—from Singapore to Jakarta—that story felt both true and more nuanced.

The froth has thinned. The Southeast Asia tech ecosystem is being re-examined. A new phase is taking hold: less hype, more discipline, and a deeper focus on building durable businesses.

From Blitzscaling to Category Building

The first wave of the region’s startup story was defined by blitzscaling. Grab, GoTo and Sea Group raised billions, capturing markets by outspending competitors and accelerating consumer adoption. That period created the region’s digital backbone: payments ubiquity, logistics networks, and a generation of consumers comfortable transacting online.

It also left behind fragile unit economics and uneven governance.

Quietly, a more durable revolution is underway. As Tech Collective argued founders are shifting toward vertical AI, industrial and logistics software, climate technology, and B2B infrastructure. Consumer scale alone no longer guarantees success. Startups are building the backbone of the digital economy and transformation.

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The talent base is maturing in parallel. Much like in other ecosystems, a new generation of spin-out founders are spinning out of leaders—alumni of Grab, Sea and Gojek—are building their own companies, bringing with them the playbooks of their alma matters.

This emerging flywheel what you see in more established hubs like Silicon Valley or Tel Aviv. A decade ago, Southeast Asia didn’t have this density. Today, it is starting to.

Enabling infrastructure has also caught up. Payments rails logistics APIs, cloud and data platforms, and embedded fintech stacks are now standard building blocks. In my book Out-Innovate (HBR Press), startups don’t need to build *as much* of the full stack as they needed to in the past. More enabling infrastructure means faster route to market. But that also means the bar for defensibility has risen: it is no longer enough to be first; one has to be deep.

A Funding Reset and a Return Reckoning

The capital cycle makes this maturation visible in the numbers. In the first half of 2025, Southeast Asia tech startups raised about US$2.0 billion, according to Tracxn’s semi-annual “SEA Tech – H1 2025” report. That total was down 24 percent from the US$2.6 billion raised in the second half of 2024.

In 2021, startups in SEA raised over $25b.

The strain is evident at the early stage. Founders are raising smaller rounds, extending runway, and being forced to prove unit economics much sooner. Perhaps the strain is highest at the growth stage.

For investors, the challenge is different but related: lofty valuations have not translated into cash. DPI—Distributions to Paid-In Capital—remains a weak spot for many Southeast Asia venture funds.

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When Trust Breaks

The funding reset has also exposed a second fault line: governance.

Two scandals—eFishery and Investree—have shaken confidence in the Southeast Asia startup ecosystem and put a spotlight on financial controls, board oversight and the role of venture investors when things go wrong.

eFishery, once Indonesia’s agritech flagship and a symbol of “impact at scale,” was valued above US$1 billion with investors including Temasek, SoftBank and Sequoia. By late 2024, it was under investigation for allegedly inflating revenues by roughly US$600 million in the first nine months of the year. Reports suggest the company claimed profits while actually posting losses. Green Queen, which mapped the saga in detail, described “the startup scandal that rocked Southeast Asia’s food-tech sector.” Integrity Indonesia reported evidence that eFishery kept two sets of books—one for management, another for investors—with divergences of up to 75 percent in reported sales.

Investree, an Indonesian SME lending and fintech platform, tells a different but rhyming story. Once held up as a model of digital credit innovation, it saw non-performing loans climb to around 16 percent—well above regulatory thresholds—amid allegations of executive misconduct and mismanagement. The Runway Ventures unpacked how a combination of governance lapses and risk controls led to a sharp breakdown in trust between lenders and the platform.

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The Builders Ahead

Yet the picture is not one of collapse. It is one of recalibration.

The funding pullback is painful for founders and investors alike, but it is also forcing the Southeast Asia startup ecosystem to look for firmer footing.

The next wave of companies will be leaner and deeper. Valuations are becoming more rational. Founders who can navigate constraint—operate as “camels” rather than unicorns—are easier to identify.

Tracxn notes that Singapore-based tech firms accounted for 92 percent of all tech funding in the region in H1 2025. That concentration underscores both strength and fragility: Singapore remains the dominant hub, but secondary centers like Jakarta, Ho Chi Minh City and Manila are quietly gaining momentum and deserve more attention from global capital.

For venture firms, return expectations are shifting too. The model that assumed endless multiple expansion and rapid exits will need to be replaced by funds designed for longer holding periods, creative liquidity (including secondaries and strategic M&A), and governance built in from day one.

Why This Is Still the Moment

All of this might seem like an argument for caution. In reality, it is an argument for discernment.

The next phase of Southeast Asia’s startup story will not be written by blitzscalers. It will be led by builders who understand constraint—who treat capital efficiency, integrity and depth as strategic edges rather than constraints to tolerate.

In Out-Innovate, I argued that ecosystems outside Silicon Valley succeed not by copying the Valley. It will be by executing over the long-term for more enduring opportunities.

Possibility in Southeast Asia will no longer come from flashes of hype. It will emerge from the bedrock beneath.

Something felt different at Money 2020 this year. Where previous shows focused on the modernization of the delivery of financial instruments (e.g. better lending, savings, insurance etc) by incumbents or startups – accompanied by the infrastructure to provide it - this year felt like bigger changes were afoot.

Coming off the back of many IPOs and M&A events this year – congrats to Chime (a historical portfolio company) and eToro - the mood was more optimistic. Yet, energy cooled on many of last year’s buzz words like “embedded finance”, “buy now pay later” and “climate finance”.

Looking back on the conference, I sensed energy and big opportunities for the future in a few places in particular:

1. AI is reinventing financial services, in some cases from first principles.

2. Stablecoins are becoming the Internet’s native settlement layer.

3. Regulation and technology are fusing into programmable trust.

1. AI Is Reinventing Financial Services

A few of the largest AI platforms made announcements in recent weeks, including of note, Anthropic with an excel plug-in with multiple financial skills. OpenAI announced integrations into multiple commercial and payments apps.

When I sat down with Mike Krieger, co-founder of Instagram and now Chief Product Officer of Anthropic, I asked him his views about the role of AI in financial services. “I think the companies that are going to grow the fastest are the ones building at the edge of model capabilities. They’re building in a way where every model release makes their product better—they’re letting the model do as much as it can, and it’s only going to get more capable and add more value.”

Anthropic’s approach to product development is built around that idea. Krieger described customers such as Parcha and Decagon who tore out custom code and rebuilt their workflows directly on Claude’s agent SDKs.

What struck me most was his pragmatism about interfaces. “At first I thought chat was too primitive,” he admitted. “Now I think it’s genius. You tell the system what you want, and everything underneath the chat box is what’s changing.” In Anthropic’s world, Claude isn’t a chatbot; it’s a computer—an agentic platform that learns and acts.

If Krieger is exploring AI as product, Sean Neville—best known as co-founder of Circle—is exploring AI as participant. His new venture, Catena Labs, is building what he calls a financial operating system for agents.

“In the future,” Neville told me, “the customers of our products will be AI agents. They’ll need to pay, get paid, borrow, lend—everything humans do.”

The concept of fintech for AI was an emerging theme. Catena, part of a growing class of startups, is developing the plumbing that would make that possible—agent identity, programmable trust, and what he half-jokingly calls Know Your Agent (KYA). “The immediate issue isn’t privacy or price,” he said. “It’s trust. Why would I trust an AI with my money?”

Investors see the same wave building.

Vivek Krishnamurthy of Commerce Ventures told me, “There’s no stopping the train when it comes to human-directed agentic commerce. Discovery and purchase through agentic platforms—ChatGPT, Perplexity—will be mainstream within twelve months.” But, he cautions, “We still have a long way to go on agent-to-agent payments. The ecosystem needs common protocols, identity, and liability standards. When we get there, we’ll disrupt the legacy card and processor value chain.”

Karim Gillani, founder of Luge Capital, added historical context: “The last decade of fintech was about unbundling and rebundling banking products. The next phase will reimagine how those products work fundamentally.”

AI as a building block, and as a customer, will likely be an important component. The next financial products won’t just empower humans with AI—they’ll empower machines to transact safely on our behalf.

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2. Stablecoins: From Curiosity to Global Rail

As I have written before, stablecoins have key advantages. “They’re fast, cheap, global, and always on,” stressed Gillani as well. “No other payment rail has all those characteristics.”

Yet, the industry is maturing. People don’t want Tether or USDC,” Neville told me. “They want dollars on their phone.” Circle’s founding thesis in 2013 was simple: put money on Internet rails. That vision has quietly materialized. Stablecoins now power payroll, cross-border remittances, and corporate treasury operations from Lagos to São Paulo. But the next battle is interoperability. “If I have $100 million, I don’t want 50 Amazon Coins and 10 USDC and 40 USDT,” Neville told me. “I need that complexity abstracted.” He predicts a payments-optimized blockchain—multi-stable, gas-free, and near-instant—that becomes the TCP/IP of money.

One challenge: today there are few barriers to entry. Jake Gibson of Better Tomorrow Ventures expects consolidation before that happens. “There are dozens of issuers and on-ramps being funded,” he said, “but payment rails always consolidate. In the end a few large networks will carry the volume.”

This consolidation has a geopolitical dimension. Neville pointed out that the U.S. and China are effectively racing to define the next settlement standard—private stablecoins versus state-issued CBDCs. “The Internet was built through private-sector innovation and public-sector policy,” he said. “That’s how we’ll build the next generation of money.”

Many of these trends are happening concurrently. Jay Ganatra of Infinity Ventures framed the convergence with AI: “AI and stablecoins are finally finding each other. Stablecoins were a solution in search of a problem—AI may be that problem.”

3. Regulation × Technology = Programmable Trust

The third current at Money 2020 was subtler but perhaps equally consequential over the long-term: the merger of compliance and code.

Some of the most interesting conversations weren’t companies delivering financial services, but rather ensuring compliance.

Vivek predicts: “AI lets fintechs sell banks Systems of Action instead of forcing them to replace their Systems of Record. That means they can finally capture SaaS and even payroll budgets—10× the market we’ve been selling into.”

This may not be the exclusive domain of fintech over time. Jeff Green, the President of Hatch Bank told me that he expects to see greater direct linkages between the most regulated institutions (like banks) and the capital providers and players in the ecosystem – which were previously abstracted by fintech platforms.

Where the Next Products Will Emerge

Looking forward, I expect some of the most interesting new fintech innovations not to be a new credit distribution or a embeddable savings tool.

AI will allow the creation of entirely new product categories (something I’m focused on professionally at Fluent Ventures), including by a number of new players. AI is making the diffusion of ideas much more rapidly to new markets, radically accelerating globalization of ideas.

Vivek sees this era as fintech’s second act. “The first 15 years were about digital distribution of existing solutions,” he told me. “The next 15 will fundamentally improve the core value proposition.”

Let’s hope so.

Everyone knows Samsung and Hyundai. But behind these global giants, a new wave of Korean companies is quietly reshaping fintech, travel, and biotech. Their stories carry lessons for entrepreneurs everywhere.

I am recently back from Korea, speaking at South Summit. Here are three startup stories that stand out.

Toss — Pods, Simplicity, and Building the Full Stack

A decade ago, sending $10 across banks in Korea required thirty-seven clicks and multiple passwords. Toss reduced it to a single swipe. They built the Venmo of the region as a first core product.

But simplicity became the wedge that pried open one of the most conservative financial systems in the world.

Today Toss is South Korea’s largest fintech, valued at over $7 billion, with more than 15 million monthly users. But the story isn’t just about scale. It’s about how the company organized itself to keep innovating.

Founder SG Lee didn’t have the linear journey of a Silicon Valley wunderkind. He started as a dentist, realized it wasn’t his path, and spent years in introspection. Before Toss, he launched eight failed startups. He’s clear-eyed about resilience: “The problem of being an entrepreneur is that a large part of success is determined by luck.”

Toss succeeded because it didn’t stop at payments. Korea’s financial ecosystem was riddled with gaps — only 9% of millennials traded online, and just 10% accessed unsecured loans digitally, versus over 50% in the US. As Lee put it: “We couldn’t understand why there was such a huge gap… That’s why Toss could not just be for money transfers.”

Instead of one product, Toss built the full stack: loans, insurance, investing, wealth management, credit scoring. More than forty services in all. That runs against the Valley’s conventional wisdom to “do one thing really well.” But in frontier markets, sometimes one thing isn’t enough.

The company also rethought how to organize for scale. Toss built internal “pods” — autonomous teams run like startups within the startup. Each pod operates like a founder-led company, with the freedom to experiment.

As Lee told me: “While it was hard to delegate, it was a leap of faith… the management team doesn’t have to control things. They just need to align and coordinate. Essentially, they are playing coach.”

That structure turned Toss from a payments app into Korea’s financial super-app. The broader lesson: start with radical simplicity, but design the organization for complexity.

Yanolja — From Motels to Global Travel SaaS

If Toss reinvented finance, Yanolja reinvented travel. Its origins are as improbable as they come. Founder Sujin Lee was orphaned, worked as a janitor in a motel, and eventually launched a website called “Motel Story” to review budget accommodation. Out of that unlikely beginning, he built Yanolja, now one of the world’s fastest-growing travel tech companies.

At first glance, Yanolja looks like a booking app. But the real engine is Yanolja Cloud, a cloud-based (SaaS) technology ecosystem that powers hotels and travel businesses around the world. In 2024, Yanolja processed $18.3 billion in transactions, up 186% year-over-year. Its enterprise solutions now serve over 1.3 million travel businesses and more than 21,000 sales channels.

Imagine combining Booking.com’s marketplace, Airbnb’s community-driven growth, and Salesforce’s cloud architecture into one company.

“At Yanolja, our goal is to make travel smarter, easier, and more connected for everyone. Through our cloud-based Travel Enablement Platform powered by AI, we are helping hotels and travel enterprises digitize operations, apply AI to real business challenges, and deliver more seamless and personalized experiences for travelers around the world,” says Yanolja Cloud CEO Jeff Kim.

Yanolja shows two lessons. First, great companies can emerge from unexpected beginnings. A “motel app” doesn’t sound like the foundation of a global travel leader — until it is. Second, consumer apps often hide much bigger infrastructure businesses beyond them. Yanolja isn’t just a travel brand; it’s becoming the operating system of global hospitality.

SoftBank Vision Fund invested $1.7 billion to back this ambition, and Yanolja has grown far beyond Asia to become a global travel technology company operating in more than 200 countries. It’s no longer just a local player. It’s a global platform shaping the future of travel.

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CHA Bio — The Camel of Biotech

Not all innovation moves at app speed. CHA Bio is one of Korea’s quiet giants in biotech, specializing in stem cell research and fertility treatments. In 2023, it posted record revenues of 954 billion KRW (about $798 million). In the first half of 2025, revenues rose another 21% year-on-year.

CHA Bio’s story is one of patience. Biotech requires decades of R&D, infrastructure, and regulatory work before scaling. CHA spent years building that foundation — research centers, clinics in the US, Japan, and Korea, and a reputation that makes it a magnet for medical tourism.

CHA Bio has pioneered advances in regenerative medicine — from stem-cell–based therapies and fertility treatments to cutting-edge work in immunology and cell rejuvenation — supported by one of Asia’s most advanced private research networks.

Like other global innovators, they have built their own talent pipeline. For example, they launched CHA university.

The lesson here is different from Toss or Yanolja. Not every company can blitzscale. Some must grow like camels — slowly, durably, across long horizons. The moat isn’t speed but persistence.

Honorable Mentions

Korea’s innovation story doesn’t stop with these three. Coupang has redefined e-commerce with its “rocket delivery” model, leveraging dense cities and logistics innovation to compete with Amazon on its home turf. Lunit has emerged as a global leader in AI cancer diagnostics, proving that Korean healthtech can clear FDA approval and scale internationally. SendBird, which started in Korea and scaled in Silicon Valley, now powers chat APIs for global platforms like Reddit, PayPal, and DoorDash, showing the country’s strength in developer infrastructure. BankSalad, Toss’s fintech rival, illustrates how intense local competition forces even small players to move quickly and broaden scope. And Krafton, the gaming studio behind PUBG, demonstrates that Korean cultural IP isn’t just music or TV dramas — it’s also interactive and global.

Lessons for Entrepreneurs Everywhere

Taken together, these companies reveal a powerful set of lessons. They demonstrate the importance of a long-term outlook, a focus on building local ecosystems to succeed, and unique approaches to management and scale.

The larger point is clear: the future of innovation isn’t only in Silicon Valley. It is being written in unexpected places, solving unexpected problems, in unexpected ways.

This story first featured in my Forbes column

For years, the crypto headlines have vacillated between hype (coin X is breaking out!) and gloom (but limited real-world adoption is nil).

Quietly, the industry has migrated from speculation, into becoming the real plumbing of global finance.

In this piece, I wanted to highlight three key developments that are harbingers of change to come.

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The Tokenization Of Real-World Assets

BlackRock already has a tokenized U.S. treasury vehicle with over $1b in assets. This makes it the largest tokenized firm of its kind.

But to me, that’s not the big news. Blackrock is reportedly looking to tokenize its ETFs. This would change how ETFs are traded. It would allow them to be traded 24/7 – and represent an explosion in relevant assets.

BlackRock CEO Larry Fink was blunt: “Every stock, every bond, every fund — every asset — can be tokenized. If they are, it will revolutionize investing.”

Robinhood is making similar moves, launching both tokenized versions of stocks and ETFs over the summer. Interestingly, it includes those of private companies like OpenAI or SpaceX.

The market for tokenized assets already grew 85% last year to $15 billion (excluding stablecoins). McKinsey estimates tokenized markets could reach $2 trillion by 2030. The World Economic Forum projects tokenization could represent 10% of global GDP as soon as 2027.

Tokenization is moving from fringe experimentation, into a likely mainstay of some of the world’s largest asset managers.

Stablecoins Are Becoming Core Money Rails, And Creating New Apps

Stablecoins represent more than $250 billion in value today. More than 500 million wallets now hold stablecoins, with emerging markets driving much of that growth.

While in the past crypto wallets were for speculation, many use cases today are mainstay financial services across treasury, settlements, cross-border payments. For corporates, they enable instant settlement with transparency. For banks, they radically reduce counterparty risk. For investors, they provide stability in volatile markets.

And for consumers in emerging markets, stablecoins offer a way to escape currency depreciation. In countries like Argentina, Nigeria, and Turkey, inflation and currency volatility erode savings. Apps like Dollar App are building on top of stablecoins to allow users to save and spend in US dollars.

Fintechs And Central Banks Are Building Their Own Rails

Making headlines of course are fintech players. For example, Stripe is incubating Tempo, a new Layer-1 blockchain designed for payments. Its design partners include Visa, Deutsche Bank, Shopify, Revolut, Nubank, DoorDash, OpenAI, and Anthropic. Stripe has also spent over a billion dollars acquiring stablecoin infrastructure — including its $1.1 billion acquisition of Bridge (Fintech Futures).

Circle, Visa, and others are experimenting with proprietary blockchains to reduce costs and accelerate settlement.

More quietly, but likely far more transformative are central bank actions. One hundred and thirty-seven countries, representing 98% of global GDP, are now exploring central bank digital currencies. Seventy-two are in advanced development or pilot stages. In Nigeria, the eNaira doubled to 10 million active users in 2024. In India, the e-rupee in circulation grew 334% in a year, exceeding $120 million by Q1 2025.

As governments adopt digital money, banks, fintechs and corporates will likely follow.

The Tone Is Shifting

Whereas much of this innovation was once the viewed as fantasy, it is increasingly becoming mainstream. The U.S. passed the Genius act. Europe passed the MiCA framework for digital assets.

But it has happened slowly and now seemingly all at once.

Before Visa was a trillion-dollar network, it was a scrappy community experiment led by Dee Hock.

I have had his book: Birth of the Chaordic Age on my bookshelf for years, and - taking advantage of the summer to catch-up on my backlog - have *finally* finished it (H/T Ben Goering for giving me the push).

One of the reflections I’ve loved the most so far was on the role of manager, reflecting on how Dee Hock’s observations can be applied to startups.

What do you think are the most important duties of a manager?

His answer is not what you think.

In this post I will share the framework. I wanted to share reflections specifically on what they would mean for founders as well.

1. First duty of a manager: Manage Yourself

“It is the management of self that should occupy 50% of a manager’s time and the best of one’s ability. And it’s the one thing that can never be delegated.” — Dee Hock

Before you lead a team, raise capital, or scale a product, you have to lead yourself. That means clarifying your values, mastering your emotions, staying grounded through volatility, and cultivating the discipline to focus on what truly matters.

In the volatility of startups, this is existential. Without self-awareness, founders overreact to setbacks, burn out, or make decisions rooted in ego. Without self-discipline, product strategy pinballs with every customer meeting or board request.

Self-management isn’t glamorous, but it’s foundational. Think of it as your internal operating system. Everything else runs on it.

2. Second duty of a manager: Manage Upward

In the startup world, managing upward means managing your customers, board, lead investors, and advisors. It’s not about appeasement or politics—it’s about active alignment and expectation-setting.

Founders often make the mistake of under-communicating or over-delegating this responsibility. But great founders treat their board not as a necessary evil, but as a force multiplier—when managed well.

That means:

• Setting clear expectations

• Pushing back with data and conviction when appropriate

• Being honest and proactive, especially when things go wrong

• Asking for help strategically

If you don’t manage your board, they’ll manage you. And not always in the way you want.

3. Third duty of a manager: Manage Laterally

Startups are forged in close quarters—often between a few co-founders and an early leadership team. Managing those relationships is as essential as it is delicate.

This involves:

• Resolving tension before it festers

• Disagreeing productively

• Being clear about roles and boundaries

• Balancing friendship with accountability

Peer management is tricky because it requires influence without authority. But it’s also where culture is set, especially in the early days. If trust doesn’t exist here, it won’t magically appear later.

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4. Fourth and least important duty of a manager: Manage Downward

Ironically, the responsibility most associated with “leadership”—managing your team—is the easiest if you’ve done the others well. That’s why Dee Hock put it categorically last in importance.

Great founders don’t micromanage. They don’t try to have all the answers. Instead, they:

• Hire people better than themselves

• Create clarity of mission

• Build systems of autonomy

• Give feedback with humility and consistency

Crucially, they also allow their team to manage upward—creating the kind of recursive leadership loop Hock envisioned. If your reports are self-managing, and managing you upward, your job becomes less about control and more about enablement.

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The Startup Paradox: The Most Visible Work Is Often the Least Important

Fundraising. Recruiting. Shipping product. These are the most visible founder tasks—and they matter. But they rest on a quieter foundation: how well you manage yourself and your key relationships. How you’ve built your culture, how much agency you’ve given your team and how you get the best of your people.

Hock’s framework flips the traditional org chart on its head. It reminds us that leadership is a function of self-mastery more than positional power. And that in startups—chaotic, fast-moving, and emotionally taxing—this hierarchy of responsibilities may be the difference between durable success and early implosion.

So next time you find yourself obsessing over how to manage your team, ask instead:

Am I managing myself? Am I managing my board? Am I managing my co-founder relationships?

Start with the hardest work. That’s where the leverage is.

Is the center of gravity for where the most consequential developments in technology are happening moving from the US to other places? This question has lately been the subject of much commentary globally and perhaps found its most scholarly expression in Alan Greenspan and Adrian Wooldridge’s book Capitalism in America in which they argued that the economic dynamism that set the US apart from other nations is now beginning to fade: “Look at any measure of creative destruction, from geographic mobility to company creation to tolerance of disruption, and you see that it is headed downward. The United States is becoming indistinguishable from other mature slow-growth economies such as Europe and Japan in its handling of creative destruction.”

The parallel rise of China has only brought this sentiment into sharper relief. I’ll skip the usual examples of the country’s growing relevance to frontier tech and reference one that doesn’t get nearly the amount of attention that it deserves: ResNet, short for “Deep Residual Learning for Image Recognition”, is a paper published by four researchers at the MSRA lab in Beijing in 2015 which outlines a method to train neural networks hundreds of layers deep; a seminal advancement in machine learning that paved the way for more powerful AI systems. The ResNet paper has in the span of a decade racked up over quarter of a million citations on Google Scholar. It is the most cited artificial intelligence paper ever. It is the most cited computer science paper ever. It is in fact the most cited paper in any academic field published in the 21^st century.

ResNet was authored by Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun. All four got their undergraduate, graduate, and doctoral degrees at Chinese universities. None of them had worked outside China prior to publishing their landmark paper. They have all won awards at top global AI conferences and computer vision contests. In 2015, they won ImageNet, a major competition in artificial intelligence at Stanford which invites researchers to submit AI algorithms to identify objects in images. The MSRA submission was the first time that an AI system surpassed human-level performance at image-recognition on their dataset. ResNet was not a one-off. The last three editions of the ImageNet challenge were all won by teams that came from China.

The ResNet example ought to dispel any lingering doubts about China’s technical capabilities. The country doesn’t just imitate, it also innovates. Its competence is not limited merely to developing applications of technologies but extends to the underlying research breakthroughs that enable them. “China produces a lot of good quality research and some absolutely world-class research in artificial intelligence,” Geoffrey Hinton, the acclaimed British computer scientist and professor at the University of Toronto, told me in an interview. Hinton is the author of AlexNet, the paper that kicked off the modern revolution in AI. Ilya Sutskever, Hinton’s coauthor on that paper, would go on to found OpenAI. Hinton has won every major accolade in computer science, including the Turing Award, often called the Nobel Prize in computing, and the actual Nobel Prize, this time in physics. When I asked him which country was best positioned to take the lead in AI his answer was unequivocal: China.

That would appear to be a ringing endorsement of Greenspan and Wooldridge’s thesis from an unassailable source. Except the question of who’s winning the global tech competition is interesting precisely because it defies easy answers and divides opinion among the field’s loftiest authorities. It is ironic that Capitalism in America came out in 2018, the year when Apple became the first company ever to cross a trillion-dollar valuation. Since then seven other US tech companies have joined the club. The extent of America’s primacy in tech has grown to a scale that can be hard to grasp. The combined value of just the ten largest US tech companies is greater than the entire GDP of every single country in the world except the US itself. Just five American tech companies are worth more than every company listed on every stock exchange in all of mainland China combined. If that is what decline looks like, then what is ascendance?

John Hennessy, the Chairman of Alphabet, who previously served as the President of Stanford for 16 years, was nonplussed when I asked him whether he thought the Valley’s best years can now best be seen in the rear-view mirror. “It’s the killer app that has driven the Valley time and again,” he said. Small and medium-sized advances have always come from different places. But the Valley’s been the place that consistently throws up that big, hairy, epoch-defining technology that changes everything: semiconductors, personal computers, software, smartphones. And it doesn’t look like that’s about to change anytime soon. “It is the center of the next generation of AI companies,” he said. “There will be ones elsewhere, but certainly the Valley probably outnumbers anybody else by a factor of, I don’t know, two, three, four or five probably?”

As the world moves from the dot com era to the dot ai era, the US does appear to have an unassailable lead. But that doesn’t mean that China is not a plausible competitor. The commentariat has a poor track record of predicting the country’s technological trajectory. Just four years ago, in 2021, an article in Foreign Affairs argued that “China has worked for decades to develop a car brand that can rank among the world’s top automakers – but its car companies have had difficulty producing anything that consumers in developed countries actually want to buy.” With BYD now outselling Tesla and the entire German car industry in EVs, one does wonder whether there is another industry assessment out there that has aged quite so badly so quickly.

China winning the next platform shift might just be what it takes for it to tip the balance definitively in its favor. Seven out of ten of the highest profile researchers poached by Meta for its new Superintelligence Lab got their undergraduate degrees at just three institutions on mainland China. Is that an early sign of the shape of things to come? The status quo seems immutable until it doesn’t. Hennessy has been on the scene long enough to have experienced the last major shift. When he first moved to Palo Alto in 1977 all the major technology companies – IBM, Raytheon, DEC – were out in the east. “When you wanted to talk to the movers and shakers in the computer industry you got on a plane and you flew back to either New York or Boston, and that’s just the way it was,” he recalled. But change came fast and it didn’t take longer than a decade for the momentum to switch. “Quite frankly, I’m surprised at how once things began to swing how quickly it happened,” he said.

While it would be prudent to acknowledge the complexity of the US-China tech competition – not simply the story of the rise of one and the fall of the other – it is also I think necessary to look beyond it. The global tech race is often framed as a two-way contest with everyone else a mere also ran. And while it is true that there is unlikely to be a third competitor who can become relevant across the entire spectrum of new technologies, we do have hard to ignore countries and centers of excellence in specific domains coming up in various parts of the world. Asia’s dominance of the battery industry would be a case in point. All ten of the largest battery manufacturers are now Asian: six Chinese, three Korean, and one Japanese. In the time it took me to write my new book Northvolt went from promising upstart to Europe’s best funded startup ever to a collapsed has been. When I interviewed its founder Paolo Cerruti in 2020 he was upbeat that the company could own 25% of the continent’s market for batteries which would ensure that Europe “takes a strategic part of the value of the future car in its own hands.” The ambition struck me as realistic, even modest, given it was regional and not global in scope – which in my mind set it apart from companies in the Valley which sell far more fantastical visions. But the fact that it couldn’t deliver on what seemed to me to be circumscribed ambition shows the stranglehold that Asian players have on this corner of the tech industry.

Another reason to widen our peripheral vision when it comes to tech is that just because two countries dominate the landscape doesn’t mean that valuable lessons and life-changing opportunities can’t be found elsewhere. Let’s take an example from the venture industry. Earlybird was one of 107 new funds that came up in Germany during the first dot com boom in 90s. A quarter century later only three are still standing and Earlybird is the largest of them all. In its early years it opened an office in Silicon Valley to take on marquee names in the industry. The experiment failed. “We totally misjudged and underestimated the challenge of getting access to the best deals in the US in a very well-funded market,” Hendrik Brandis, the firm’s founder, told me. “You have to be pretty lucky to find extremely good opportunities because so many people have looked at it before you and you must see something that nobody has seen yet.”

The firm’s failed expansion to the US gave Hendrik the seed of an idea that would pave the way for future triumphs. It shifted its focus from the West to the East and opened an office in Istanbul to prospect opportunities in Eastern Europe. In 2015 the eastern fund invested in a small startup called DeskOver run by two entrepreneurs from a shabby building in Bucharest, Romania. The company would later change its name to UiPath and when it went public at the NYSE in 2021 it debuted at a valuation of $36 billion, the largest IPO for a European company ever at the time. Earlybird was the first outside investor in UiPath. Its modest million-dollar investment would net the fund upwards of $2 billion, perhaps the best early stage bet in European history.

Another interesting case study is Altos Ventures. It was founded in Palo Alto in 1996 by two Korean immigrants, Han Kim and Ho Nam, who met at Stanford GSB. The fund found it impossible to compete with the more established names and almost went out of business. Their struggles are the subject of two HBS case studies. Han told me that the company eventually found its footing by expanding out to regions overlooked by traditional funds where they worked with immigrant entrepreneurs who got little love from the bigger names in the industry. They also eventually entered the Korean market. Altos is today one of few funds that have managed to succeed on both sides of the Pacific. It was the largest shareholder in Roblox, a stake that was worth $8 billion at IPO, and an early investor in Coupang, Korea’s largest e-commerce platform, whose market cap tops $50 billion.

But perhaps the most important reason for tuning into other geographies is that at some point our collective beliefs become self-fulfilling prophecies. If everyone thinks that tech is a US-China duopoly then that’s what it’s going to be. Alex has previously written about how we’ve gone from vibe coding to vibe investing – AI companies raising vast fortunes without any product or customers or financials to speak of. Perception drives reality. While we have strong opinions when picking sides between the US and China; one of the few things that probably everyone can agree on is that it can only be a good thing for more places join the mix. The more we move the spotlight to other regions the more likely it is that they will attract the resources they need to at least show up to the starting line. Talk is cheap and that’s an excellent reason to have more of it.

Alex: Globally, certain markets dominate industries. Others are becoming experimentation labs. In fintech, I’d argue that Brazil is a little bit of each. It is home to global powerhouses like Nubank. Yet, a combination of world-leading Whatsapp penetration, government led open-banking regulation, real-time and nearly free payments via PIX, and of course an AI overlay, is creating the potential for business models in the U.S. we can’t yet even imagine.

In this edition of 99%Tech, my good friend Luiz Manzano, GP of Big_Bets (with whom we co-led the Avenia Preseed (the Bridge of Brazil) writes about the fintech ecosystem.

By Luiz Manzano

Boston has biotech. Israel dominates cybersecurity. And Brazil? Well, Brazil is fintechland. And if you think this is just excited Brazilian talk, grab a seat because the data—and stories—speak louder.

Take, for example, the rise of Pismo. Founded in São Paulo, Pismo quietly built one of the most sophisticated and scalable banking-as-a-service platforms in the world. In 2023, it was acquired by Visa for $1 billion—one of the largest exits in Latin American fintech history. The cofounder, Daniela Binatti, started her career in enterprise tech and leveraged deep technical insight and relentless focus to deliver for some of the most demanding financial institutions on the planet. Her story isn’t an outlier—it’s a signal.

So what’s behind Brazil’s fintech dominance?

Let's start with Pix, the payment system that became synonymous with instant transfers in less than five years. In 2024, Pix processed an astonishing $4.56 trillion (R$ 26.45 trillion, considering an exchange rate of 5.8 BRL/USD), handling over 63.5 billion transactions throughout the year—a 54% increase compared to 2023. Over 60% of the Brazilian population used Pix at least once a month in 2024, with the Federal District showing the highest adoption at 77%. During Black Friday alone, Pix registered nearly 240 million transactions, moving $22.4 billion (R$ 130 billion) in a single day. With 82% of transactions carried out via mobile devices, Pix is clearly the backbone of Brazil's modern financial infrastructure.

If Pix leads in popularity, Brazilian Open Finance takes the crown as the "largest open financial ecosystem on the planet." By 2025, more than 60 million active consents and over 2 billion integrations highlight a massive leap in financial inclusion, surpassing the US and Europe by a wide margin.

Financial market giants? Brazil has plenty. Nubank, born in Brazil, now surpasses Itaú in market value and serves over 110 million customers across Latin America. It’s the region's first digital bank to achieve this milestone, firmly positioning Brazil on the global fintech map. And the growth doesn't stop there: Stone, PagSeguro, and a new generation of fintechs such as Ume, specialized in Pix-based credit; BRLA, at the forefront of the stablecoin revolution as Brazil moves closer to regulatory clarity; and Conta Simples, simplifying financial management for entrepreneurs—are all building robust businesses, many listed on international stock exchanges.

Speaking of money, venture capital continues to flow strongly into Brazilian fintechs. In 2024 alone, $1.55 billion (R$ 9 billion) was invested. Even as the global economy slows down, Brazil speeds up. Investors place big bets on local fintechs, confident that solutions developed here will soon be replicated worldwide.

But Brazil isn’t just growing—it’s uniquely positioned. A few preconditions have turbocharged this ecosystem:

• A massive TAM: With over 200 million people and a historically underbanked population, Brazil offers scale that few fintech markets can match.

• Mandatory e-invoicing laws (Nota Fiscal Eletrônica): These created a standardized, digital trail of B2B commerce—fertile ground for credit underwriting and receivables financing startups.

• WhatsApp penetration: Brazil is one of the top WhatsApp markets globally, making it a powerful channel for onboarding, engagement, and even payments.

• A modern, progressive central bank: The Central Bank of Brazil isn’t just tech-friendly—it leads innovation, from Pix to Open Finance to the forthcoming Drex digital currency.

These foundational elements haven’t just made fintechs grow—they’ve changed how society operates. For instance, digital inclusion has had downstream effects in unexpected places. Small business owners in the favelas of Rio can now receive instant Pix payments and qualify for credit based on verified transaction history. Informal workers once paid in cash can open digital accounts in seconds and access government subsidies during crises.

It’s also influencing education and employment. As fintech adoption rises, so does the demand for digital skills. Universities and bootcamps now offer specialized tracks in fintech, compliance, and data science. Many founders of Brazil’s top startups are under 35, and many of them come from nontraditional backgrounds. Fintech is no longer just a sector—it’s a pathway to social mobility.

International platforms are taking notice too. Global banks and payment networks are partnering with local players to expand services. Visa’s acquisition of Pismo is just one example. Stripe, Adyen, and others are either investing in or collaborating with Brazilian infrastructure providers to tap into local expertise. These partnerships reinforce Brazil’s status not just as a local powerhouse but as a global hub of fintech innovation.

What about the future? Brazil’s fintech stack is now the baseline for a new generation of apps and services. We’re seeing fintech become embedded in everyday tools—CRMs that issue invoices and reconcile payments automatically, e-commerce platforms that integrate real-time settlement, and accounting tools built around Pix-native architecture. Drex, Brazil’s planned CBDC, will likely add another layer of programmable money to this foundation.

And that leads to a broader point: why should anyone outside of Brazil care?

1. Brazil is a preview of what’s to come. What’s happening here foreshadows global fintech trends. The success of Nubank, Pismo, and others has already inspired a wave of founders and investors asking, "Who's building the Nubank of Africa? The Pismo of Southeast Asia?"

2. A new generation is building on this stack. Jota.ai combines WhatsApp ubiquity, Pix, Open Banking, and AI to create novel financial services from the ground up. Iniciador, another standout, leverages new initiation rails to power seamless B2B payments. These aren’t just Brazil plays—they’re blueprints for fintech infrastructure everywhere.

3. There are lessons for every ecosystem. Bold regulatory moves, public-private collaboration, and modern infrastructure can dramatically accelerate financial inclusion. Other markets would do well to study—not just admire—Brazil’s approach.

4. It’s not just innovation—it’s resilience. Brazilian fintechs have been forged in a challenging macro environment, with high interest rates, inflation, and currency volatility. That’s made founders battle-tested, products more efficient, and go-to-market strategies more disciplined.

Brazil offers not just a vision of fintech’s future, but a playbook. From regulation to user behavior, from infrastructure to imagination, it’s showing the world what’s possible.

Next time someone asks why Brazil is the fintech capital of the world, you’ll know exactly why: the data speaks loud and clear, and the financial future is already here.

[99%Tech] Rebranding?

When I started 99%Tech, the name was always a placeholder. Hence why it was [square bracketed]. I was always considering renaming it eventually.

Since then, this newsletter has scaled to ~10k subscribers, including startup founders, CEOs of technology companies and VCs around the world. I have also written a book (“Out-Innovate with HBR) and started a VC fund (Fluent Ventures). And the tech industry has continued its relentless globalization.

I’m considering renaming the newsletter. I’d love your feedback. Here are some ideas we’re considering, including keeping it as is. What do you think?

Thank you! And now to your regular programming.

This post originally posted on my Forbes column.

Dispatches from SuperReturn Berlin and the Inovia VC Summit

“It was the best of times, it was the worst of times.” On the heels of Super Venture & Super Return Berlin, and a LP/GP summit in Montreal organized by Inovia, I wanted to reflect on what felt like a panoramic view of the industry, across 1) managers of VC funds 2) startups raising capital and 3) incumbents in the public markets. What struck me most wasn’t any one deal or datapoint, but the duality of two starkly different realities.

The technology industry today, for startups and venture capital firms alike, is best described as a tale of two cities.

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Venture capital

In venture capital, the divergence could not be more stark. Research by Pitchbook demonstrated that nine firms collected 50% of all venture funding last year. The top 30 took the vast majority, across a few hundred firms that announced raises.

At SuperReturn, partners from megafunds spoke about oversubscribed raises. Meanwhile, emerging managers are scraping to survive and define their edge.

As Scott Hartley, co-founder and managing partner of Everywhere Ventures told me: “For emerging managers differentiation is key, as venture returns heavily skew due to a long tail of large outcomes. While it may seem safer to get on-base at bats, median venture returns barely outpace other asset classes. The reason allocators look at VC is for asymmetric exposure, which means providing capital to yet undiscovered drivers of the future economy.”

First-time and even second-time funds have faced arguably one of the hardest fundraising markets in history. Similar research from Pitchbook suggests a risk of certain emerging managers dying off.

One panelist summed it up succinctly: “Consolidation is the new diversification.”

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Startups: AI Boom vs. Everyone Else

The gulf between the haves and have-nots is perhaps even more stark in startups, the companies VCs fund.

Asaf Horresh of Vintage explained during his Super Venture keynote: “if you’re AI it’s 2021”. Capital is flowing freely into foundation model startups, AI infrastructure plays, and workflow automation layers. Several venture firms have reoriented their entire sourcing around AI, and LPs are watching closely.

But for nearly everyone else, Asaf put it perfectly: “you’re in the desert.” Even solid companies are seeing down rounds or resorting to insider-led bridges. The bar has never been higher.

While I am nervous about nosebleed valuations and non-Camel strategies - the potential for AI justified. But the capital imbalance is striking. At SuperReturn, AI was on nearly every main stage. As Arpan Punyani, Co-Founder and General Partner at Garuda Ventures told me: “Like the transistor, cloud, or mobile, AI is a foundational enabling technology. If you’re not building an AI company at some level, the bar is just incredibly high to raise venture capital now.”

Carta noted that seed deals are growing scarcer, demonstrating the growing scarcity. However, average valuations, pulled up by A.I. startups have increased.

The other vector in startups was geography.

Today, like it or not, capital is re-concentrating in the old capitals partially because of AI: San Francisco, London, Tel Aviv. Startups in non-central ecosystems are finding it that much harder to raise capital. From side conversations, there’s a growing sense that global GPs need to “earn the right” to go abroad again.

The irony (and certainly central to my day job at Fluent Ventures) some of the best startups are being built in emerging ecosystems—with less burn, less competition, and lower valuations.

Public Markets: A Mirror Image

The bifurcation is not limited to venture. In the public markets, the “Magnificent Seven” (Nvidia, Meta, Apple, et al.) account for the lion’s share of returns. Small caps and international equities remain underloved. It’s the same pattern: consolidation of value, divergence of experience.

Looking Ahead

In the technology industry, the power law is the rule of the game.

But the magnitude of the power law is not. As exits increase, releasing DPI, market sentiment calms, and desire for diversification outside the U.S. grows, I expect much of this to normalize. But this will take time and there will certainly be collateral damage.

But, as history tells us, sometimes, the revolution begins in the second city.

Most people look to Silicon Valley to see the future. As many readers in this newsletter know, I’ve often found it helpful to look elsewhere.

Years ago, while working at a previous firm, Omidyar Network, we were exploring the rise of neobanks globally. I saw models that worked: apps that offered mobile-first banking to underserved consumers, built trust in low-trust environments, and scaled profitably. I didn’t know it then, but these learnings would help me get to conviction on one of the biggest U.S. fintech stories of our time: Chime.

I am grateful to Chris, Ryan, and Matt for the opportunity to support them at the Series B. Investing in Chime was also how I eventually met Cathay Innovation, which led the round, and where I eventually worked for 5 years, before launching Fluent Ventures.

As Chime (NASDAQ: CHYM) went public this week, it’s easy to frame it as a classic Silicon Valley success. But to me, it’s something more interesting: a case of geo-arbitrage—where global patterns helped de-risk what looked like a novel U.S. play.

Let me explain.

The Global First-Movers

Before Chime, there was Tinkoff in Russia. Founded in 2006, it built a full-stack digital bank in a market with poor infrastructure and low consumer trust. It began with credit, scaled without branches, and became one of the world’s first profitable neobanks.

In the 2010s, Europe’s neobanks entered the scene. Monzo, Revolut, and N26 targeted digital natives disillusioned with high fees and poor UX. They began with checking accounts or foreign exchange and expanded horizontally. But in Europe—where interchange fees are heavily regulated—they had to get creative. Their model relied on cross-selling paid subscriptions, lending, and add-on products to make the economics work.

Then came Latin America. Nubank launched in Brazil with a different approach: credit-first. Credit card penetration was low, interest rates were high, and consumer pain was real. Nubank became a beloved brand by offering radically better credit to millions of previously excluded users—and then expanded into a full suite of financial services.

On the other side of the world, in Korea, Toss built a financial superapp. It started with payments and evolved into a multi-product ecosystem spanning insurance, investments, and even healthcare. Its playbook wasn’t about monetizing a single product, but about becoming the trusted financial platform for daily life.

Different geographies. Different products. But a shared insight. Customers were looking for a modern banking experience. They wanted clear and transparent products, no hidden fees (overdrafts at the time were still a $30b+ industry!), convenience and simplicity. They wanted to be treated with dignity and respect.

Chime’s Unique Model

The U.S. financial system is paradoxical. It’s the largest in the world, yet it has some of the most dysfunctional consumer banking experiences. Tens of millions of Americans live paycheck-to-paycheck, hit with overdraft fees, account minimums, and confusing disclosures.

That’s the market Chime entered. Chime’s wedge was simple: a no-fee checking account with early access to direct deposit and no overdraft penalties. But behind that simplicity was a sophisticated strategy—one rooted in U.S.-specific regulatory arbitrage.

Thanks to the Durbin Amendment, banks under $10B in assets are exempt from interchange caps. Chime partnered with Durbin-exempt banks and was able to monetize debit card usage,which made every swipe profitable.

And because Chime won when its customers used the product, they were deeply aligned with creating a long-term relationship.

While Nubank used credit to grow LTV, Chime used debit. While Revolut sold add-ons, Chime scaled with trust. While Toss built breadth, Chime focused on simplicity.

The model was tailored to the American context—but the conviction came from understanding how these patterns had worked globally.

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What Chime Got Right

Product and economics aside, what truly set Chime apart was its customer focus.

It didn’t just eliminate fees. It reimagined the entire relationship between a bank and its customer:

• Get paid early gave users liquidity when it mattered most.

• No overdraft fees meant no punishment for being poor or not paying attention to your balances. They also created a SpotMe feature for small microloans.

• Transparent communication reduced anxiety around balances and bills.

• Responsive support made users feel seen—not just serviced.

In doing so, it built a brand that stood for something. Chime wasn’t a disrupter. It was an ally. That’s a powerful thing in a country where nearly half the population struggles with financial fragility.

The Lesson: Geo-Arbitrage Goes Both Ways

As venture investors, we often talk about exporting U.S. models globally. But geo-arbitrage works in reverse too. Sometimes the best way to understand an opportunity at home is to see what’s already been proven abroad.

Chime looked like a bold bet. But to anyone watching the neobank revolution unfold from São Paulo to Seoul, it felt inevitable.

The Series B investment is up from $0.47/share to $43 at it’s stock market debut. Geographic arbitrage worked.

Critically, geo arbitrage is not copy-paste. But it provides mental scaffolding to believe Chime could work—uniquely adapted to the U.S. market. It is also what led my investment in other neobanks globally, including Neon (a unicorn in Brazil).

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What’s Next?

As Chime enters the public markets, it’s more than a fintech success story. It’s a reminder that innovation doesn’t just flow from Silicon Valley out to the world. It flows in every direction. This is what I call the innovation supply chain.

If we want to see the future, sometimes we just need to shift our gaze outward.

Because of the next category? It might already be winning—in Jakarta, in Lagos, or in São Paulo.

We just have to pay attention.

I bought my first bitcoin in 2013. Like many, I was captivated by the promise of decentralized finance. But while I’ve dabbled in the space for over a decade in my personal capacity, as a professional investor, I never had the confidence to invest someone else’s money in the sector—until now.

At Fluent Ventures, we’ve avoided the speculative mania. Instead, we’ve focused on areas where this new infrastructure might offer 10x better solutions than its analog counterparts. Over the last few years, we’ve been excited about one intersection of crypto and decentralized finance: stablecoins. With Avenia, in Brazil, we have made our first investment.

The Rise of Stablecoins: A Quiet Revolution

Amid the noise of volatile tokens and meme coins, stablecoins have quietly become one of the most practical and widely adopted use cases in crypto. Pegged to fiat currencies like the U.S. Dollar or Brazilian Real, they offer the best of both worlds: the trust and familiarity of traditional currency, and the speed and flexibility of blockchain rails.

Stablecoins have exploded in use around the world.

International transfers via stablecoin rails offer three specific and concrete benefits:

• Settlement is near-instant, enabling real-time global transactions. Cross-border wires can take a few days to clear.

• Transactions are transparent, powering greater visibility. If you send money from the U.S. to France via traditional networks, a customer quite literally has no idea who has your money at a specific moment in time. On stablecoin rails, it is visible in real-time.

• Fees are significantly lower, especially compared to SWIFT, Western Union, or traditional remittance channels. Even when comparing to next gen platforms like Wise (which I use) stablecoins avoid the need for a FX provider to hold balances in multiple geographies for “netting” (Wise and others do not move all the money back and forth, instead they only move the net balances of all the back-and-forth wires.)

Stablecoin volumes haven’t just increased. A number of new use cases have emerged across B2B payments, payroll, international invoicing, and even treasury management. In emerging markets, stablecoins are creating new opportunities for customers or businesses to hold balances in hard currencies without the need to open local accounts. Expect a longer post on this soon.

The Required Plumbing: Proven Models

For stablecoins to work, one key piece of infrastructure is required: compliant on-off ramps, that are easy to access, with programmable workflow tools. And in markets where local stablecoins are not offered, these may be needed.

The value of this infrastructure is already being demonstrated globally:

• Bridge was acquired by Stripe in 2024 for $1.1 billion. The company built stablecoin-based payment APIs that allows enterprises to integrate crypto-native rails seamlessly into traditional workflows.

• Circle, the issuer of USDC, is going public. Its growth reflects increasing institutional trust in stablecoin-backed infrastructure. USDC is now used by major fintechs, banks, and enterprises for a wide range of financial operations.

• Tether, the issuer of USDT, is the world’s most profitable company on a per-employee basis. With a small team and massive adoption, Tether quietly generates billions in net income, underlining the power of well-executed infrastructure.

Avenia: Building Stablecoin Infrastructure for Brazil

Our thesis on Avenia is that similar infrastructure will be required in many markets around the world. Avenia is focused on Brazil. The company is building stablecoin rails and a digital BRL token—a localized version of what has worked globally, tailored for the unique dynamics of Brazil.

The founding team brings experience from Brazil’s top fintechs (Nubank, BTG Pactual), global crypto platforms like Coinbase, and even running a crypto hedge fund. They blend regulatory fluency with technical execution—a rare combination in any market.

Brazil is a particularly compelling geography for this model. It’s home to one of the most dynamic fintech user bases in the world. It is deeply integrated with the world economy. The regulatory environment is sophisticated, complex, and open to cryptocurrencies.

In under 12 months, they have already processed R$ 3 billion across 2 million transactions, and are profitable. When we invested, they had more cash in their bank account than when they started!

Why We Believe There is GeoAlpha with Avenia

At Fluent, we back globally inspired companies tailored to local ecosystems. We look for models that are proven, but where the edge comes from nuanced execution on the ground.

Avenia fits squarely into that approach:

1. A proven model. We’ve seen this playbook before, and we know how powerful it can be.

2. A Local winner is likely. For this business model and in financial infrastructure more broadly, we believe trust, regulatory know-how, and local integrations create strong moats.

3. Early traction. Avenia has had explosive “camel” like growth with profitable unit economics and managed burn.

4. Co-investment with a local leader. Excited to partner with big_bets, one of our favorite local coinvestors.

5. Stage-aligned. We’re investing early, where we can be most valuable as a partner.

What Comes Next

We believe Avenia represents a broader shift, not just a bet on Brazil or stablecoins, but a deeper belief in infrastructure-first models operating at the intersection of crypto and decentralized finance.

We’re thrilled to be on this journey with Avenia. If you are building something similar elsewhere, we’d love to hear from you. We are open to partnering with several teams in the same category across different geographies.

This piece was first published on my Forbes column

Global innovation has exploded around the world. Yet few markets are as large or as deep as the U.S. Taking Latin America as an example: In 2024 alone, LATAM fintechs raised +$2.6 billion in venture . There are over 30 fintech unicorns across the region.

While global attention focuses on the "what" of these startups, the "how" is equally revealing. How do these companies scale? How do they navigate a fragmented, highly regulated, and deeply local landscape?

Answering this question has been a core aspect of my work over the last decade as a venture capitalist, and my book Out-Innovate (HBR). I am just back from Brazil, and in this piece will use case studies from this region to outline what I see as a global trend outside Silicon Valley: three distinct key archetypes – each with their own advantages, tradeoffs and lessons for founders and VCs alike.

Archetype 1: Single country champion

The first archetype is the single-country champion. These are startups that focus on winning one massive market, often because that market alone is big enough to support a multi-billion-dollar outcome. Think Brazil or Mexico.

This only works for the largest TAMs in the largest markets. And it favors sectors where regulation is complex, consumer behavior is localized, and operating environments demand deep on-the-ground execution. Going deep rather than broad is the answer.

Nubank is perhaps the most iconic example. It launched in Brazil and spent years dominating its home turf, expanding beyond its first product, a credit card, into other product lines like wealth management or bank accounts. Still primarily a Brazilian business (though it recently expanded to Spanish-speaking Latam), it is one of the largest digital banks in the world with a current ~$56 billion market value.

Clip in Mexico followed a similar path—starting with payments and expanding into a full-stack SMB platform. Likewise, Kueski (a portfolio company) began as a lender and grew into a broader consumer finance play, integrating products like BNPL.

In each case, the playbook is the same: win big at home. Prioritize product expansion in your home market over expansion. Only when fully saturated, expand cautiously. These startups compound by layering multiple offerings, turning high-friction markets into powerful moats.

Archetype 2: Regional Player

The second Latam startup archetype is the regional player. These are companies that recognize their home markets are too small on their own, so they go multi-country from the beginning.

Anecdotally, during a recent panel at Kauffman Fellows with Rafael de Haro of Cometa and Antonia Rojas of Attom Capital, we explored how this is most common in Spanish-speaking Latin America, particularly outside Mexico, where linguistic and cultural similarities make regional expansion more feasible – and local market TAM demands it.

In my view, Colombia has become one of the prime examples of regional launching points. Rappi is one of the best-known examples. Founded in Colombia, it quickly spread across Latin America, with operations in 9 countries and over 250 cities just 5 years after its inception, becoming a regional super-app. Contrast that with iFood, which focused solely on Brazil and dominated there. Another example is Ualá, the Argentine neobank that now operates in Mexico and Colombia. And in my historical portfolio, Xepelin exemplifies this model. Starting in Chile, it quickly expanded to Mexico to scale its B2B payments and credit platform. For these companies, success hinges on being able to replicate product-market fit across diverse geographies very early.

As Daniel Vogel, the Co-founder and CEO of Bitso told me: “When we started Bitso in Mexico, we weren’t just building a crypto platform—we were responding to real financial pain points. It quickly became clear that these challenges weren’t unique to Mexico. They were regional. That insight drove our expansion into Argentina, Brazil, and Colombia. Each market is different, but the demand for more inclusive and efficient financial infrastructure is universal across Latin America.”

In my book Out-Innovate (HBR Press), I nicknamed these companies “born global.” Often, it involves starting in a smaller market to test, then moving into a larger anchor market like Mexico to scale. It’s a strategy that balances speed and depth.

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Archetype 3: global infrastructure builder

To me, one of the more nascent archetypes is the global-born infrastructure builder. These are Latin American startups that, from day one, are designed to serve the world. Typically, they offer enterprise-grade infrastructure, rather than B2B or consumer services, that are inherently cross-border. Many have emerged out of the smallest markets to become global from day one.

Uruguay is quietly becoming a key launching point. dLocal, born in Uruguay, is one of the best examples. It built a global cross-border payments network serving large international merchants across emerging markets. Today, it offers more than 900 payment methods in over 40 countries. Sergio Fogel, dLocal’s CSO & Co-Founder told me “We launched in Brazil before Uruguay… [Referring to the mindset that led the company to scale rapidly across markets] It forces you to think internationally if you have ambition.”

Even within larger markets, this model is rising. For example, Pismo is a standout here. The Brazilian cloud-native core banking platform was recently acquired by Visa for $1 billion, with customers around the world. As Daniela Binatti, Pismo’s Co-founder told me in a recent interview: “One of the things that we had in mind since the very beginning was building something to scale and to be ready to go global.”

These companies succeed because they operate in enterprise segments where global demand outweighs local complexity. Customers literally pull them across borders. They also benefit from macro tailwinds: talent cost arbitrage, rising engineering capabilities across the region, and increasingly, AI-enabled development that reduces the barriers to global SaaS plays.

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What this means

These three archetypes aren’t rigid boxes. There is a lot of grey. Neither do they apply only to fintech (though fintech illustrates them especially well).

For founders, it’s a reminder to pick your battles, and spend your limited resources, wisely. In massive, high-friction markets like Brazil and Mexico, depth wins. In smaller Spanish-speaking countries, breadth may be necessary. And for those with global DNA or enterprise models, the world is increasingly accessible from Latin America.

For investors, it’s a signal to look beyond the product and ask: what is this company’s path to scale? Is it a Nubank or a Pismo? A Rappi or a Clip?

At Fluent Ventures, the venture capital firm I work with, we believe localization and regional execution eats everything else. And as AI continues to reshape product development and talent becomes increasingly distributed, I expect we’ll see even more Latin American startups start global from day one.

That’s a good thing. It’s a sign of maturity. A sign that Latin America is no longer just catching up, but leading in its own way.