tag:jeffreypaine.com,2013:/posts Jeff (Startup Whisperer) 2025-07-12T03:51:51Z Jeffrey Paine tag:jeffreypaine.com,2013:Post/2210225 2025-07-12T03:51:50Z 2025-07-12T03:51:51Z The Startup's Guide to Global IT Markets: Navigating Real Opportunities in the US, Europe, and Southeast Asia

The global IT spending landscape presents both tremendous opportunities and significant challenges for startups seeking to establish themselves in enterprise markets. While the total addressable market appears massive at first glance, the reality for emerging companies is far more nuanced, shaped by regional purchasing behaviors, cultural preferences, and established vendor relationships that can either accelerate or hinder startup growth.

The Global IT Spending Landscape: Size and Scale

The worldwide IT market represents one of the largest and fastest-growing sectors in the global economy. In 2025, global IT spending is projected to reach $5.61 trillion, with significant regional variations that directly impact startup opportunities1. The three major regions present distinctly different market characteristics and growth trajectories.

Total IT Market Size Comparison Across US Europe and Southeast Asia for 2025
Total IT Market Size Comparison Across US, Europe, and Southeast Asia for 2025

The United States dominates the global IT spending landscape with a forecasted $1.9 trillion market in 2025, representing nearly 35% of worldwide IT expenditure. This massive scale reflects both the maturity of American enterprise technology adoption and the substantial budgets allocated to digital transformation initiatives. European IT spending, while substantial at $1.28 trillion in 2025, demonstrates more conservative growth patterns with established enterprises showing measured adoption of new technologies. Southeast Asia, though representing the smallest absolute market at $55.1 billion, exhibits the highest growth potential with a compound annual growth rate of 9.1%.

Regional Market Dynamics and Characteristics

United States: Innovation-Friendly but Highly Competitive

The American market offers the most favorable environment for startup penetration, characterised by high enterprise spending per employee ($916 annually) and a cultural openness to innovative solutions. US enterprises demonstrate greater willingness to engage with unproven vendors when the technology offers compelling advantages. However, this market also presents intense competition, with over 50,000 active startups competing for attention.

American enterprises allocate substantial budgets to software, with enterprise software spending projected to reach $159.39 billion in 2025. The venture capital ecosystem provides robust support, with $209 billion invested in 2024, creating a funding-rich environment that enables startups to compete effectively.

Europe: Conservative Procurement with Established Vendor Bias

European enterprises exhibit more conservative purchasing behaviours, with a strong preference for established vendors and proven solutions. The enterprise software market of $70.6 billion in 2025, while substantial, requires startups to navigate complex procurement processes that often favor incumbent suppliers. European buyers demonstrate lower per-employee spending ($168) compared to their American counterparts, reflecting more cautious technology investment approaches.

The challenge for startups in Europe extends beyond market size to cultural procurement preferences. European organizations typically require extensive validation and proof of concept before considering new vendors, particularly those without established track records. This creates significant barriers to entry for emerging companies seeking to establish market presence.

Southeast Asia: Emerging Opportunities with Growing Digital Adoption

Southeast Asia presents a unique opportunity for startups, despite its smaller absolute market size. The region's enterprise software market of $4 billion in 2025 reflects emerging digital transformation initiatives and increasing acceptance of innovative solutions. With only $11 per employee spent on enterprise software, the market demonstrates significant upside potential as digital adoption accelerates.

Regional characteristics favor startup penetration, with 69.3 billion in technology investments from global majors demonstrating growing confidence in the market. The startup ecosystem, while smaller with approximately 4,000 companies, faces less saturated competition compared to mature markets.

Startup Total Addressable Market Analysis

Understanding the realistic market opportunity requires moving beyond total IT spending figures to analyse what portion of these markets is genuinely accessible to startups. Traditional market analysis often overestimates startup opportunities by failing to account for established vendor relationships, procurement biases, and enterprise risk aversion.

Startup Total Addressable Market comparison showing conservative and optimistic scenarios across three regions
Startup Total Addressable Market comparison showing conservative and optimistic scenarios across three regions

Conservative estimates suggest startups can realistically target 10% of the US IT market, 5% of the European market, and 15% of the Southeast Asian market.

These percentages reflect the varying degrees of market openness to new vendors and cultural acceptance of startup solutions. Under conservative scenarios, this translates to addressable markets of $190 billion (US), $64 billion (Europe), and $8.3 billion (Southeast Asia).

Optimistic projections, assuming successful market penetration and cultural shifts toward startup adoption, increase these figures to $380 billion (US), $154 billion (Europe), and $13.8 billion (Southeast Asia). These optimistic scenarios require startups to overcome significant cultural and procedural barriers that currently limit market access.

Cultural and Procurement Challenges

Enterprise Risk Aversion and Vendor Selection

Modern B2B purchasing decisions involve complex stakeholder groups, with 77% of buyers rating their procurement experience as extremely challenging. This complexity particularly disadvantages startups, as procurement teams often exhibit unconscious bias toward familiar suppliers and established vendors.

The incumbent supplier bias represents a significant barrier for startups across all regions. Procurement professionals frequently favor existing relationships due to loss aversion and risk management concerns. This bias becomes particularly pronounced in Europe, where conservative procurement practices and established vendor preferences create higher barriers to entry.

Regional Purchasing Behaviour Variations

American enterprises demonstrate greater willingness to engage with innovative startups, particularly when solutions offer clear competitive advantages. The cultural acceptance of risk-taking and innovation creates more opportunities for unproven vendors to gain initial customer traction.

European procurement practices emphasise stability and proven performance over innovation potential. The preference for established vendors creates longer sales cycles and higher customer acquisition costs for startups. Additionally, European enterprises often require extensive compliance documentation and regulatory adherence that can overwhelm resource-constrained startups.

Southeast Asian markets show increasing openness to startup solutions, driven by rapid digital transformation initiatives and less entrenched vendor relationships. However, limited local funding and smaller average deal sizes can constrain growth potential for startups in this region.

Market Attractiveness Assessment for Startups

Radar chart comparing startup market attractiveness across multiple factors for US Europe and Southeast Asia
Radar chart comparing startup market attractiveness across multiple factors for US, Europe, and Southeast Asia

A comprehensive evaluation of startup market attractiveness reveals significant variations across regions when considering multiple factors beyond simple market size. The United States scores highest overall (8.8/10) due to exceptional market size, startup-friendly culture, and abundant funding availability.

However, intense competition and high customer acquisition costs present ongoing challenges.

Europe's moderate attractiveness score (6.8/10) reflects substantial market size offset by conservative procurement practices and limited startup friendliness. The region's established vendor preferences and complex regulatory environment create additional barriers for emerging companies.

Southeast Asia's balanced score (6.0/10) demonstrates the region's potential despite smaller absolute market size. High growth rates and emerging digital adoption create opportunities, though limited funding availability and smaller enterprise budgets constrain immediate potential.

Strategic Implications for Startups

Market Entry Strategy Considerations

Startups should approach these regional markets with differentiated strategies reflecting local characteristics and constraints. In the United States, focus on rapid scaling and competitive differentiation to capture market share before competitors respond. The abundant venture capital and cultural acceptance of innovation support aggressive growth strategies.

European market entry requires patience and methodical relationship building. Startups should invest in compliance capabilities, case study development, and partnership strategies with established system integrators. The longer sales cycles necessitate sufficient funding runway and realistic growth expectations.

Southeast Asian markets offer opportunities for startups willing to adapt solutions for emerging market requirements. Lower price points and simplified implementations can create competitive advantages, though startups must balance reduced margins against growth potential.

Funding and Growth Considerations

The dramatic differences in venture capital availability across regions significantly impact startup viability. With $209 billion in US venture funding compared to $18 billion in Europe and $1.6 billion in Southeast Asia, American startups enjoy substantial funding advantages.

This disparity affects everything from product development timelines to customer acquisition strategies.

European startups face funding constraints that require more capital-efficient growth strategies and earlier focus on profitability. The limited venture capital ecosystem demands stronger unit economics and more conservative growth projections.

Southeast Asian startups must often rely on international funding sources or bootstrap growth through early revenue generation. The emerging venture capital ecosystem provides opportunities but cannot match the scale available in more mature markets.

Conclusion: Realistic Market Opportunities for Startups

The global IT spending market, while massive in aggregate, presents highly varied opportunities for startups depending on regional characteristics and cultural factors. The United States offers the largest addressable market and most startup-friendly environment, but also the most intense competition. Europe provides substantial market opportunity tempered by conservative procurement practices and established vendor preferences. Southeast Asia presents emerging opportunities with high growth potential but smaller absolute market size and limited funding availability.

Successful startup market entry requires understanding these regional nuances and developing strategies aligned with local purchasing behaviors and market dynamics. Rather than viewing the global IT market as uniformly accessible, startups must carefully evaluate regional characteristics, cultural preferences, and competitive landscapes to identify realistic growth opportunities and develop appropriate go-to-market strategies.

The real market size for startups is significantly smaller than total IT spending figures suggest, but substantial opportunities exist for companies that understand regional dynamics and adapt their approaches accordingly. Success requires matching startup capabilities with regional market characteristics, building appropriate funding strategies, and developing solutions that address specific regional requirements and preferences.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2205850 2025-06-25T02:23:14Z 2025-07-12T03:39:00Z The Rebels Who Code: How Cluely's Generation Is Leading the AI Revolution

The torch of technological rebellion is being passed—and it’s burning brighter than ever. What we’re witnessing today isn’t the corruption of Silicon Valley’s hacker culture, but its magnificent evolution. 

The idealistic builders who gave us Facebook and Twitter have paved the way for a new breed of rebels: entrepreneurs harnessing artificial intelligence to augment human potential, not just connect the world.

The Natural Progression: From Connection to Augmentation

The journey from Mark Zuckerberg’s Harvard dorm room to Roy Lee and Neel Shanmugam’s AI revolution was inevitable. While the social media generation taught us to connect minds across the globe, the AI generation is showing us how to amplify those minds’ power. Facebook, PayPal, and Twitter weren’t just companies—they were the infrastructure that made today’s AI revolution possible. Zuckerberg’s “Hacker Way” of rapid experimentation and boundary-pushing has become the playbook for today’s AI rebels.

Two Generations, One Mission: Breaking Barriers

The data tells a story of unprecedented acceleration. Where social media startups took 18–24 months to reach market, AI-native companies now do it in 6–12 months. Teams have shrunk from 15–25 to just 5–10, thanks to AI’s transformative efficiencies. This isn’t just about moving faster—it’s about fundamentally changing how innovation happens.

Redefining Rebellion: From “Move Fast” to “Think Instantly”

What critics call “cheating,” these visionaries call democratization. When Cluely’s founders say “we want to cheat on everything,” they’re not promoting dishonesty—they’re challenging systems that artificially limit human potential. Lee’s suspension from Columbia for creating Interview Coder wasn’t a setback; it was the catalyst for building a universal platform for AI-augmented performance. This is positive rebellion: breaking the right rules to unlock new possibilities.

The Democratization Revolution

AI is making innovation accessible to more people than ever before—74% of innovators say AI has broadened access to entrepreneurship. Gen Z founders, raised on technology, move fast, experiment freely, and scale globally from their bedrooms. They spot opportunities and create solutions that previous generations might never see.

AI-Powered Entrepreneurship: The Numbers Don’t Lie

Cluely’s meteoric rise illustrates this new paradigm. Within weeks of launch, it attracted 70,000 users and reached $3 million in annual recurring revenue—a pace unimaginable in the social media era. AI-native startups now achieve product-market fit in months, not years, and VC funding is following suit: Cluely secured $15 million in Series A to fuel this rapid growth.

Enterprise Validation and Viral Growth

Cluely isn’t just a consumer phenomenon—it’s already proving itself in enterprise settings, especially in sales, with rapid adoption and real business impact1. The company’s growth team, each with personal audiences over 100,000 followers, exemplifies how the AI generation blends technical prowess with modern marketing.

Positive Disruption: Amplifying, Not Replacing, Human Intelligence

This generation’s rebellion serves a different purpose. While their predecessors connected people and information, the AI generation is focused on amplifying individual human capability. AI isn’t about replacing intelligence—it’s about enabling people to perform at levels never before possible.

A Cultural Shift: Creative Rebels with a Cause

Today’s entrepreneurs are “positive deviants”—rebels with a cause, willing to embrace controversy to advance human potential. Their viral campaigns and user-generated content strategies aren’t just for attention; they’re about demonstrating AI’s real-world impact.

A Utopian Vision: Empowerment at Scale

The future these companies are building isn’t dystopian—it’s utopian. They envision a world where everyone becomes a creator, where technical barriers disappear, and where AI personal assistants are available for every task. Just as Facebook democratized publishing and Twitter democratized broadcasting, the AI generation is democratizing expertise itself.

An Ecosystem of Acceleration

The success of AI-native startups creates a positive feedback loop, inspiring more entrepreneurs and attracting greater investment. The result: an ecosystem where innovation accelerates and barriers to entry continue to fall.

Conclusion: The Spirit of Rebellion Lives On

The entrepreneurs behind Cluely and similar companies aren’t destroying hacker culture—they’re fulfilling its highest aspirations. They represent the evolution from connecting minds to amplifying minds, from breaking things to building intelligence. Their rebellion isn’t about chaos, but about progress: breaking barriers so the rest of us can achieve more than we ever thought possible.

The AI revolution isn’t happening to us—it’s being built by a new generation of audacious entrepreneurs. The rebels are coding, the barriers are falling, and the future is being written in real-time. This is what progress looks like when “impossible” is just the starting line.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2205845 2025-06-23T13:32:22Z 2025-06-25T02:19:13Z The Base44 Phenomenon: How a Solo Founder's $80 Million Exit Redefined AI-Powered Development

In June 2025, the tech world witnessed a landmark event: Wix, the Israeli website-building powerhouse, acquired Base44 for $80 million in cash. While startup acquisitions are nothing new, this deal stands out for what it represents—a bold leap into the future of software development, where AI-driven "vibe coding" empowers solo entrepreneurs to build companies of unprecedented scale and impact.

From Military Intelligence to Startup Stardom

At the heart of this story is Maor Shlomo, a 31-year-old Israeli entrepreneur whose journey began in the elite Unit 8200 of the Israeli Intelligence Corps. There, he honed his skills in data science and artificial intelligence, earning accolades for his innovative data mining systems. His entrepreneurial path took off with Explorium, a data discovery platform that raised $127 million and earned him a Forbes 30 Under 30 nod.

But it was a personal experience during reserve duty after the October 7, 2023 attacks that sparked the idea for Base44. Tasked with helping a nonprofit build simple internal tools, Shlomo was shocked by the high costs and lengthy timelines quoted by traditional agencies. This frustration led him to envision a platform where anyone could create custom applications using conversational AI—no coding required.

Vibe Coding: The Next Software Revolution

Vibe coding, a term popularized by computer scientist Andrej Karpathy in early 2025, marks a paradigm shift in how software is built. Instead of painstakingly writing code, developers (and even non-developers) describe their goals in plain language. AI then handles the technical implementation, iterating based on user feedback. This approach transforms the developer’s role from coder to creative director, guiding and refining AI-generated solutions.

The no-code market has exploded alongside this trend, growing from $28.11 billion in 2024 to $35.86 billion in 2025, fueled by the demand for rapid digital transformation and AI integration.

Base44: All-in-One, AI-Powered App Creation

What set Base44 apart in the crowded no-code landscape was its all-in-one approach. Unlike platforms that require a patchwork of third-party integrations, Base44 offered a seamless conversational interface. Users simply described what they wanted—be it a task manager, a social app, or a complex business system—and the AI did the rest, building everything from the user interface to backend logic and database structures.

This frictionless experience resonated: within six months of its early 2024 launch, Base44 amassed over 250,000 users and was generating $189,000 in monthly profit, far outpacing initial forecasts. Its user base ranged from solo creators to businesses seeking affordable, custom solutions without the traditional development overhead.

Strategic Partnerships and Viral Growth

Base44’s credibility was further cemented by partnerships with major Israeli tech firms like eToro and Similarweb. Shlomo’s transparent “building in public” approach—sharing milestones and even operational costs on social media—helped fuel viral growth and community engagement.

Why Wix Bought In

For Wix, the acquisition of Base44 is a strategic move to expand beyond website building into the broader realm of AI-powered digital creation. The deal brings not only cutting-edge vibe coding technology and a fast-growing user base, but also Shlomo and his team, with $25 million earmarked for employee retention1. Base44 will remain a distinct business unit, leveraging Wix’s scale while maintaining its innovative edge.

A Shifting Competitive Landscape

The vibe coding space is heating up, with competitors like Lovable, Windsurf, Cursor, and Replit all vying for dominance. Cursor leads with 7 million developers, while GitHub Copilot remains the industry standard for AI-assisted coding. Base44’s unique focus on natural language interaction and its all-in-one architecture set it apart in this crowded field.

Implications: The Rise of the Solo Unicorn

Perhaps most striking is what this acquisition signals for solo entrepreneurship. While Base44 had grown to eight employees by the time of the deal, Shlomo operated as a solo founder for most of its journey. This “solo unicorn” phenomenon—enabled by AI tools that dramatically lower the barriers to building and scaling companies—may reshape the economics of startups and the very nature of software development as a profession.

Conclusion: A Pivotal Moment for AI and App Creation

The Base44 acquisition is more than a headline-grabbing exit. It marks a fundamental shift in how software is created and who gets to create it. As vibe coding and conversational AI interfaces mature, the power to build sophisticated applications is moving from the hands of a few to the many. For Wix, it’s a strategic leap into the future. For the broader industry, it’s validation that the next wave of digital innovation will be driven by intent, creativity, and AI—not just code.


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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2205799 2025-06-23T07:34:19Z 2025-06-25T02:14:52Z The AI Revolution: What Top Universities Are Building in 2024 (quick research paper analysis)

The artificial intelligence landscape is evolving at breakneck speed, and the world's leading research institutions are at the forefront of this transformation. After analyzing cutting-edge research from Stanford University, UC Berkeley, MIT, and Carnegie Mellon University, we've uncovered the most exciting trends shaping AI's future—and they might surprise you.

The Multimodal AI Takeover Is Real

Forget single-purpose AI systems. The biggest story of 2024 is the explosive growth of multimodal AI—systems that seamlessly blend text, images, audio, and video to create truly intelligent experiences. Stanford researchers are pioneering "Agent AI," interactive systems that don't just process information but take meaningful actions in both physical and virtual environments.

The numbers tell the story: the multimodal AI market is projected to skyrocket from $1.83 billion in 2024 to an astounding $42.38 billion by 2034. Gartner predicts that by 2027, 40% of all generative AI solutions will be multimodal—a massive leap from just 1% in 2023. This isn't just growth; it's a fundamental shift in how AI systems operate.

The Great Model Divide: Industry vs. Academia

Here's where things get interesting. While universities continue to produce groundbreaking research, industry has become the dominant force in frontier AI model development. In 2023, private companies created 51 notable AI models compared to academia's 15. The reason? Money. Training costs have reached unprecedented heights, with OpenAI's GPT-4 estimated at $78 million and Google's Gemini Ultra at a staggering $191 million.

But there's a fascinating counter-trend emerging: small language models that punch above their weight class. These efficient alternatives deliver comparable performance while being cost-effective and capable of running on everyday devices—a game-changer for accessibility and sustainability.

Computer Vision Gets a 3D Upgrade

Stanford's Computational Imaging Lab has been particularly busy, with 9 papers accepted to CVPR 2025 and 5 to NeurIPS 2024. The focus has shifted to real-time object detection using advanced YOLO architectures and 3D vision and reconstruction technologies. Perhaps most excitingly, researchers have achieved breakthroughs in open-vocabulary object detection, enabling AI to identify objects it has never seen before.

Robotics Meets Real-World Intelligence

MIT's approach to robotics is revolutionary. Their Heterogeneous Pretrained Transformers (HPT) adapts large language model training methods to create universally adaptable robots. Meanwhile, Berkeley researchers are pushing the boundaries of interactive imitation learning, exploring how off-policy reinforcement learning can outperform traditional expert-based approaches.

The robotics-AI integration market is projected to reach $35.3 billion by 2026, reflecting the massive commercial potential of these advances.

The Safety-First Movement

Perhaps the most sobering trend is the unprecedented focus on AI safety and risk assessment. Researchers have identified 314 unique AI risk categories, organized into System & Operational Risks, Content Safety Risks, Societal Risks, and Legal & Rights Risks. MIT has created the world's first comprehensive database cataloging over 700 AI risks—a stark reminder that with great power comes great responsibility.

Meet the Visionaries Behind the Revolution

The human faces behind these technological leaps are as impressive as their work:

Stanford's Christopher Manning, the Thomas M. Siebel Professor and Director of Stanford AI Lab, continues to lead groundbreaking research in natural language processing and deep learning. His colleague Fei-Fei Li, Co-Director of Stanford HAI, made headlines in 2024 by raising $230 million for her startup World Labs while maintaining her academic leadership.

At UC Berkeley, Pieter Abbeel directs the Berkeley Robot Learning Lab and co-directs the BAIR Lab, pushing the boundaries of reinforcement learning and robotics. MIT's Daniela Rus, the first woman to direct MIT CSAIL, leads over 1,000 researchers in shaping the future of AI and robotics.

Carnegie Mellon's Tom Mitchell, who founded the university's Machine Learning Department, continues to influence the field as a visiting scholar at Stanford.

What This Means for You

These aren't just academic exercises—they're the building blocks of tomorrow's technology. The shift toward multimodal AI means your next virtual assistant might understand your gestures, tone of voice, and facial expressions, not just your words. The focus on smaller, efficient models suggests AI capabilities will soon be available on your smartphone without requiring cloud connectivity.

The emphasis on safety frameworks indicates that researchers are taking seriously the societal implications of their work. As AI systems become more capable, the academic community is proactively addressing potential risks rather than reacting to them after the fact.

The Road Ahead

Looking forward, several key developments are on the horizon:

Cost Efficiency Revolution: The emphasis on smaller, more efficient models reflects growing concerns about the environmental and economic sustainability of current AI scaling approaches.

Industry-Academia Convergence: The dominance of industry in frontier model development is driving new collaboration models between universities and private companies.

Real-World Integration: The focus on multimodal systems and robotics integration suggests AI will soon move beyond screen-based interactions to become embedded in our physical environment.

The AI revolution isn't coming—it's here. And based on what the world's brightest minds are building in their labs, the next few years promise to be nothing short of extraordinary.


This analysis is based on quick data scan of research publications and developments from Stanford University, UC Berkeley, MIT, and Carnegie Mellon University throughout 2024, representing the latest trends in artificial intelligence and machine learning research.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2205222 2025-06-21T02:05:00Z 2025-06-21T02:05:00Z Why U.S. AI Startups Need an Overseas Game Plan Sooner Than Ever

Going Global from Day One

“In AI, geography is optional—​but timing isn’t.”

If you’ve just closed your pre-seed, seed or Series A and the roadmap on your wall still shows “U.S. first → rest-of-world later,” grab a fresh marker. The ground under American AI startups is shifting fast, and the winners will be the teams that treat international expansion as a Day-1 feature, not a post-IPO nice-to-have.


1. The Home-Turf Reality Check

  • 57 % of global AI VC dollars already land in the U.S.—but deal count is at a five-year low.

  • Big Tech’s GPU budgets make nine-figure raises look tiny.

  • Talent demand is on track to outstrip supply by up to 700 k jobs in two years.

Translation: More money is chasing fewer startups, and the bar to stand out keeps rising.


2. Across the Pond (and Pacific) Lies the Growth

Region  2025 Market Size      2030 Forecast      CAGR
Asia-Pacific  $32.9 B      ≈ $380 B      43 %
Europe  $21.2 B      ≈ $180 B      33 %
North America  $51.6 B      ≈ $250 B      30 %

APAC alone could add 10× more new AI dollars than the U.S. over the next five to eight years. That’s green-field demand waiting for the first mover who shows up with a localized product.


3. Cost & Talent: The Secret Weapons Abroad

  • Senior AI engineer: ~$150/hr in SF vs. ~$70/hr in Bangalore or Ho Chi Minh City.

  • Benefits load: 30-40 % in the U.S.; often half that in Southeast Asia.

  • Cloud/energy: Singapore and certain Gulf states offer AI-friendly power prices + GPU credits to attract R&D hubs.

Lower burn unlocks longer runway—and the chance to reinvest savings into GTM.


4. Regulation Doesn’t Have to Be a Roadblock

U.S. → uncertain federal AI bill
EU → AI Act (18 mo compliance; $$$)
Singapore → “light-touch” sandbox (≈3 mo; <$ 100k)
UAE/KSA → “green-lane” visas + cash rebates for AI labs

Smart founders pick one high-value, low-red-tape jurisdiction as their international beachhead, then expand outward once playbooks are repeatable.


5. Founder Checklist: Launching Global Earlier

  1. Heat-map your inbound sign-ups by country—users may be telling you where to go first.

  2. Hire a fractional local operator (or advisor) before you sign leases or incorporate.

  3. Localize pricing & support with AI-powered translation; don’t over-engineer the product.

  4. Open a dev or data-labeling pod in a talent-rich, cost-effective city—think Toronto, Warsaw, Manila.

  5. Time your fundraising narrative around “international traction” to stand out in crowded U.S. pitch rooms.


6. Quick Case Snippets

  • OpenAI: London → Dublin → Singapore offices within 12 months to capture talent & government partnerships.

  • Cohere: CEO splits weeks between Toronto and London; London team expected to double in 2025.

  • Recursive (Stealth LLM): APAC + Gulf build-outs before even launching a U.S. sales team.

Proof that even well-funded players see global presence as a moat, not a capstone.


7. Parting Thought

Domestic-first made sense when cloud costs were low, Series B rounds were plentiful, and regulatory headwinds were mild. In 2025, the calculus flipped. International expansion is now cheaper, talent-richer, and strategically safer than waiting for the U.S. market to settle.

So redraw that roadmap. Because in AI, the map is the moat.



🚀 Like this post? Share it with a founder who’s still hunting for their Delaware C-corp papers and remind them: the next great AI unicorn might be born in San Francisco—but it will grow up everywhere. If they need references on foreign venture funds who can help you access markets, let me know.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2197128 2025-05-13T07:30:15Z 2025-05-13T07:37:07Z Funding or Footprint First? How Overseas Startups Succeed in the US

For founders based outside the United States, deciding whether to raise capital from American venture capitalists before or after entering the US market is a pivotal and also a costly strategic decision. The optimal approach depends on your industry, market readiness, and operational objectives. Drawing on recent data that we analysed, here’s a comprehensive look at the factors that should guide your choice.

Key Data on Overseas Startups Raising in the US

A study of 153 overseas startups that raised capital in the US reveals several notable trends. On average, these companies secure their first US investment 4.3 years after founding. Nearly 45% obtain US funding within two to five years, while only about 13% do so in their first year. Interestingly, startups founded after 2015 reach US investors more quickly, with those established in 2020 averaging just 1.6 years to their first US investment (due to 2021 bull run).

Patterns: US Hiring vs. Fundraising

The sequence of US hiring and fundraising varies by industry and can influence the scale of capital raised. About 30% of companies hire US employees before securing US funding, a pattern most common in healthcare, biotech, and payments sectors, typically resulting in lower initial capital raised. Roughly 35% raise US funding before making local hires, a trend prevalent in fintech, software, and IT, and these companies tend to secure larger funding rounds. A smaller group, around 14%, hires and raises in the same year, while a niche 3% raise US capital without hiring locally, often in remote-first or specialized sectors. The data suggests that startups raising before hiring in the US are more likely to secure larger investment rounds.

Industry and Geography: What Shapes the Sequence

Industry and geographic origin play a significant role in shaping US entry strategies. Life sciences and regulated sectors, such as healthcare and biotech, often prioritize hiring US talent before fundraising. This approach is driven by the need for local expertise, regulatory navigation, and credibility with investors and customers. In contrast, digital and software startups-especially in fintech and enterprise IT-frequently raise US capital first, leveraging product traction and global relevance to attract investors before building a local team. Startups from Southeast Asia and Australasia are more likely to establish a US presence before fundraising, signaling commitment and reducing perceived execution risk for American investors.

Strategic Implications for Founders

Fundraising Before US Expansion

This approach is best suited for SaaS, fintech, and enterprise software platforms with strong product-market fit and global appeal. Securing US funding before establishing local operations preserves capital for growth, demonstrates capital efficiency, and allows startups to test US market demand before making significant investments. Typically, these companies secure US investment and then set up US operations within two to three years.

Hiring Before Fundraising

For regulated or capital-intensive sectors like healthcare, biotech, or financial services, hiring US talent or leadership before fundraising is often essential. Building a local team enhances credibility, accelerates regulatory approvals, and signals long-term commitment to the market. The typical path involves recruiting key US personnel, setting up local operations, and then approaching US investors.

Simultaneous Approach

Some startups, particularly those with ample resources or operating in highly competitive sectors, pursue parallel strategies-raising funds and hiring in the US simultaneously. While this maximizes speed and market learning, it requires greater capital and operational bandwidth.

Best Practices for US Market Entry

Successful US market entry requires more than just capital or a local presence. Deep market research is essential; founders should avoid assuming that US buyers behave like those in their home markets and must localize their value proposition accordingly. Strategic partnerships with established US players can accelerate credibility and market access, sometimes reducing the need for immediate local hires. Phased rollouts-starting in select regions-allow startups to test and adapt before scaling nationally. For regulated industries, early legal and compliance planning is crucial to avoid costly delays. While many US investors still prefer local teams, especially at early stages, there is a growing acceptance of remote-first models and global teams.

Practical Guidance by Sector

For enterprise software and fintech startups, focus on demonstrating product traction and global relevance. It is often possible to raise from US investors before hiring locally, but you should have a clear plan for US expansion. In healthcare and biotech, prioritize hiring or partnering in the US before fundraising, as local presence is often a prerequisite for regulatory and investor confidence. Regardless of your sector, align your US hiring and fundraising strategies with your operational capacity and market readiness. Investors seek both commitment and capital efficiency.

“There is no universal rule, but your US hiring strategy should align with your market readiness, funding strategy, and operational capacity. Investors want to see commitment, but also capital efficiency and product clarity.”

Bottom Line

There is no one-size-fits-all answer to whether overseas startups should raise capital before or after entering the US market. The optimal sequence depends on your industry, business model, and market strategy. For most SaaS and digital startups, raising capital before building a US team is often preferable-but this usually requires exceptional traction that signals the potential for a 20x or greater return. In regulated or high-touch sectors, establishing a US presence first is crucial to unlocking investor interest and market access. Many successful startups blend both approaches, adapting as they learn from the market and investor feedback. Ultimately, careful planning, deep market understanding, and a tailored strategy are essential for a successful US entry and fundraising journey.


By Jeffrey Paine and Annette Wei



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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2194452 2025-05-02T08:12:14Z 2025-05-02T08:12:14Z The Future of AI Innovation: A Data-Driven Analysis of Research Trends and Startup Opportunities 2025-2027

AI is entering a transformative phase, with research and market data revealing both mainstream growth and emerging frontiers. Based on an extensive analysis of over 20,000 research papers from NEURIPS and detailed startup activity, this post highlights the key trends and commercial gaps that will define AI innovation through 2027.

Mainstream AI Evolution: 2025 Forecast

Enterprise AI Infrastructure & Optimization

  • Research Activity: 2,405 papers

  • Market Context: The AI infrastructure market is projected to reach between $60 billion and $82 billion in 2025, with forecasts of continued double-digit growth as organizations prioritize AI integration for operational efficiency and competitive advantage.

  • Key Opportunities:

    • Automation for enterprise-scale AI deployment

    • Resource and cost optimization for large language models (LLMs)

    • Workflow management and orchestration tools

Despite widespread belief in AI’s benefits, only a small fraction of organizations have fully implemented enterprise AI, signaling significant room for expansion and innovation.

AI Safety and Governance

  • Research Volume: 1,985 papers

  • Market Dynamics: Regulatory scrutiny is intensifying globally, with governments introducing frameworks for transparency, accountability, and risk management in AI systems.

  • Growth Areas:

    • Compliance and audit platforms

    • Bias detection and mitigation systems

    • Privacy-preserving AI solutions

    • Safety monitoring and risk assessment tools

The shift toward responsible AI is driving demand for solutions that ensure compliance and address ethical concerns, especially as regulations become more complex.

Generative AI 2.0

  • Research Focus: 1,594 papers

  • Market Activity: The generative AI market is expected to exceed $22 billion globally by 2025, with North America leading in revenue share.

  • Emerging Opportunities:

    • Industry-specific generative AI solutions

    • Controlled and reliable generation systems

    • Multi-modal and creative AI platforms

Generative AI is rapidly moving from general-purpose applications to specialized, vertical-focused tools that address enterprise needs and regulatory requirements.

Emerging Niche Subsectors

Fastest Growing Research Areas

Subsector  Growth Rate     Research Volume     Commercial Gap    Example Applications
Neuro-symbolic AI  600%     27 papers      High     Explainable AI, reasoning
Few-shot Learning  191%     339 papers      High     Efficient learning, enterprise
Privacy-Preserving AI  175%     72 papers      High     Regulated industries

These areas are seeing rapid research growth but remain under-commercialized, representing high-potential opportunities for new ventures.

Emerging Hybrid Fields

  • Self-supervised + Unsupervised Learning: 31 recent papers, no commercial implementations, significant market gap

  • Federated + Privacy-Preserving Systems: 22 papers, rising regulatory demand, strong commercial potential

  • Meta-learning + Few-shot Systems: 18 papers, promising for enterprise automation

Hybrid approaches are gaining traction in research but have yet to see widespread commercial adoption, highlighting a fertile ground for startups.

Market Gap Analysis

Several foundational AI fields show a pronounced gap between research activity and commercial presence:

Area  Research Papers      Companies      Gap Score
Unsupervised Learning  269       0       269.0
Self-supervised Learning  261       0       261.0
Few-shot Learning  203       0       203.0

This gap suggests that while academic interest is high, practical solutions are lagging, creating strong opportunities for innovation and market entry.

Future Predictions: 2025-2027

Highest Potential Areas

  • Enterprise AI Infrastructure: Demand for scalable, cost-effective, and reliable deployment solutions will continue to surge as organizations increase AI adoption and spending.

  • AI Safety & Governance: Regulatory pressures and compliance needs will drive adoption of safety, audit, and risk management platforms.

  • Specialized Industry Solutions: Custom AI applications tailored to specific sectors (healthcare, finance, manufacturing) will become a major growth driver.

Strong Potential Areas

  • Healthcare AI: Clinical decision support, medical imaging, drug discovery, and workflow optimization

  • Multimodal Systems: Integration of text, image, and sensor data for advanced applications

  • Edge AI Solutions: On-device optimization, edge-cloud hybrid systems, and IoT integration

Emerging Areas

  • Specialized LLMs: Domain-specific language models for enterprise and industry

  • Autonomous Systems: Industrial automation, robotics, and decision systems

  • Generative AI 2.0: Controlled, reliable, and industry-focused generative AI

Research-to-Market Timeline

There is typically a 1-2 year lag between peaks in research activity and commercial implementation. Current research trends-especially in neuro-symbolic AI and privacy-preserving systems-are poised to become viable startup opportunities within the 2025-2027 window.

Conclusion

The AI landscape is shifting from general-purpose platforms to highly specialized, industry-focused solutions. The greatest opportunities lie where research is robust but market saturation remains low, particularly in enterprise infrastructure, AI safety, and sector-specific applications. Emerging hybrid fields and niche subsectors with large research-to-market gaps are especially promising for innovators and startups. As AI adoption accelerates and investment strategies mature, the next wave of AI innovation will be led by those who can bridge the gap between cutting-edge research and practical, scalable solutions.

Methodology Note:
This analysis is based on a dataset of 20,629 research papers (2020-2024) from NEURIPS, data on 952 AI companies, and growth analysis across 26 technical domains. Funding data from a limited set of startups was excluded in favor of broader market and industry statistics.


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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2193501 2025-04-28T09:22:29Z 2025-04-29T08:13:55Z The DNA of Modern Tech Founders: A Data-Driven Analysis of 137 Successful Entrepreneurs
The tech entrepreneurship landscape is evolving—and our deep dive into 137 founders’ LinkedIn profiles reveals a new archetype of today’s innovators. From elite alma maters to unexpected career paths, here are eight data-driven insights reshaping what it takes to launch and scale groundbreaking ventures.

1. Stanford leads: 37 founders (27%) earned degrees there—far outpacing any other institution. Top contenders: MIT follows with 13 alumni (9.5%), while Berkeley and Harvard tie at 8 each.
This “Stanford effect” underscores the power of its ecosystem in spawning high-impact founders.

2. The Technical Foundation
CS prevalence: 63 founders (46%) majored in Computer Science.
Tech vs. business: Technical degrees outnumber MBAs by 3-to-1, and over 90% hold at least one STEM qualification.
Modern entrepreneurship demands deep technical skills—business degrees alone won’t cut it.

3. The Path to Founding
7.8 years to first venture (median 6 years).
Founder experience: 90.5% have launched at least one company.
Role spotlight: Co-founder is the most common title (33 profiles).
Contrary to the “launch straight out of college” myth, successful founders invest significant time gaining expertise.

4. Geographic Concentration
U.S. dominance: 127 founders (93%) are stateside.
Hub power: San Francisco Bay Area claims 51 founders (37%), with New York a distant second (10).
Despite remote work’s rise, proximity to top tech clusters remains critical.

5. Network Size Paradox
Median followers: 7,511 on LinkedIn.
Wild range: From 313 to 2.7 million followers, yet 75% fall below 27,000.
Building a unicorn doesn’t require a massive social media presence—just meaningful connections.

6. Career Transition Patterns
Non-traditional paths: 71 founders rose outside big tech or academia.
Few big-tech veterans: Only 10 founders came directly from major tech firms.
Academic bridge: Many transition from research roles rather than corporate ones.
Diverse career journeys fuel fresh perspectives—and break the mold of “big tech first.”

7. Industry Focus
Healthcare & biotech: Leading companies include Hippocratic AI and Xaira Therapeutics.
AI/ML infrastructure: Anysphere, Perplexity, and CoreWeave stand out.
Enterprise solutions: Wiz and other B2B platforms dominate.
Deep tech—especially in health and infrastructure—drives the next wave of innovation.

8. Language Skills
Multilingual edge: English (33 mentions), Spanish (14), French (10), Hindi and German (6 each).
Global communication skills hint at cross-border ambitions and diverse market reach.

The Modern Founder Archetype: 
Deeply technical, patient builders who average 6–8 years of experience, cluster in major hubs, and tackle high-stakes domains—from biotech to enterprise AI.

Looking Ahead: Technical depth trumps pure business training, physical hubs still matter, and social media clout is optional. Expect the next big breakthroughs from seasoned experts with global mindsets, not overnight influencers.


Stay tuned for more data-driven insights on the people shaping the future of technology.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2189705 2025-04-11T13:02:13Z 2025-04-11T13:02:13Z Predicting Success in AI Startups: A Data-Driven Investment Analysis Part 3 - 2024 Vintage
Our machine learning approach to identify high-potential AI startups has yielded exceptional results yet again but much fine-tuning, significantly outperforming industry benchmarks and validating our investment methodology.

Project Framework

We applied our established machine learning methodology to identify promising AI ventures, maintaining consistency with our previous analysis. Our approach incorporated:

- Six predictive variables: Industries, Company Description, Founder Biography, Founder Gender, Location, and Educational Background
- A dual-model ensemble combining Random Forest and XGBoost algorithms
- Advanced text vectorization for unstructured data

Portfolio Performance

Our model-selected portfolio of 15 companies founded in 2024-2025 demonstrates remarkable performance:

- 40% Success Rate: 6 companies have already achieved significant success
- 86.67% Projected Success Rate: Including companies currently "on track"
- 5.43x Outperformance: Compared to the industry baseline of 7.37% (note: real world constrains have not been factored)

Geographic Distribution and Success Patterns

Our portfolio shows strategic geographic diversity while maintaining concentration in key tech hubs:

- San Francisco Bay Area: 7 companies (4 successful, 57% success rate)
- New York: 2 companies
- Other locations: 6 companies across Texas, Delaware, and Washington
- California companies show a 50% success rate vs 20% for non-California companies


Key Successes (sample selection):

- Safe Superintelligence (Palo Alto): AI safety and systems
- World Labs (San Francisco): 3D perception and interaction
- Sapien (San Francisco): AI for finance

Significance and Implications

This experiment provides several significant insights:

Model Validation
- Demonstrates the effectiveness of ML-driven startup selection
- Shows strong predictive power for early-stage success indicators
- Validates the use of historical patterns for future success prediction especially in a vertical context (i.e AI)

Portfolio Strategy Validation
- Confirms the value of geographic diversity while maintaining focus on tech hubs
- Shows the importance of confidence thresholds in investment decisions
- Demonstrates successful risk management (only 1 failure in 15 investments)

Industry Implications
- Suggests potential for systematic outperformance using ML-driven selection
- Indicates high success potential in specific AI subsectors (cybersecurity, financial services)
- Demonstrates the value of data-driven decision making in venture capital

Looking Forward

With a projected success rate of 86.67% and current performance 5.43x above industry baseline, our results strongly validate the ML-driven approach to startup selection. The model's ability to identify promising companies across different locations and AI applications suggests scalability and broader applicability.

The strong correlation between model confidence scores and actual outcomes provides a compelling case for incorporating machine learning into venture capital decision-making processes. As we continue to monitor the portfolio, the early results suggest that AI-powered startup selection could significantly improve venture capital returns while reducing investment risks.

**Disclaimer**: This analysis is for educational purposes only. Past performance does not guarantee future outcomes.
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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2188462 2025-04-06T13:23:17Z 2025-04-06T13:29:38Z Predicting Success in AI Startups: A Data-Driven Investment Analysis Part 2 - 2021 Vintage

This version 2 research extends our machine learning approach to identify high-potential AI startups from the 2021 vintage, yielding compelling results that further validate our investment methodology.


Project Framework

We applied our established machine learning methodology to identify promising AI ventures in the 2021 cohort, maintaining consistency with our previous analysis.

Our approach continued to incorporate:

- Six predictive variables: Industries, Company Description, Founder Biography, Founder Gender, Location, and Educational Background

- A dual-model ensemble combining Random Forest and XGBoost algorithms

- Advanced text vectorization for unstructured data


Portfolio Performance

Our model selected 19 companies from the 2021 vintage all the way till 2024 (evenly distributed) with the following current performance:


- 9 companies (47.37%) have already achieved valuations exceeding $500M, including:

  - Perplexity AI: Reached $9 billion valuation in December 2024, with over $100 million in annualized revenue as of March 2025

  - Cyera: Secured $300 million in Series D funding, reaching a $3 billion valuation in November 2024

  - Hippocratic AI: Achieved unicorn status with a $1.64 billion valuation in January 2025

  - Anumana: Showcasing leadership in AI-powered cardiovascular solutions

  - World Labs, Protect AI, Mytra, DatologyAI, and Revefi


- 4 companies (21.05%) demonstrate strong growth trajectories

- 4 companies (21.05%) are too early in their development to evaluate conclusively

- 2 companies (10.53%) have not ceased operations but are unlikely to achieve significant success


This 47.37% high-performer rate significantly outperforms the best venture capital unicorn success rates of 5% (Sequoia), with potential to reach 68.42% as companies currently on track continue to develop. The 10.53% failure rate thus far remains substantially lower than industry averages of 75%, not factoring in various constraints of real investing.

Our model continues to demonstrate strong predictive capability while serving as a decision support tool rather than a replacement for comprehensive due diligence.

We will continue to analyze additional vintages across larger geographies and sectors, publishing results as they become available.


Disclaimer: This analysis is for educational purposes only. Past performance does not guarantee future outcomes.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2187575 2025-04-02T13:41:36Z 2025-04-02T13:41:36Z New Zealand's Innovation Pathway

As a Singapore-based VC, I've witnessed how innovation ecosystems evolve naturally when properly supported. Singapore initially emphasised deep tech but allowed market forces to shape developments organically.

Critiques of New Zealand's funding imbalance misses a crucial point: successful startups need significant market power quickly, regardless of their technological depth. Creating numerous small non-deep tech ventures won't deliver the economic impact New Zealand seeks. You need to continue to focus on both.

Three focused recommendations:

  1. Establish a national coordination body with a hands-on advisory panel of experienced entrepreneurs and investors who can directly mentor founders to scale globally. This addresses both fragmentation and practical scaling challenges.

  2. Develop diverse funding mechanisms prioritizing ventures with global potential rather than simply increasing startup quantities. Government initiatives on grants, fund of funds support should continue with momentum but understand the signs of change and adapt to it.

  3. Implement more talent development/retention programs, one example to take note of is Singapore's NUS Overseas College, which immerses students in innovation hubs like Silicon Valley, creating globally-minded entrepreneurs with valuable networks. Net new migration into New Zealand needs to be positive over time, but this is likely to be the toughest challenge yet.

New Zealand should focus more on building globally competitive companies with proper ecosystem support. I know you can do it. You know you can do it. Whāia te iti kahurangi - pursue that which is precious.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2187125 2025-03-31T12:55:54Z 2025-03-31T12:57:03Z Predicting Success in AI Startups: A Data-Driven Investment Analysis

This version 1 research applies machine learning to identify high-potential AI startups from 2017-2019, yielding significant insights for investment decision-making.

Project Framework

We developed a machine learning methodology to identify promising AI ventures across two cohorts: 2017-2018 (475 companies) and 2019 (329 companies). 

Our approach incorporated:

  • Six predictive variables: Industries, Company Description, Founder Biography, Founder Gender, Location, and Educational Background

  • A dual-model ensemble combining Random Forest and XGBoost algorithms

  • Advanced text vectorization for unstructured data

Portfolio Performance

Our model selected 15 companies across both time periods:

2017-2018 Selections (10): Jerry, Health Note, Cylera, Deep Cognition, Determined AI, NoTraffic, MovieBot, SupplyHive, Kami Vision, Rowzzy

2019 Selections (5): Eleos Health, Anyscale, Baseten, Anvilogic, Fairmatic

Current Performance:

  • 6 companies (40%) achieved valuations exceeding $500M

  • 3 companies (20%) demonstrate strong growth trajectories

  • 3 companies (20%) show steady growth

  • 3 companies (20%) have ceased operations

This 40% high-performer rate significantly outperforms typical venture capital success rates of 10-20%, while the 20% failure rate is substantially lower than industry averages of 75%. This do not factoring in various constraints of real investing.

Key Investment Domains

Four predominant themes emerged:

  1. Enterprise AI Infrastructure (Determined AI, Anyscale)

  2. Healthcare AI Applications (Eleos Health, Health Note)

  3. Security Solutions (Cylera, Anvilogic)

  4. Financial Technology (Jerry, Fairmatic)

Investment Implications

Successful AI ventures consistently demonstrate:

  • Enterprise-focused solutions with clear value propositions

  • Technical excellence within founding teams

  • Strategic presence in major technology ecosystems

While our model demonstrates strong predictive capability, it remains a decision support tool rather than a replacement for comprehensive due diligence.

We will continue to do more and larger permutations in AI and work larger geographies and sectors and publish the results once they are done.


Disclaimer: This analysis is for educational purposes only. Past performance does not guarantee future outcomes.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2182526 2025-03-14T06:18:56Z 2025-03-14T06:18:57Z Rise of the Tinkerer VCs

The venture capital landscape in 2025 is evolving rapidly. I think the days of purely financial-focused "AUM" investors are slowly fading, replaced by a new breed of venture capitalist: the tinkerer VC. These investors don’t just write checks—they think like and are builders, actively engaging with founders and creating value through technical expertise, product strategy, and operational support.

This shift is particularly visible in early-stage venture capital, where founders demand more from their investors. Economic pressures and increasingly complex technologies are forcing VCs to rethink their approach. In this environment, the tinkerer VC—someone who understands startup engineering, product development, and go-to-market strategies—is becoming indispensable.

Capital is abundant, but value-added support is rare. They want partners who can help them build—not just financially, but technically. This is especially true for startups in fields like AI, biotech, or climate tech. Founders need investors who understand their technology deeply and can contribute to solving technical challenges or scaling efforts. A VC who can’t engage meaningfully with the latest technologies risks being left behind.

The market correction of 2022–24 shifted the focus from growth-at-all-costs to capital efficiency and sustainable growth. Startups now need to do more with less funding, which opens the door for tinkerer VCs who can help optimize operations and refine strategies. Investors who understand the mechanics of building—from engineering to execution—are better equipped to guide startups through these challenges.

Specialization is becoming essential in venture capital. Generalist investors struggle to compete when technical fluency is required to evaluate opportunities or support founders meaningfully. Tinkerer VCs—often with backgrounds in engineering or product development—stand out in sectors like generative AI or climate tech because they can dive deep into technical challenges and provide actionable advice.

If you’re an investor—especially in early-stage—it’s time to adapt to this new reality. Technical savvy isn’t optional anymore; it’s a competitive advantage that sets you apart in a crowded field. 

Here’s how you can evolve:

1. Learn Startup Engineering
Understand how startups build products by learning the fundamentals of software engineering, product design, and system architecture. Take coding courses, experiment with building projects yourself, or work with the latest technologies like generative AI tools. Hands-on experience will give you insights that spreadsheets never will.

2. Build Things Yourself
Invest time in tinkering—whether it’s coding apps, experimenting with hardware, or prototyping solutions using cutting-edge tools like GPT APIs or cloud platforms like AWS and systems programming like CUDA. Founders respect investors who understand what it takes to build something from scratch.

3. Specialize Where You Can Add Value
Focus on sectors where you can develop deep expertise—whether it’s AI, climate tech, fintech, or another domain—and commit to understanding those industries inside out. Specialization improves your ability to evaluate opportunities and enhances your reputation among founders.

The venture capital industry is changing—and tinkerer VCs are leading the way forward in 2025 and beyond. Investors who embrace technical fluency and hands-on engagement will outperform those stuck in traditional financial models.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2180409 2025-03-05T15:26:44Z 2025-03-05T15:26:44Z The Future Belongs to the Bold: Backing Founders Who Dare to Dream Big

Investing in Southeast Asia for many years now, I’ve witnessed cycles of growth, correction, and reinvention. Yet, the current moment feels uniquely challenging—and transformative. The sectors emerging at the forefront for the next few years—B2B and deep tech—are ones where many of us have struggled to find consistent success over the last decade, especially compared to B2C and fintech. At the same time, our fund sizes have grown larger than ever, but the market size we operate in hasn’t proportionally expanded. This mismatch creates a tension that demands we rethink how we approach risk, ambition, and execution.

Since the 2022-2023 crash, large VC funds have increasingly gravitated toward safer, private-equity-like deals while becoming more multi-stage. It’s understandable; preserving capital feels prudent in uncertain times. But playing it safe won’t build the future. We cannot afford to give up on audacious founders—those who dare to think big and aim for transformative impact. These are the people who will unlock new markets, redefine industries, and create outsized returns—not just for investors but for society as a whole.

To thrive in this new era, we must retool and reinvent ourselves as investors. This means recalibrating how we assess risk, developing deeper expertise in emerging sectors, and being smarter and more calculated in our bets (keeping Power Law Distribution firmly in mind). It’s not about reckless optimism; it’s about supporting bold ideas with discipline and clarity.

This is a call to action: let’s not retreat into comfort zones or limit our vision. Let’s figure out what needs to change—within ourselves, our teams, our ecosystems, our founders, and our strategies—and make those changes happen. The future belongs to those willing to take calculated risks on founders with big dreams. Let’s ensure we’re part of building that future.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2158339 2024-12-11T15:14:59Z 2024-12-11T15:15:08Z Unlocking the Code of Venture Capital Success: Revelations from the Top VCs Globally (Midas List update)


As we journey through the fascinating world of top venture capitalists, we uncover a treasure trove of insights that shed light on the educational backgrounds, career paths, and the shifts in the demographic landscape of the industry. This data-driven exploration aims to provide a comprehensive view for limited partners, aspiring VCs, and students, as we delve into what makes these venture capitalists stand out.


Key Insights and Importance of Education


Top Undergraduate Universities


- Stanford University (13% of VCs)

- Harvard University (8%)

- MIT (7%)

- University of Pennsylvania (4%)

- Yale University (3%)


Stanford's dominance is unmistakable, emphasizing its pivotal role in the tech VC landscape.


Top Undergraduate Majors


- Engineering, Computer Science, and Related Disciplines (30%)

- Economics (17%)

- Business or Management (11%)

- Public Policy, Political Science, or Government (8%)

- Mathematics & Applied Mathematics (6%)


The importance of a STEM background remains evident, but there's a significant representation of business-related studies, reflecting the need for a multifaceted skill set.


Graduate Education


Graduate Degrees: 67% of VCs hold graduate degrees from esteemed institutions:

  - Stanford GSB (14%)

  - Harvard Business School (12%)

  - Columbia Business School (3%)

  - Wharton School, University of Pennsylvania (3%)

  - MIT Sloan School of Management (2%)


This trend speaks to the value placed on continuous learning and specialization in fields like business, finance, and technology.


Entrée into the Venture Capital Arena


- Direct Entry: 23% of VCs under 45 started their careers directly in VC, compared to only 13% for those over 45. This early specialization trend highlights a demand for nuanced expertise at the outset of one's career.


A New Generation's Rise


- Technical Backgrounds: 38% of VCs under 45 vs. 25% over 45, indicating an industry shift toward tech-savvy investors.

- Investment Banking: Investment banking serves as an initial career path for 45% of young VCs vs. 30% of their older counterparts, showcasing the sector's increasing integration with venture capital.


Experience and Impact in VC


- Founder Experience: 29% of VCs under 45 were founders, in contrast to 37% for those over 45, signifying a slower but still prevalent trend of operational experience.

- Analytical Backgrounds: Both cohorts show high levels of analytical savviness, with older VCs boasting experience in diverse roles like sales, strategic planning, and product management.


Diversifying Demographics


- Female Representation: A gradual increase in the younger cohort to 12% vs. 8% for older VCs, signaling progress in industry diversity.

- International Backgrounds: 36% of top VCs have international roots, underlining the global nature of venture capital, with significant representation from China, India, and Europe.


Key Insights for Stakeholders


For Limited Partners


- Invest in funds with multi-generational VCs to leverage industry trends and seasoned experience.

- Recognize the evolution in career paths, with younger VCs more likely to have an analytical or entrepreneurial background.


For Aspiring VCs and Students


- While technical education is advantageous, business and economic knowledge is equally important for understanding the broader market dynamics.

- Seek internships in investment banking, consulting, sales, or product management for hands-on experience.


Advances in Venture Investment Trends


- Industry Evolution: The venture capital landscape now leans towards sector specialization, with notable increases in tech-focused investments (most recently in AI).

- Diversification: Despite incremental progress in gender diversity, the industry recognizes the need for further internationalization and broader inclusivity.


In conclusion, the profile of top venture capitalists has evolved, adapting to changing industry needs, educational trends, and innovation. The combination of technical knowledge, diverse professional backgrounds, and a nuanced understanding of market dynamics remains key to navigating the entrepreneurial journey and gaining success in venture capital.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2152180 2024-11-13T12:44:19Z 2024-11-13T12:44:25Z The New Power Players: Who's Really Shaping the Future of AI Startups

The artificial intelligence gold rush isn't just about the tech giants and mega VCs anymore. A new quick and dirty analysis of the top 390 investments in top AI startups reveals a fascinating shift in who's really driving innovation in the AI ecosystem, with individual operators and specialized firms playing an increasingly crucial role.

The Rise of Operator-Investors

Leading the pack is Elad Gil, with investments in 12 cutting-edge AI companies including Perplexity and Character.ai. Gil's investment pattern reveals a keen focus on foundational AI technologies that could reshape entire industries. But what's particularly interesting is how former tech executives are leveraging their operational experience to spot the next big thing in AI.

Take Nat Friedman (former GitHub CEO) and Scott Belsky (Adobe CPO), who have each made strategic bets on three AI startups. Their investments often focus on developer tools and creative AI applications – areas where their deep industry expertise provides unique insight into market needs.

The New Wave of Specialized Firms

While traditional VCs still dominate in terms of dollar amounts, smaller, specialized firms are proving to be remarkably influential in shaping the AI landscape. Firms like Alumni Ventures (18 investments) and HongShan (19 investments) are punching above their weight, particularly in early-stage deals.

What sets these firms apart is their focused approach. Rather than casting a wide net, they're making concentrated bets in specific AI domains:

  • Enterprise AI infrastructure
  • Developer tools and platforms
  • AI in healthcare and biotech
  • Generative AI applications


Geographic Diversification

Perhaps most intriguing is the growing geographic diversity of AI investments. While Silicon Valley remains the epicenter, we're seeing increased activity in:

- Toronto (Cohere)

- London (DeepMind spinoffs)

- Berlin (Helsing)

- Beijing (Moonshot AI)


What This Means for the Future

The emergence of these new power players suggests a maturing AI ecosystem where expertise and specialized knowledge are becoming as important as capital. For founders, this means more options for smart money that comes with deep operational expertise and focused support.

The trend also points to a future where AI development might be less centralized than previous tech waves. With individual operators and specialized firms backing startups across the globe, we're likely to see more diverse and innovative applications of AI technology.

For those watching the AI space, keep an eye not just on the big names, but on these emerging kingmakers. They're the ones spotting and nurturing the next generation of AI breakthroughs, often before the bigger players take notice.

The AI investment landscape is rapidly evolving, and while the headlines might focus on the biggest checks, it's these individual operators and specialized firms that are often the first to spot and support the most innovative AI startups. Their growing influence suggests a future where AI development is more distributed, diverse, and potentially more impactful than ever before.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2143086 2024-10-04T12:32:34Z 2024-10-04T12:32:35Z Navigating the AI Startup Ecosystem: Insights from Network Analysis

The artificial intelligence (AI) startup ecosystem is a complex network of founders, investors, and companies working together to drive innovation and growth. To better understand the dynamics of this ecosystem, we conducted a quick and dirty network analysis using GAT (Pytorch Geometric) of 601 AI startups (deemed successful since 2013), focusing on the connections between founders and investors. Our findings provide valuable insights for founders seeking to raise funds at different stages of their startup journey.

Our analysis revealed the top 10 most influential investors in the AI startup ecosystem based on their number of connections:

1. Sequoia Capital: 43 connections

2. Insight Partners: 41 connections

3. Tiger Global Management: 40 connections

4. NVIDIA: 35 connections

5. Andreessen Horowitz: 34 connections

6. HongShan: 32 connections

7. Lightspeed Venture Partners: 29 connections

8. Google Ventures: 28 connections

9. BlackRock: 25 connections

10. Intel Capital: 24 connections


These investors play a significant role in shaping the AI startup landscape through their investments and partnerships for the last 10 years.


Series A Investors

1. Sequoia Capital

2. Andreessen Horowitz

3. Lightspeed Venture Partners

4. Google Ventures (tend to invest a little more in Series B in recent years)

5. Intel Capital


Series B and Later-Stage Investors

1. Insight Partners

2. Tiger Global Management

3. NVIDIA

4. HongShan (Focused on China mostly, going international now)

5. BlackRock (More later stages)


Advice for Founders in AI

Based on our analysis, we recommend the following approach for founders seeking to raise funds:

1. Series A: When raising a Series A round, focus on investors like Sequoia Capital, Andreessen Horowitz, and Lightspeed Venture Partners. These investors have a strong track record of backing early-stage startups and can provide valuable support beyond just capital.

2. Series B and Later: As you progress to Series B and later rounds, consider investors like Insight Partners, Tiger Global Management, and NVIDIA. These investors have the resources and expertise to help startups scale rapidly and navigate the challenges of later-stage growth.

3. Build Relationships: Regardless of the stage of your startup, it's important to build relationships with investors early on. Attend industry events, participate in startup accelerators, and leverage your network to get introductions to potential investors.


Disclaimer: Of course, past track record does not mean the future will be the same.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2083542 2024-02-06T01:42:38Z 2024-02-06T01:42:39Z Three Reasons Why Nations Whisper in Wonder at the Scarcity of Large Venture Capital FDI

In Southeast Asia's vibrant venture capital and startup landscape, a transformation echoes through the realms of enterprise software and deep technology as they descend upon us. As we embark on this new era, nations, both burgeoning and mature, ponder deeply on nurturing startups that reach for the stars. The venture funding sphere, once a bastion of bold dreams, now yearns for revolutionary creations and teams with global aspirations.

Reflecting upon this, I have discerned three pearls of findings:

First, the Luminance of Product and Technology:

In an age where only the extraordinary captivates, a startup's product or intellectual property (IP)/technology must not just innovate but shine among the global elite. This shift towards top-tier innovation resonates with trends favouring enterprise and deep technology.

Second, The Founding Team's Odyssey Beyond Borders:

The spirit of the founding team is pivotal. In a world without borders, founders must carry belief, confidence, and courage to journey globally. This international vision is the heartbeat of venture capitalists seeking market disruptors.

Third, The Art of Skill and Global Canvas:

The founding team's mastery in global expansion is crucial. Skills in international storytelling, team building, and capital raising form the fabric of their venture. Success is increasingly measured by the global footprint and international business acumen.

As we conclude, remember that in the universe's grand dance, every venture has its place. The pursuit of large venture capital FDI is a journey through an ocean of possibilities.

Echoing Rumi, "You were born with wings, why prefer to crawl through life?" Startups and nations must realize their potential to soar in the global market. Let this understanding uplift them toward horizons of success and innovation.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2085051 2024-02-05T03:18:35Z 2024-02-05T03:18:35Z Luck Plays a Crucial Role in Extreme (Venture/Startup?) Success

As seasoned venture capitalists, we frequently strive to unearth the crème de la crème of entrepreneurial talent—those brilliant minds brimming with tenacity and innovation. Yet, recent intriguing studies have uncovered a hidden gem: luck. Yes, you read correctly! It seems that while talent remains essential, fortune's favour might play an even larger role in achieving extraordinary heights.

In a groundbreaking 2018 study conducted by Italian researchers, they developed a compelling model illustrating the delicate dance between talent and luck. Although talent is undeniably important, their findings reveal that luck often holds sway over those reaching the pinnacles of success. Surprisingly enough, moderately talented individuals who experience a stroke of serendipity tend to excel beyond expectations.

These revelations hold significant weight when considering investment strategies. Investors must acknowledge the considerable impact of luck and external circumstances. No longer should we solely target the topmost talents; instead, casting a wider net could lead to increased efficiencies.

Moreover, this study sheds light on the fact that success adheres to a power law distribution, whereas talent follows a standard bell-shaped curve. Companies such as Google and Facebook owe part of their monumental achievements to sheer luck, being in precisely the right place at the right moment.

While identifying gifted founders remains crucial, we must recognise that extreme success transcends mere talent. Even an ordinary founder armed with a remarkable concept can benefit from a fortunate turn of events and surpass the most accomplished competitors. Diversifying investments increases the likelihood of capturing future blockbuster ventures. Talent and luck both matter, yet luck reigns supreme among the elite.

So, how does one discern whether a founder possesses an innate knack for luck? Perhaps by posing questions such as, "Do you consider yourself a lucky individual since your early years?" Gathering responses linked to startup performance data might yield surprising results. After all, fortune favours the bold...and perhaps the curious too!

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2083482 2024-02-02T11:44:04Z 2024-02-05T03:21:48Z The Traits That Make Great Founders vs. Those Who Fail - Quick and Dirty Experiment

In recent years, researchers and practitioners alike have been studying the personalities of successful startup founders to understand what makes them tick. By analysing the Big Five personality traits—openness, conscientiousness, extraversion, agreeableness, and neuroticism—we can gain insights into the characteristics that contribute to a founder's success or failure. In this blog post, we will use what a quick Google search list as the best and worst rated founders and take a look at their personality traits. However, I only did a small sample set as a quick experiment. 

Best Rated Founders

The following five founders stand out as examples of those who excel in their roles:

1. Patrick Collison (Stripe)

2. David Vélez (Nubank)

3. Max Levchin (Affirm)

4. Brian Armstrong (Coinbase)

5. Stewart Butterfield (Slack)

These founders generally exhibit high levels of openness and conscientiousness, moderate to high agreeableness, moderate extraversion, and low neuroticism. These traits help them navigate the challenges of building and growing successful startups.


Worst Rated Founders

On the other hand, there are founders whose actions and decisions led to negative consequences for themselves and their companies. Some notable examples include:

1. Travis Kalanick (Uber)

2. Elizabeth Holmes (Theranos)

3. Parker Conrad (Zenefits)

4. Billy McFarland (Fyre Festival)

5. Adam Neumann (WeWork)

Founders here often display high openness and extraversion, but extremely low conscientiousness and agreeableness, along with low neuroticism. Their actions and decision-making processes contributed to the failures of their respective ventures.


Findings

Based on the analysis of these founders, several patterns emerge:

- Successful founders typically exhibit high openness and conscientiousness, moderate to high agreeableness, moderate extraversion, and low neuroticism.

- Unsuccessful founders often show high openness and extraversion, but very low conscientiousness and agreeableness, and low neuroticism.

- Sociopathic founders are characterized by very high extraversion, very low agreeableness, conscientiousness, and neuroticism, with variable openness.

- Founders with Narcissistic Personality Disorder (NPD) tend to have high extraversion, very low agreeableness, moderately low conscientiousness and neuroticism, with no clear pattern in openness.


As Rumi once said, "What you seek is seeking you." Similarly, the qualities that make great founders also attract them to entrepreneurship. 

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2083051 2024-01-31T11:51:43Z 2024-01-31T11:51:43Z Analyzing the Roots of Success: The Backgrounds of Top Venture Capitalists

In the dynamic and often unpredictable world of venture capital, understanding what shapes the best in the business is not just intriguing but essential. The journey to becoming a top venture capitalist (VC) varies, with backgrounds ranging from founding startups to crunching numbers in analytical roles. But what path is most trodden by these elite investors? Our analysis of a comprehensive list of the world's best VCs sheds light on this question, offering insights into the experiences that shape the minds investing in tomorrow's leading companies. We analyse around 372 VCs who have been on the Forbes Midas List since inception.

The Analytical Pathway: A Common Ground

Our findings reveal a striking pattern: a substantial 91.1% of top venture capitalists previously held positions in analytical fields. This statistic underscores the value of an analytical mindset in the world of venture capital. Analytical roles, encompassing areas such as financial analysis, investment management, and data-driven decision-making, equip VCs with the acumen to dissect complex market trends, evaluate business models, and make calculated investment decisions. The high percentage of VCs with this background suggests that an analytical foundation is not just beneficial but perhaps essential in navigating the intricate landscape of venture investment.

Entrepreneurial Experience: Valuable but Less Common

Contrary to the popular belief that most successful VCs are former entrepreneurs, our analysis paints a different picture. Only 21.5% of the top venture capitalists were founders before stepping into their current roles. While this figure highlights the significance of entrepreneurial experience, it also clarifies that it's less common than one might expect. Having been in the founder's shoes does provide unique insights into the challenges and dynamics of starting and scaling a business. However, it appears that having a founder's background, while advantageous, is not a predominant trait among the world's leading VCs.

Diverse Roads to the Top

The journey to becoming a top VC is diverse and multifaceted. While a strong analytical background is prevalent among these successful individuals, it is by no means the only path. The world of venture capital values a variety of experiences, whether it's steering a startup through turbulent waters or navigating the complexities of financial markets. This diversity in backgrounds contributes to a richer, more versatile approach to investment strategies, benefiting both the VCs and the innovative companies they choose to back.

Conclusion: Blending Analytical Acumen with Varied Experiences

The landscape of venture capital is as varied as it is challenging. Our analysis reveals that top venture capitalists often share a common thread of analytical experience, providing them with the skills necessary to assess and manage risk effectively. However, the path to becoming a leading VC is not monolithic. Experiences as diverse as entrepreneurship, financial management, and technology development all play a role in shaping the instincts and insights of these investment leaders. As the venture capital industry continues to evolve, the blend of analytical rigor and diverse experiences will remain pivotal in identifying and nurturing the next generation of groundbreaking companies.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2052713 2023-11-19T14:56:05Z 2023-11-19T14:56:05Z Beyond the Business Plan: Assessing Startup Founders Holistically

As venture capitalists, we see many promising business plans from talented founders. However, the stresses of starting a company can take a toll on mental health especially since Covid. Studies show over 70% of founders report some impact on their mental wellbeing[1]. While passion and vision are critical, we must also evaluate how a founder's mental health could affect their ability to lead a successful startup. 

When reviewing business plans, here are some important considerations:

- Look for self-awareness and maturity. Founders who are open about their mental health needs and actively manage them signal responsibility. Seek out those who prioritize self-care and have supportive personal and professional networks.  

- Scrutinize financial planning more than usual. Impulsivity or unrealistic projections may reflect impaired judgment. Look for pragmatic financial models with executive pay aligned to value creation.

- Assess the team dynamics. Diverse, complementary teams tend to be more resilient. Watch for "red flags" like frequent turnover or poor communication that may indicate unmanaged mental health issues.

- Consider market viability to another level of detail. Evaluate the business model, competitive landscape, and addressable market.

- Provide mentorship. All founders need guidance navigating startup life's ups and downs. Be available as a sounding board and connect founders to resources like coaches, therapists, and peer support groups.

With awareness and support, founders with mental health issues can channel their creativity to build sustainable, impactful companies. As investors, we have an opportunity to foster an ecosystem where mental health is openly addressed so founders can fulfill their visions. Evaluating founders holistically is key to funding resilient startups poised for long-term success.

Times are different now, investors should be more aware of what to look for and how to help founders more going forward.


Citations:

[1] https://www.pnas.org/doi/full/10.1073/pnas.2215829120

[2] https://executive.berkeley.edu/thought-leadership/blog/impacts-poor-mental-health-business

[3] https://hbr.org/1985/05/how-to-write-a-winning-business-plan

[4] https://www.nature.com/articles/s41598-023-41980-y

[5] https://www.forbes.com/sites/melissahouston/2023/05/31/the-impact-of-mental-health-on-business-owners/?sh=266080683e41

[6] https://www.crowdspring.com/blog/what-investors-want-in-a-business-plan/

[7] https://www.forbes.com/sites/annefield/2023/04/29/startup-founders-report-entrepreneurship-is-taking-a-toll-on-their-mental-health/?sh=266a8c8e2192

[8] https://www.forbes.com/sites/tracybrower/2023/02/28/mental-health-delivers-big-business-benefits-3-strategies-for-success/?sh=2667109b3c8d

[9] https://www.linkedin.com/pulse/what-do-investors-look-business-plan-mike-kovach

[10] https://finance.yahoo.com/news/72-startup-founders-report-impact-190904214.html

[11] https://www.paychex.com/articles/human-resources/workplace-mental-health-effects

[12] https://startupnation.com/start-your-business/investors-business-plan/

[13] https://www.fastcompany.com/90969820/will-your-startup-fail-personality-traits-for-success

[14] https://hbr.org/2021/10/its-a-new-era-for-mental-health-at-work

[15] https://www.indeed.com/career-advice/career-development/business-idea-evaluation

[16] https://www.sciencedaily.com/releases/2023/10/231017215925.htm

[17] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969895/

[18] https://www.investopedia.com/financial-edge/0412/5-essential-steps-to-evaluating-your-business-idea.aspx

[19] https://link.springer.com/article/10.1007/s11187-018-0059-8

[20] https://blog.exit-planning-institute.org/how-owning-a-business-impacts-mental-health-and-stress-levels

[21] https://www.entrepreneur.com/starting-a-business/5-things-investors-want-to-know-before-signing-a-check/234536

[22] https://grepbeat.com/2022/07/13/startup-lifes-dark-secret-founders-often-face-mental-health-challenges/

[23] https://www.putnam.com/individual/content/perspectives/8047-mental-health-is-a-business-issue-how-companies-are-supporting-their-employees

[24] https://aofund.org/resource/what-do-investors-look-for/

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/2024545 2023-09-15T16:47:00Z 2023-09-18T09:53:17Z Were there discipline in venture capital investing during the hype cycle in 2021/2022?

I recently did a quick data analysis on Southeast Asia early stage venture capital investments in different firms over the past few years. The data (from Crunchbase) shows the ratio of investments made by each firm in a recent period of hype (March 2021 to March 2022) compared to their average number of investments over the previous 2-3 years. Let's dig into the data and see what insights we can gather. 

Overall, the data shows a fair bit of variation between firms in terms of how their recent investment levels compare to their historical averages. 

A few key observations: 

  • Most firms (15 out of 17) saw increases in their investment levels compared to historical averages. This indicates an overall uptick in VC activity among these firms during the hype period. However, the degree of increase varied quite a bit. 3 firms saw modest increases of 50% or less compared to their averages. There are 2 firms that saw massive increases of 200-500% above their typical investment cadences. 
  • There were 2 firms that saw decreases in investments in the 25-60% range compared to historical averages. So the pullback in investing among these firms depicted strong contrarian behavior compared with the surge in activity among the highest growing firms. 

Overall, these data reflect a VC market that saw accelerated growth in 2021 but with an uneven distribution - very few firms are pulling back showing investment discipline while others are rapidly expanding investments. 

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1981214 2023-05-29T06:36:50Z 2023-05-29T16:20:58Z Strategic Approaches for Emerging Markets Early Stage Funds in 2023

In the complex and multifaceted realm of venture capital and startups in 2023 post 2022 slow down, emerging markets present a unique set of opportunities and challenges. A significant challenge is the potential diminution of later-stage follow-on funds and a concurrent decline in the quality of later-stage investors. This situation can engender a funding gap for startups in their growth phase and a dearth of strategic guidance. However, through strategic planning and innovative thinking, early-stage funds can effectively navigate these challenges.

When later-stage capital becomes scarce, it can create a funding vacuum that hampers the growth trajectory of startups, potentially leading to a deceleration in the overall startup ecosystem. The decline in the quality of later-stage investors can exacerbate this situation (based on performance and just the law of large numbers). In such a scenario, early-stage funds need to adopt a proactive and innovative approach. Here are some strategies:

  1. Strategic Partnerships: Early-stage funds should seek alliances with firstly your limited partners, corporate investors, family offices, or other entities that have a vested interest in the startup ecosystem. These partners can provide not only capital but also strategic guidance, market access, and other resources. Focus and Lean on your Limited Partners, especially those who are financially driven not just strategic.

  2. Syndicate Investments: Early-stage funds should consider forming syndicates with other early-stage investors. Syndicates allow investors to pool their resources, share risks, and increase the total amount of capital available for follow-on rounds.

  3. Investor Relations: Early-stage funds should maintain strong relationships with existing investors and continuously engage with potential new investors. Regularly communicating portfolio companies' progress and milestones can help attract follow-on investments. 

  4. Continue to focus on Capital Efficiency (from 2022): Early-stage funds should work closely with their portfolio companies to improve their capital efficiency. Adopt an advisory mindset builds trust and results.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1969002 2023-04-23T07:03:13Z 2023-04-27T14:03:35Z Quick and dirty experiment - Top SEA Startups and where the founders went to school

An Analysis of Founder and Executive Education Backgrounds at Top Southeast Asian Startups

I conducted an analysis of the educational backgrounds of founders at 99 of the highest-funded startups in Southeast Asia. Using Crunchbase as the database and then researched the schools and programs listed for key leaders at each company.

By far the most represented university is National University of Singapore (NUS), with 18 attendees out of 227. No other university comes close, underscoring NUS’s dominance as a pipeline for Southeast Asian startup talent (bachelors). 

U.S. schools are also popular, especially Stanford (6 attendees) and Carnegie Mellon (6 attendees). However, an interesting finding is Harvard Business School (MBA) comes in second with 12 attendees.

Several other insights emerge:

  • Within Singapore, beyond NUS, notables include Nanyang Technological University (10 attendees) and Singapore Management University (5 attendees).

  • STEM degrees are common from schools across the board.

  • US schools beat UK and Australian schools by a wider margin.

  • Indonesian founders - ITB is creates more of such founders than University of Indonesia.

This analysis still only scratches the surface. With additional data on companies, founders, executives, and their educational paths, we could develop even richer insights into the human capital flows behind Southeast Asia’s tech innovation and entrepreneurship. Please let me know if you would like me to pursue any further research.

p.s For Parents from Singapore: Go to NUS for bachelors and HBS for MBA - there you go no pressure. You are welcome.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1935555 2023-01-31T06:22:47Z 2023-04-23T06:51:26Z Brace for 2023

Forewarning: 

I accurately forecasted the tech crash globally and in SE Asia earlier in 2021 (although I was a quarter late (Q3 2022)- I did not predict the the war). The tech industry has seen a major downturn in 2022 due to various macroeconomic factors like rising inflation, interest rates hikes, and geopolitical tensions. While the timing of my prediction was slightly off, the rationale behind the forecast was sound.

The next softer correction is expected in Q3/Q4 2023 due to declining late 2022/early 2023 funding and disparity between performance and valuations. Venture capital funding in tech startups peaked in 2021 and has been declining ever since. At the same time, the valuations of many private tech companies remain very high relative to their performance and growth. This disconnect is unsustainable and will likely lead to a downward valuation adjustment for many startups.

To safeguard your investments and your own startups, consult with trusted advisors, investors, and shareholders on your business growth, projections, and capitalisation strategy. Startup founders and investors should review financial projections and valuation models to ensure they are grounded in realistic expectations for growth and performance. Companies should also evaluate their capital needs and options for meeting those needs if VC funding continues to slow down (this slow down will stretch till end of 2023). Plans may need to be made for extending runway, cutting costs, and pursuing alternative funding sources. There will be instances where existing investors may force strategic options to even cease operations and return capital, be mindful of the rationale and use data and evidence to help with your decision making.

Brace for impact from end of Q2. The effects of reduced funding and more cautious investor sentiment will start to be felt more acutely toward the end of the second quarter of 2023 and into the third quarter. Startups and investors should prepare now for this changing landscape to avoid being caught off guard.

Stay alert. 

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1830534 2022-05-23T02:00:02Z 2022-12-30T23:45:36Z Time to sharpen your pencils

Art by Ivan Dubovik

Firstly, let me apologize for this really tardy post. I have been wanting to post this back in late 2019 and again in mid 2021. Startup activity and valuations crept higher in late 2019 due to the launch of several new funds in 2018 in Southeast Asia, followed by more capital inflows from US, Europe, Korea, Japan, India and China.

In 2020, we had a short burst of panic from March to July 2020 but investments restarted with smaller rounds and finally back in full vengeance from the start of 2021. This contributed to the best year ever in 2021 in terms of capital inflow in our region. To top it off we had interests from US SPACs and direct IPOs with companies in Southeast Asia. 

At the moment with the public market correction and uncertainty coupling with the effects of the US inflation due interest rate hikes and the war in Ukraine. There is a fear that this will come to the private markets, and yes it will. Valuations are 50-70% over valued since years before the pandemic.

What are the reasons? I will briefly touch on two.

1. We have not experienced a correction in Southeast Asia since the GFC contributing to a strong growth of new founders and investors in our ecosystem. In addition, without a flow of exits like quick acquihires, M&As and IPOs, many of our companies remain private with mostly paper gains and when IPOs do arise, early investors are cashing out and not invested for growth. As such, the quality of founders and investors reduces over time. This gives rise to undisciplined investments in companies where unit economics and growth rates are blurred between companies that gives venture returns vs those who don't. Finally the pandemic don't help in with the situation as it also gives rise to a postponement of performance and extension of rounds with little to no causation to performance.

2. Compressed funding rounds spread out over a shorter period of time in order to capture market share became more prevalent. If research on market size, adoption and timing is not done well, the execution of the business will be impacted. Overselling of our region's size and growth without relying on real business or consumer drivers affects the speed and consistency of market adoption. Hence some valuations of companies fails to be justified with performance. The region is still an emerging one, its maturity may sometimes be far from what we expect, making business projections difficult to forecast. 


So what do you if you are a founder or investor?

1. For new startup founders - Work on and refine your 12 year plan and capitalization strategy and find valuation comparables that are realistic to achieve. This is not an easy exercise but an exercise you have to do nevertheless.

2. For operating founders post Series A - Speak to Series C and D investors and ask them what are they expect of your business milestones and try to close that knowledge gap.

Besides the usual rhetoric of telling you to tighten your belt and extend your runway to over 18 months, you need to be operating your business at a level that will interest capital providers who have now sharpened their pencils. The silver lining here is there is still a large over hang of venture capital raised in 2020/2021 but trust me the investors will be more stringent going forward. Realign your approach to performance once you are clear of what is expected of you. There are situations when it is too late to turn back, and this will lead you to take a strategic option that unfortunately is the best path ahead for your company, employees and shareholders. 

I foresee higher stress levels for founders in the next few quarters. Do lean on your trusted network of advisors, mentors and coaches to help guide you through whatever is coming. 

If you need help or someone to talk, do reach out to me or the team at Coachable Initiative

Keep your heads up, we got this.

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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1784871 2022-02-05T22:05:45Z 2022-12-30T23:46:14Z 5 Questions for your kids

Here are some questions you can try with your kids to have a healthy exchange after picking them up or coming home from school.

1. What happened in school today?

- this trains observation and descriptive abilities


2. What did you perform well today?

- encourages no matter what is deemed good to be shared and we can encourage them to do better


3. What did you learn today?


4. Are there anything you don't know or don't understand today? Anything disturbing or feels weird?


5. Are there areas mom and dad can help you with?

- help to figure which areas they can solve themselves and which areas parents can help solve


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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1568745 2022-01-10T07:50:00Z 2022-12-30T23:46:28Z Startups have a new Squid Game

I have been asked many times about smaller startup ecosystems in Southeast Asia what they should do to generate large technology startups and thus attract more foreign direct investment in their countries. After yet another roundtable with a government entourage and local and regional ecosystem leaders, let me share a few thoughts. 

Start by using historical data and research to give you a place to start. We have over 10 years of startup and funding data to study in Southeast Asia of which I will not cover in depth, but for those who are keen to chat about using data driven strategies to run your fund please contact me.

Here are some high level data for you.

In SE Asia, most of the largest valued companies are:

  • Global aspiration - 8% (most are B2B)
  • Indonesia only aspiration - 40%
  • SEA regional aspiration (usually with Indonesia as one of the aspired market) - 30% (1 in many)
  • SEA ex-ID Squids - 17% (many in 1)
  • SEA ex-ID only aspiration - 3% (hardly funded nor grow fast enough - 1 in 1)

With this as a backdrop, and the fact that the founders are aware that they are more than likely a copycat (99% are).

What should you do then?

1. Gather Knowledge

  • Understand your environment in your beach head market or markets you are targeting and figure out your problem statement, consumer and business drivers and timing
  • Figure if you and your team are the ones that are capable to address these market(s)
  • Then focus on product and growth metrics while serving these markets and try to move from the bottom left to the top right corner of the chart above

We (founders and investors) have a fundamental lack of knowledge flow between capital providers from different stages. I would recommend more open conversations between accelerators and Series B to D capital providers to really understand what they are looking for. We also need to speak to other founders they are likely to copy around the world to learn what not to do in their businesses. Lastly, we need to learn from others in both developed and developing markets and understand what drivers are needed to help startups to be successful. Everyone needs to gather knowledge.

2. Market Mapping

If you are able to go global and compete with the best in class, likely aiming to be the top 4 in the world, go for it. However, from historical data, the probability of that happening is low but not impossible.

The higher probability of where you are now or will be are the 2 bolded options above.

First, if you are not addressing Indonesia from day one, you need to start planning your regional plan from day one as there will be other copycats in the region as well with a head start because they are either already based in Indonesia, or has raised more capital and/or launched in multiple markets earlier than you.

Second, be a Squid

This is where most startups get stuck, they are there but not quite. Look to be a squid with 2 tentacles and 8 arms in your home country, and plan to extend 2 tentacles to potentially 2 countries and 8 arms into potentially 8 different business lines. This way, your total combined addressable market will be larger than you originally sought out to do.

Hope this helps. 

Happy New Year!





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Jeffrey Paine
tag:jeffreypaine.com,2013:Post/1598609 2020-10-04T05:47:51Z 2022-12-30T23:46:43Z The 1% focus

99% of companies should not raise capital from venture capital firms.

But many founders who are in the 99% thinks they are the 1% who should. Sometimes investors think the same way and that may spell trouble many rounds or years later.

Work with your cofounders, advisors and investors to make sure where you stand.

If you are the 99% (and there is absolutely nothing wrong with this), and want to be the 1%, work hard and leverage on your team, capital and strategy (timing/speed), and execute to address larger markets (Y-axis) and increase the sophistication of your MOATs (X-axis). See http://reactionwheel.net/2019/09/a-taxonomy-of-moats.html.

Once you know who you are and what you will be in 7-10 years will you be able to honestly approach the right investors who fit you. 


In Vietnamese

99% các công ty không nên huy động vốn từ các công ty đầu tư mạo hiểm.


Nhưng nhiều nhà sáng lập nằm trong 99% này lại cho rằng họ là 1% còn lại nên muốn làm. Đôi khi các nhà đầu tư cũng nghĩ như vậy và điều đó gây rắc rối trong nhiều lần hoặc nhiều năm sau đó.


Làm việc với những người đồng sáng lập, cố vấn và nhà đầu tư của bạn để đảm bảo vị trí của bạn.


Nếu bạn là 99% (và hoàn toàn không có gì sai với điều này) và muốn trở thành người 1%, hãy làm việc chăm chỉ và tận dụng đội ngũ, vốn và chiến lược của bạn (thời gian / tốc độ) và thực hiện để giải quyết các thị trường lớn hơn (Y -axis) và tăng độ tinh vi của MOAT (trục X) của bạn. 


Xem http: //reactionwheel.net/2019/09/a-taxonomy-of-moats.html.


Một khi bạn biết bạn là ai và bạn sẽ là gì trong 7-10 năm nữa, bạn sẽ có thể tiếp cận thực tế những nhà đầu tư phù hợp với mình.


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Jeffrey Paine