Notes on Building Startups From Years of Watching Founders Navigate Emerging Markets

I could write about the afternoon I sat in a conference room in Makati watching a presentation on financial inclusion. The slides were polished, the data compelling, the market opportunity measured in billions. But I kept thinking about something my taxi driver had mentioned that morning—how he sends money home to Mindanao every month using a network of relatives and shop owners who move cash through WhatsApp messages, charging a fraction of what Western Union charges.

The presenters never mentioned systems like this. I’m still trying to understand why.

What strikes me now, months later, is how often I’ve sat in similar rooms listening to similar presentations about “underserved markets” while the people being discussed have already solved their problems in ways that work better than what’s being proposed. The taxi driver’s remittance system moves money faster and cheaper than the regulated alternatives. The motorcycle taxi networks that existed years before Grab arrived. The hyperlocal delivery services run through Facebook groups.

I thought this was just about financial services until I started noticing the pattern everywhere. What looks like absence of infrastructure is actually presence of different infrastructure. What looks like market opportunity is often working systems that outsiders haven’t bothered to understand.

This matters because it reveals the first principle of building in emerging markets: the assumption that existing solutions are primitive is usually wrong. The speed at which you discover this determines whether your venture survives its first encounter with reality.

Early stage companies die when founders lose faith in their ability to figure things out, and faith erodes fastest when progress feels invisible. I’ve watched this happen enough times to recognize the pattern. Founders spend months analyzing market reports and competitive landscapes, building elaborate models about customer acquisition costs and lifetime value. Then they launch and discover that people behave nothing like their spreadsheets predicted.

The companies that survive are the ones that built their entire operation around closing the gap between assumption and reality as quickly as possible. They don’t just talk about lean methodology; they structure everything, across hiring, product development, even office leases to maximize learning velocity.

But here’s what I couldn’t figure out for the longest time: why some founders embrace this uncertainty, while others fight it. Now I think it’s simpler than that. The ones who succeed treat ignorance as temporary and interesting, rather than permanent and shameful. They’ve learned that being wrong quickly is a competitive advantage.

This requires a particular kind of discipline when entering unfamiliar terrain. The natural instinct is to reduce uncertainty through research. You read the reports. You study the demographics, then later map the competitive landscape. I understand there’s comfort in data, because it makes you feel like you understand something without requiring you to change anything about yourself.

But cultural knowledge—the kind that determines whether people actually adopt your product—resists quantification. It lives in the gap between what people say they want and what they actually use. You can’t learn this from surveys. You have to earn it through proximity and time.

The founders who succeed don’t just visit markets; they embed themselves long enough to develop intuition about what works and what doesn’t that goes beyond what they can articulate in a business plan.

I’ve spent some afternoons in government offices to understand that regulations work differently than most founders expect. The written rules are rarely the most important part of the equation. What I couldn’t understand, during my first few encounters with regulatory agencies, was why identical applications would receive different responses depending on who reviewed them. I assumed this was arbitrary.

What I now know, is that regulations are not neutral technical documents. They are expressions of political priorities and social anxieties. The officials who interpret them are humans with careers and constituencies and concerns about reputation. And each official is solving a different problem, and not just whether your business complies with the law, but whether approving it creates headaches they’ll have to deal with later.

This changes the approach entirely. Instead of trying to compliance your way around obstacles, you focus on alignment. What outcomes do these people actually care about? What would success look like from their perspective? How can you make their lives easier while achieving your goals?

The most successful companies I’ve encountered didn’t fight regulations. Instead, they helped shape them. Not through lobbying, but by demonstrating that their approach solved problems regulators cared about. They turned potential adversaries into stakeholders by making regulation work better, not by working around it.

This requires patience that venture-backed companies often don’t have, which points to a deeper tension in how startup ecosystems develop. The models that work in centers of capital and innovation like San Francisco assume certain institutional conditions across predictable legal frameworks, accessible capital markets, sophisticated customer bases.

In markets where these conditions don’t exist, different models evolve. Companies that grow through customer revenue rather than investor capital. Products that solve urgent problems rather than creating new desires. Business models that work within existing social structures rather than trying to disrupt them.

What’s interesting about these constraints is how they force clarity about what actually matters. When capital is scarce, you focus on customers who pay immediately for things they need urgently. When infrastructure is unreliable, you build solutions that work offline and degrade gracefully. When trust is earned rather than assumed, you design for transparency and control.

I used to think these were limitations to overcome. They’re actually design principles that produce better products.

Consider the accessibility question. Walk through any tech hub in Manila or Cebu and you’ll see teams debating how to “adapt” their products for local conditions. The conversation usually centers around what to remove—simpler interfaces, reduced functionality, lighter apps that work on cheaper phones.

But the most successful products go the other direction. They start with radical simplicity and add complexity only when it’s essential. They assume intermittent connectivity and treat constant access as a luxury. They design for sharing and offline use because that’s how most of the world actually works.

What’s remarkable is how often these constraints produce innovations that prove valuable everywhere. Products designed for slow connections load faster in San Francisco too. Interfaces optimized for low literacy are easier for everyone to use. Business models that work without venture capital are more sustainable.

This suggests something important about the relationship between margins and centers in the development of technology. The assumption that innovation flows from rich markets to poor ones is increasingly backwards. The most pressing constraints—environmental sustainability, economic inequality, technological accessibility—are felt most acutely in emerging markets, which means the solutions developed there often point toward futures that everyone else will eventually face.

But recognizing this requires abandoning some cherished beliefs about how technology creates value. Apps designed to maximize time-on-device often make people’s lives worse, not better. Growth at any cost creates costs that compound over time. Disruption, as a goal rather than a side effect, often destroys more value than it creates.

The companies that understand this don’t just build different products; they build with different intentions. They track metrics that correlate with whether the lives of their users actually improved, rather than whether engagement increased. They measure success by whether they’ve made tomorrow easier than today for people whose days were already hard enough.

In markets where alternatives are scarce and switching costs are high, I argue trust becomes one of the ultimate competitive moats. And trust is not something you can hack or optimize or scale artificially. You earn it by building things that work as promised, that treat users with respect, that solve real problems without creating new ones.

You, more importantly, earn it by being present when things go wrong and responsible when the consequences of your choices extend beyond your immediate users. You also earn it by caring about the ordinary lives of people whose problems you’re trying to solve more than you care about the extraordinary valuations of companies whose problems you’ll never face.

Because here’s what I’ve learned watching technology reshape communities: the innovations that matter most in the long run are the ones that help people live with more dignity, more agency, more hope about tomorrow than they had today.

Everything else is just clever engineering.