When Two Small Fish first started in 2015, we formulated our “Thesis 1.0” to focus on network effects exclusively. We leveraged our hands-on product experience in scaling Wattpad from 0 to 100 million users—essentially a marketplace for readers and writers—and applied a similar lens to other verticals, both in B2C and B2B.
It worked incredibly well for TSF because, at the time, network effects were the holy grail for defensibility, yet they were often misunderstood (for example, going viral is not the same as having network effects, and simply operating a marketplace does not guarantee strong network effects!). Our skill is more transferable than you might think!
So, Eva created the ASSET framework, which helped us identify the best network-effect investment opportunities and, more importantly, helped entrepreneurs understand and increase their network effect coefficient—the measure of true network effects—and ultimately embed strong network effects into their products. In short:
• A stands for “atomic unit”
• S stands for “seed the supply side”
• The other S stands for “scale the demand side”
• E stands for “enlarge the network effect” or “enhance the network coefficient”
• T stands for “track proprietary insights”
This framework provided a simple yet systematic way to judge whether a company truly had network effects or merely the illusion of them.
However, toward the end of the last decade, it became increasingly difficult to find investable network-effect opportunities. Well-established incumbents already had very strong network effects in place, effectively setting the world order. It became exceedingly difficult for emerging disruptors—both in consumer and enterprise spaces—to find a gap to break through.
We began looking for other forms of technology defensibility (for example, semiconductors) and gradually moved away from “shallow tech” network-effect investments, as we found very few investable opportunities. In fact, our last shallow tech investment was made about three years ago.
Then, in late 2022, ChatGPT arrived.
As the world now understands, generative AI is the first technology in human history capable of learning, reasoning, creativity, cross-domain functionality, and decision-making. It’s the most significant platform shift since mobile, social, and cloud computing in the late 2010s—and arguably the biggest one in human history. It also means the playing field has been leveled. Today, there are numerous ways to create new products with powerful network effects that can render incumbents’ offerings obsolete (for example, I haven’t used Google Search regularly for a long time) because newcomers can disrupt incumbents from all three angles: technology, product, and commercialization (e.g., business models). Incumbents are vulnerable!
On the other hand, the ASSET framework also needed a refresh, as we’re no longer dealing with simple, well-understood marketplaces. What if one side of the marketplace is now AI? Even though our original framework was designed to handle data-driven network effects, the speed and scale of data generation have multiplied by orders of magnitude. How does this affect enlarging the network effects and increasing the coefficient?
The good news is that there are now ways to massively increase the network effect coefficient in a remarkably short time. The bad news is that all your competitors—large or small—can do the same. Competition has never been fiercer.
After ChatGPT was released, we quickly revised our ASSET framework to version 2.0. Since then, we’ve been guest-lecturing this masterclass worldwide for well over a year. By fully leveraging AI’s creativity and reasoning capabilities, entrepreneurs can now harness human-machine collaboration to supercharge both the demand and supply sides, blitz-scale, and create new atomic units. Here’s the gist of 2.0:
• A – Atomic Unit of Product
• S – Super Seed the Supply Side (now amplified by Gen AI)
• S – Supercharge the Demand Side (now leveraging Gen AI)
• E – Exponential Engagement (using the human + AI combo)
• T – Transform Business with New AI-powered Atomic Units
Like 1.0, this new framework is easy to understand but difficult to master—and it’s even more complex now because, with Gen AI, it’s non-linear. Our masterclass covers the lecture material, but the real work happens in our private tutoring, where execution matters—and this is how we help our portfolio companies win.
The old network effect is dead. Thanks to the AI platform shift, network effects are roaring back in a different and far more potent way in the new world order. The combination of deep tech defensibility plus network effect defensibility is the new holy grail—and we are specialized in both.
With the AI platform shift, all of a sudden, there are many new investable opportunities that didn’t exist before. At the same time, the ground has shifted: the old playbook is out, and the new playbook is in. It’s exciting; we love the challenge, and we wouldn’t have it any other way.
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