I recently spent a few weeks in Asia, visiting Tokyo, Hong Kong, Singapore, and Taiwan before returning to Toronto. Eva joined me for the first part of the journey, while I spent time in Singapore on my own, a city I’ve visited numerous times before. In Taiwan, I was accompanied by Albert, who was born there and still has family ties in the region.
This was by far my longest trip in quite some time. These destinations represent some of the world’s most developed economies, with GDP per capita levels comparable to or exceeding those in North America. Singapore, for instance, has a per capita GDP of around 90,000 USD, roughly 50 percent higher than the United States’ 66,000 USD.
Conversations and Perspectives
Coincidentally, my visit aligned with Liberation Day. Needless to say, it sparked many fascinating conversations, including the so-called “penguin tariffs,” whether AI is already smarter than certain politicians, and everything in between. Around that time, I also came across a perspective that stood out. While tariffs were initially expected to threaten Asian economies, many locals believed they had ended up affecting the United States more. Businesses in the Asia Pacific region had begun diversifying away from reliance on the US market years ago. As a result, they now have more leverage, and the direct impact of tariffs has been relatively limited. The broader concern was the possibility of a global recession.
Tech Energy in the Region
Across all four regions, I witnessed growing momentum in tech entrepreneurship. I had the chance to speak at tech conferences, lead masterclasses, take part in fireside chats, and encourage high school students to consider entrepreneurship as a path worth exploring.
Why It’s Happening
Why is this happening? These regions have strong technical capabilities. Taiwan, for example, manufactures about 90 percent of the world’s most advanced chips, and its capabilities are unmatched by any other country. Singapore, on the other hand, excels in semiconductor fabrication and biotechnology, and its presence in AI and computing infrastructure continues to grow.
Understanding the Cultural Landscape
At the same time, the cultural differences between East and West remain clear. The East tends to emphasize social harmony, collective behaviour, and conformity. The West often puts more weight on individual expression and free spirit.
Even small things reflect these differences. Take jaywalking. In Tokyo and Singapore, it is rare. People stare at you if you do it. In contrast, after jaywalking was recently legalized in New York City, I actually felt social pressure to jaywalk. Not doing so made me feel out of place.
Why Culture Matters in Business
For companies working across borders, recognizing these kinds of cultural nuances is not optional. It is essential. A one-size-fits-all approach often leads to missteps.
The Bicultural Perspective
Having been raised in Asia and now living in Canada for decades, I’ve come to appreciate the value of navigating both worlds. That dual perspective has become a quiet but important asset in both my personal and professional life. It is not a liability.
As I often say:
“Bamboo is neutral. If it’s used as a ceiling, it becomes a barrier. But if it’s used as a pole for jumping, one can leap incredibly high. Biculturalism is a powerful asset. If you leverage it in the right context, it can become your unfair advantage.”
Biculturalism, when used with intention, becomes a meaningful advantage. It helps you understand nuance, communicate across different environments, and approach global opportunities with more adaptability.
Looking Ahead
In an increasingly interconnected world, going global is no longer just a choice. During Asian Heritage Month, this feels especially relevant. Let’s celebrate not only our roots but also the advantages that come from navigating multiple worlds.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Driven by rapid advances in AI, the collapse in the cost of intelligence has arrived—bringing massive disruption and generational opportunities.
Building on this platform shift, TSF invests in the next frontier of computing and its applications, backing early-stage products, platforms, and protocols that reshape large-scale behaviour and unlock uncapped, new value through democratization. These opportunities are fueled by the collapsing cost of intelligence and, as a result, the growing demand for access to intelligence as well as its expansion beyond traditional computing devices. What makes them defensible are technology moats and, where fitting, strong data network effects.
Ormore succinctly: We invest in the next frontier of computing and its applications, reshaping large-scale behaviour, driven by the collapsing cost of intelligence and defensible through tech and data moats.
Watch this 2-minute video to learn more about our approach:
Our Evolution: From Network Effects to Deep Tech
When we launched TSF in 2015, our initial thesis centred around network effects. Drawing from our experience scaling Wattpad from inception to 100 million users, we became experts in understanding and leveraging exponential value and defensibility created by network effects at scale. This expertise led us to invest—most as the very first cheque—in massively successful companies such as BenchSci, Ada, Printify, and SkipTheDishes.
We achieved world-class success with this thesis, but like all good things, that opportunity diminished over time.
Our thesis evolved as the ground shifted toward the end of 2010s. A couple of years ago, we articulated this evolution by focusing on early-stage products, platforms, and protocols that transform user behaviour and empower businesses and individuals to unlock new value. Within this broad focus, we zoomed in specifically on three sectors: AI, decentralized protocols, and semiconductors. That thesis guided investments in great companies such as Story, Ideogram, Zinite, and Blumind.
But the world doesn’t stand still. In fact, it has never changed so rapidly. This brings us to the next and even more significant shift shaping our thesis.
A New Platform Shift: The Cost of Intelligence is Collapsing
Reflecting on the internet era, the core lesson we learned was that the internet was the first technology in human history that was borderless, connected, ubiquitous, real-time, and free. At its foundation was connectivity, and as “the cost of connectivity” steadily declined, productivity and demand surged, creating a virtuous cycle of opportunities.
The AI era shows remarkable parallels. AI is the first technology capable of learning, reasoning, creativity, cross-domain functionality, and decision-making. Like connectivity in the internet era, “the cost of intelligence” is now rapidly declining, while the value derived from intelligence continues to surge, driving even greater demand.
This shift will create massive economic value, shifting wealth away from many incumbents and opening substantial investment opportunities. However, just like previous platform shifts, the greatest opportunities won’t come from digitizing or automating legacy workflows, but rather from completely reshaping workflows and user behaviour, democratizing access, and unlocking previously impossible value. These disruptive opportunities will expand into adjacent areas, leaving incumbents defenceless as the rules of the game fundamentally change.
Intelligence Beyond Traditional Computing Devices
AI’s influence now extends far beyond pre-programmed software on computing devices. Machines and hardware are becoming intelligent, leveraging collective learning to adapt in real-time, with minimal predefined instruction. As we’ve stated before, software alone once ate the world; now, software and hardware together consume the universe. The intersection of software and hardware is where many of the greatest opportunities lie.
As AI models shrink and hardware improves, complex tasks run locally and effectively at the edge. Your phone and other edge devices are rapidly becoming the new data centres, opening exciting new possibilities.
Democratization and a New Lens on Defensibility
The collapse in the cost of intelligence has democratized everything—including software development—further accelerated by open-source tools. While this democratization unlocks vast opportunities, competition also intensifies. It may be a land grab, but not all opportunities are created equal. The key is knowing which “land” to seize.
Historically, infrastructure initially attracts significant capital, as seen in the early internet boom. Over time, however, much of the economic value tends to shift from infrastructure to applications. Today, the AI infrastructure layer is becoming increasingly commoditized, while the application layer is heavily democratized. That said, there are still plenty of opportunities to be found in both layers—many of them truly transformative. So, where do we find defensible, high-value opportunities?
Our previous thesis identified transformative technologies that achieved mass adoption, changed behaviour, democratized access, and unlocked unprecedented value. This framework remains true and continues to guide our evaluation of “100x” opportunities.
This shift in defensibility brings us to where the next moat lies.
New Defensibility: Deep Tech Meets Data Network Effects
Defensibility has changed significantly. In recent years, the pool of highly defensible early-stage shallow tech opportunities has thinned considerably, with far fewer compelling opportunities available. As a result, we have clearly entered a golden age of deep tech. AI democratization provides capital-efficient access to tools that previously required massive budgets. Our sweet spot is identifying opportunities that remain difficult to build, ensuring they are not easily replicated.
As “full-spectrum specialists,” TSF is uniquely positioned for this new reality. All four TSF partners are engineers and former startup leaders before becoming investors, with hands-on experience spanning artificial intelligence, semiconductors, robotics, photonics, smart energy, blockchain and others. We are not just technical; we are also product people, having built and commercialized cutting-edge innovations ourselves. As a guiding principle, we only invest when our deep domain expertise can help startups scale effectively and rapidly cement their place as future industry-disrupting giants.
Moreover, while traditional network effects have diminished, AI has reinvigorated network effects, making them more potent in new ways. Combining deep tech defensibility with strong data-driven network effects is the new holy grail, and this is precisely our expertise.
What We Don’t Invest In
Although we primarily invest in “bits,” we will also invest in “bits and atoms,” but we won’t invest in “atoms only.” We also have a strong bias towards permissionless innovations, so we usually stay away from highly regulated or bureaucratic verticals with high inertia. Additionally, since one of our guiding principles is to invest only when we have domain expertise in the next frontier of computing, we won’t invest in companies whose core IP falls outside of our computing expertise. We also avoid regional companies, as we focus on backing founders who design for global scale from day one. We invest globally, and almost all our breakout successes such as Printify have users and customers around the world.
Where We’re Heading
Having recalibrated our thesis for this new era, here’s where we’re going next.
We have backed amazing deep tech founders pioneering AI, semiconductors, robotics, photonics, smart energy, and blockchain—companies like Fibra, Blumind, ABR, Axiomatic, Hepzibah, Story, Poppy, and Viggle—across consumer, enterprise, and industrial sectors. With the AI platform shift underway, many new and exciting investment opportunities have emerged.
The ground has shifted: the old playbook is out, the new playbook is in. It’s challenging, exciting, and we wouldn’t have it any other way.
To recap our core belief, TSF invests in the next frontier of computing and its applications, backing early-stage products, platforms, and protocols that reshape large-scale behaviour and unlock uncapped, new value through democratization. These opportunities are fueled by the collapsing cost of intelligence and, as a result, the growing demand for access to intelligence as well as its expansion beyond traditional computing devices. What makes them defensible are technology moats and, where fitting, strong data network effects.
Ormore succinctly: We invest in the next frontier of computing and its applications, reshaping large-scale behaviour, driven by the collapsing cost of intelligence and defensible through tech and data moats.
So, if you’ve built interesting deep tech in the next frontier of computing, we invest globally and can help you turn it into a product. If you have a product, we can help you turn it into a massively successful business. If this sounds like you, reach out.
P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
A solo musician doesn’t need a conductor. Neither does a jazz trio.
But an orchestra? That’s a different story. You need a conductor to coordinate, to make sure all the parts come together.
Same with AI agents. One or two can operate fine on their own. But in a multi-agent setup, the real bottleneck is orchestration.
Yesterday, we announced our investment in GenseeAI. That’s the layer the company is building—the conductor for AI agents, i.e. the missing intelligent optimization layer for AI agents and workflows. Their first product, Cognify, takes AI workflows built with frameworks like LangChain or DSPy and intelligently rewrites them to be 10× faster, cheaper, and more reliable. It’s a bit like “compilation” for AI. Given a high-level workflow, Cognify produces a tuned, executable version optimized for production. Their second product, currently under development, goes one step further: a serving layer that continuously optimizes AI agents and workflows at runtime. Think of it as an intelligent “virtual machine” for AI, where the execution of agents and workflows is transparently and “automagically” improved while running.
If you’re building AI systems and want to go from prototype to production with confidence, get in touch with the GenseeAI team.
Read Brandon‘s blog post here or in the following for all the details:
At Two Small Fish, we invest in founders building foundational infrastructure for the AI-native world. We believe one of the most important – yet underdeveloped – layers of this stack is orchestration: how generative AI workflows are built, optimized, and deployed at scale.
Today, building a production-grade genAI app involves far more than calling an LLM. Developers must coordinate multiple steps – prompt chains, tool integrations, memory, RAG, agents – across a fragmented and fast-moving ecosystem and a variety of models. Optimizing this complexity for quality, speed, and cost is often a manual, lengthy process that businesses must navigate before a demo can become a product.
GenseeAI is building the missing optimization layer for AI agents and workflows in an intelligent way. Their first product, Cognify, takes AI workflows built with frameworks like LangChain or DSPy and intelligently rewrites them to be faster, cheaper, and better. It’s a bit like “compilation” for AI: given a high-level workflow, Cognify produces a tuned, executable version optimized for production.
Their second product–currently under development–goes one step further: a serving layer that continuously optimizes AI agents and workflows at runtime. Think of it as an intelligent “virtual machine” for AI: where the execution of agents and workflows is transparently and automatically improved while running.
We believe GenseeAI is a critical unlock for AI’s next phase. Much of today’s genAI development is stuck in prototype purgatory – great demos that fall apart in the real world due to cost overruns, latency, and poor reliability. Gensee helps teams move from “it works” to “it works well, and at scale.”
What drew us to Gensee was not just the elegance of the idea, but the clarity and depth of its execution. The company is led by Yiying Zhang, a UC San Diego professor with a strong track record in systems infrastructure research, and Shengqi Zhu, an engineering leader who has built and scaled AI systems at Google. Together, they bring a rare blend of academic rigor and hands-on experience in deploying large-scale infrastructure. In early benchmarks, Cognify delivered up to 10× cost reductions and 2× quality improvements – all automatically. Their roadmap – including fully automated optimization, enterprise integrations, and a registry of reusable “optimization tricks” – shows ambition to become the default runtime for generative AI.
As the AI stack matures, we believe Gensee will become a foundational layer for organizations deploying intelligent systems. It’s the kind of infrastructure that quietly powers the AI apps we’ll all use – and we’re proud to support them on that journey. If you’re building AI systems and want to go from prototype to production with confidence, get in touch with the team at GenseeAI.
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Yesterday was Star Wars Day — aka “May the Fourth be with you” — and it got me thinking, so I put together this blog post.
You might notice my title is “Operating Partner,” not “General Partner,” “Managing Partner,” or “Board Partner.” That’s intentional because I spend most of my time working directly with portfolio CEOs.
The Operating Partner role has its roots in private equity. Historically, Operating Partners are often former CEOs or COOs who use their experience to guide leadership teams, improve operational execution, and drive results, ultimately increasing the value of portfolio companies.
As far as I know, I’m the only former scale-up CEO in Canada who plays this role in an early-stage VC. At least, ChatGPT and Perplexity couldn’t find anyone else! Even in the U.S., this is very rare.
That said, I’ve always felt the “Operating Partner” title is a bit misleading. Unlike many private equity Operating Partners, I don’t step into full-time or part-time leadership roles within portfolio companies. I don’t give advice or directives either. Instead, I help CEOs solve their own problems rather than solving problems for them.
My single objective is to help portfolio CEOs improve the quality of their decisions by leveraging my experience.
Why? Most CEOs don’t need to be told what to do—they already know. Telling a CEO to grow their KPIs faster or hire great people is useless.
No CEO intentionally grows slower or hires bad people!
The real challenge for CEOs isn’t the what—it’s the how. This is where I come in, helping them navigate the how: strategic thinking, future-proofing, and decision-making that drive tangible progress, while staying alert to blind spots that could undermine success.
Hiring is an example. Many venture firms have talent partners who assist portfolio companies with recruitment. These partners, often from recruitment backgrounds, are excellent at sourcing candidates once roles are defined. However, they usually lack deep business context and may not fully understand the culture of the companies they’re supporting. This can result in untargeted candidates who don’t fit. I experienced this issue firsthand when I was a CEO.
That’s why I strongly favour internal recruiters who have an intimate understanding of the business and culture. Even so, recruiters typically get involved after roles are clearly defined. Before that, to design the organization, we need someone who has visibility into the broader perspective of the business. Only one person truly has it: the CEO. Besides, CEOS usually can’t ask their leaders about organizational design for obvious reasons.
That’s where I step in—well before recruiters are involved. I act as a sounding board for organizational design, considering not just immediate hiring needs but also how roles and teams will evolve over time. What level of talent should they hire now? When will this position need to level up? What downstream implications will these decisions have?
By addressing these questions early, I help ensure hiring decisions are aligned with the company’s long-term strategy and culture.
Of course, hiring is just one area where I provide support. Design future-proof stock option plans? Manage internal and external communication challenges? Interact with strategic conglomerates? Navigate inbound acquisition offers? Resolve leadership dysfunction? Handle unreasonable investors? Make board meetings more effective? Fend off super aggressive competitors or internet giants?
And yes, one of the most frequent requests I get is: “Can you help me with my pitch deck?”
Bring them on!
I’ve faced these challenges firsthand multiple times, and when CEOs bring them to me, I’m ready to share my war scars.
At the minimum, I help narrow the options from “I don’t know how” to a set of multiple choices. I don’t make decisions for CEOs; I help them make better ones. They are ultimately responsible for their decisions, and I see my role as a guide, not a decision-maker.
Being the CEO of a fast-scaling company is an enormous challenge that people should not underestimate—the level of experience, capacity, intensity, and mental strength that one needs to cope with. That’s why it is the loneliest job. Empathy is not enough. The best help I ever got was from a more experienced CEO than me at the time — someone who had walked the road ahead — and now it’s my turn to pay it forward. It is payback time for me.
The more I think about it, the less “Operating Partner” seems to fit. I don’t step into the spotlight or take over operations. My role is more like Yoda—helping Skywalker fight the battles while staying behind the scenes.
So perhaps my title shouldn’t be Operating Partner after all. Maybe it should just be… Yoda.
May the Force be with you!
P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
