Bret Waters, a lifelong denizen of Silicon Valley, entrepreneur, investor, and respected academic and friend of mine, has spent decades at the epicenter of global innovation. As an instructor in Stanford’s Continuing Studies program since 2009, former Dean’s Advisory Council member at Stanford Graduate School of Education, author of The Launch Path: Getting from a Startup Idea to a Launch-Ready Venture, and a frequent lecturer at top business schools worldwide, Bret’s perspective on entrepreneurship and innovation is both deeply rooted and globally informed.
His latest “missive”, written from Georgia (the country, not the US state), deserves every entrepreneur’s close attention. He describes what may be one of the most profound shifts in the history of innovation: the center of gravity is moving—rapidly—away from Silicon Valley and Western capitals toward the developing world. In his remarks to students at Caucasus University in Tbilisi, Bret framed a new era: The next great wave of global innovation will not emerge from the familiar strongholds of California, London, or Beijing, but from places with fresh ambition and unique needs, places like Tbilisi, Lagos, Kyiv, or São Paulo.
For much of the last thirty years, the US set the template: Americans built out the internet’s consumer platforms and its enterprise backbone. If you wanted to launch globally, you matched their playbooks, adopted their tools, and, above all, sought their venture capital. But Bret observes a crucial transformation: the old dominant model is fading. New champions like Sweden’s Spotify, China’s TikTok, and Wise from London and Estonia prove that technology can now “break out” from anywhere. Now, with AI-driven development, we stand at the gateway to an even more radical democratization.
Bret says, “The common myth is that these countries are ‘catching up.’ But that’s not what’s happening. They are building entirely different models—solutions that are often faster, cheaper, and more inclusive than anything dreamed up in the West.” It is no longer about exporting the Silicon Valley rulebook; it’s about solutions built for local needs that scale globally. That observation calls for close examination—because the economic engine powering this movement is nothing less than a revolution in how software gets made.
How AI Coding Is Breaking Down Barriers
Historically, creating enterprise software or even sophisticated consumer apps required deep coding skill, broad teams, and significant upfront capital. In the US, risk-hungry VCs absorbed these costs. Elsewhere, especially in markets like Europe, Africa, and Asia, capital was harder to come by. Risk aversion reigned; investors wanted proven traction before writing checks. This dynamic kept entire regions on the sidelines, “catching up” rather than truly competing.
But the rise of AI-driven coding, low-code/no-code platforms, and operative AI agents has fundamentally changed the game. Today’s ambitious founders, even outside the US venture ecosystem, can:
- Prototype at speed using AI-driven development environments.
- Operate efficiently with agent-based workflows for customer support, compliance, and analytics.
- Launch products, iterate, and even scale before taking “real” money from local (often still risk-averse) investors.
The result? You can build a credible, sometimes even world-class, application without needing the capital that once gave US startups a stranglehold on global innovation.
Examples: Non-US Startups Leveraging AI, Traction Before Capital
Let’s explore several recent startups and track how far they progressed before securing outside investment. Their stories demonstrate a pattern: thanks to AI, they reached product readiness and significant traction with minimal capital and tiny teams. Funding follows results—not the other way around.
1. Synthesia (London, UK)
- Founded: 2017
- First Funding: Seed round in late 2018, led by European angel investors and MMC Ventures after initial product traction and commercial pilots. US VCs didn’t participate until much later (Series B, 2023).
- AI Role: Synthesia used proprietary AI video generation systems to build and iterate MVPs rapidly. The co-founders themselves handled product prototyping and early deployments, then grew user adoption in Europe and Asia before seeking capital to scale.
2. NALA (Tanzania/UK)
- Founded: 2017
- First Funding: Pre-seed from African-based angels and accelerator grants after successful pilot launches and real user adoption (~2018-2019). Global VCs (including US-based) were not involved until later rounds.
- AI Role: NALA automated compliance, payments, and customer operations using AI agents and lean code structures, supporting cross-border operations with a small team.
3. Preply (Kyiv, Ukraine)
- Founded: 2012
- First Funding: Initial investment (~$180k) from European angels in 2013, after demonstrating clear user traction and platform scalability. Major VC money arrived after the company was already serving thousands of users.
- AI Role: Preply automated tutor-student matching and onboarding using AI-powered workflows. Operations ran lean, enabling the team to scale regionally before expanding globally.
4. Flutterwave (Nigeria)
- Founded: 2016
- First Funding: Seed capital secured locally in Lagos and from global African diaspora investors after launching the platform and gaining merchant adoption (late 2016-2017). US/international VCs arrived at later stages.
- AI Role: Leveraged AI for fraud detection, onboarding, and support—letting the team provide enterprise-grade payments with just a handful of technical staff.
5. Lovable (Amsterdam, Netherlands)
- Founded: 2022
- First Funding: Received initial European angel support in 2023, months after reaching thousands of active users and piloting their application in multiple markets. US investors have remained prospective, not active.
- AI Role: Developed core relationship intelligence using generative models; prototypes and front-end deployments were built by core founders, not external engineers.
6. Voicery (Ukraine)
- Founded: 2017
- First Funding: European seed money awarded only after voice AI products achieved market traction in local B2B and European consumer sectors.
- AI Role: Created natural-sounding voices using deep learning, enabling rapid expansion to clients in multiple geographies without upfront US or “big” capital.
7. Paystack (Nigeria)
- Founded: 2015
- First Funding: Seed funding (local and Y Combinator) came after MVP launch and market adoption; all large US/international funding arrived only after strong product validation.
- AI Role: Used AI and automation in payment processing and compliance, expanding their service reach without excessive headcount or capital.
Why the Funding Pattern Matters
Across these examples, the message is clear:
- Funding came after traction. Early investors (often angels or regional funds) waited for real user engagement, not just a clever idea. Leveraging AI, they didn’t need a big team or capital.
- Lean teams, enabled by AI, proved the concept before capital. Founders used AI coding, operational automation, and agent-based platforms to build fundamentally sound businesses.
- US-focused VCs were late to the table. These startups didn’t depend on Silicon Valley’s money or networks to break out; by the time US investors noticed, the companies were already scaling.
The Effects: Lower Barriers, Wider Innovation
AI development tools and agents have removed traditional constraints:
- Building software is cheaper, faster, and accessible to founders everywhere.
- Operations can run on minimal headcount. AI agents now handle everything from user onboarding to troubleshooting, analytics, and marketing.
- Local investors, even with conservative attitudes, are more willing to invest after product/market fit is proven—shifting the power dynamic away from US-centric gatekeepers.
- Global collaboration is automatic. Distributed teams in Georgia, Tallinn, Lagos, or Buenos Aires work together without physical or cultural bottlenecks.
Even More Examples
Wise (London/Estonia) Early traction and revenue before significant rounds; initial backing from founders and European angels after product-market fit.
UiPath (Romania) Bootstrapped and built advanced automation products across Europe and Asia before raising VC funding, only turning to US capital after global scale was underway.
Hotjar (Malta) Launched as a lean, founder-led team relying on automated analytics and feedback, securing funding after large user adoption.
Algolia (France) Built core search AI, demonstrating traction across Europe before seeking larger investment.
What Does This Mean for Founders and Investors?
The barriers to global competition are lower than ever. The old story, US VCs writing big early checks, then dictating market winners, no longer applies in a world where teams with vision and AI tools can reach thousands (or millions) of users before raising any significant funds. For founders outside the US:
- Build your product with lean resources.
- Use AI coding and agents to automate wherever possible—development, sales, support, even compliance.
- Focus on traction in your local and adjacent markets; prove product-market fit before seeking late-stage capital.
- Raise money thoughtfully, with better leverage and terms, after you know your users and workflow.
For investors:
- Look beyond US borders for transformative startups.
- Value founders who make it work before the money arrives; they already know how to scale intelligently.
- Accept new definitions of product excellence—grounded in local needs, global ambitions, and AI-powered efficiency.
The Innovation Map Has Flipped
Bret’s insight from Georgia is a wake-up call: the greatest innovation wave is coming from places most “experts” never expected. Young founders in developing economies are not simply catching up; they are inventing new models—faster, smarter, and often more inclusive than their predecessors. AI deployment and intelligent automation let them leapfrog constraints that once seemed unassailable.
The next software unicorn might already be in Lagos, Tbilisi, Kyiv, or Santiago and they won’t need Silicon Valley to get there.