As a member of the first PC generation, I vividly recall the days of owning my IBM clone XT with its dual 5 ¼ inch floppy drives while pursuing my computer science studies. Back then, we, the early PC users, witnessed the rise of countless companies, some of which became giants like Intel and Microsoft, while others failed to reach significant heights.
In the realm of PC software, there were numerous trends to keep an eye on, including accounting, spreadsheets, personal databases, and various programming language and tools companies. However, the real key to success for the major players lay in the underlying tech platform of the PC. Surprising contenders like Seagate Technology, Dell Technologies, and Foxconn emerged in the hardware layer, thanks to their alignment with the PC architecture.
In my research paper "Is SaaS Disruptive," authored in 2007, I discussed how Software-as-a-Service (SaaS) companies like Salesforce followed a classic disruptive innovation framework. They attracted market share by offering cost leadership, reaching non-consumers, disrupting traditional distribution channels, and moving up the value chain. Through vertical integration of hardware, software, and services, combined with the ubiquity of the Internet and web browsers, these companies triumphed over incumbents like SAP and Oracle in key enterprise software segments such as customer relationship management (CRM). SaaS firms, with their vertically integrated strategy, lower transaction costs, reduced agency risks, and shared infrastructure through multi-tenant server architectures, provided CIOs with alternative enterprise solutions while creating wealth for shareholders. (Fun fact: Investing in Salesforce when my paper was published would have yielded a 16x return, with shares rising from $14 to $225.)
So, how can we apply similar disruptive frameworks to current trends in the tech industry, especially during a startup's early stages? The key is to identify disruptive forces at play. While AI garners significant attention, it is merely a tool used by software developers (builders) to create better software. Other noteworthy tools in the spotlight are the API economy and autonomous web3 software, which represent alternative ways of building software.
These differences can disrupt incumbent players by opening up new product opportunities. Take the "builder-as-the-buyer" paradigm. The driving force behind technology purchases within companies is often the builders themselves. For instance, when dealing with AI models, decisions are likely to be made by data science teams rather than CFOs.
Alternatively, companies may opt for AI-as-a-Service products, many of which will emerge in the market. These products will be composable and API-based, making them excellent investment opportunities for those willing to seek them out. Companies like Stripe, Twilio and OpenAI have followed this trend. New players such as FrankieOne and SourseAI are the trail blazers in the markets that I specialise in, APAC.
In conclusion, to excel in early-stage tech investing, it is crucial to identify the disruptive trends and emerging technologies in the software development landscape. By focusing on innovative approaches like the API economy and autonomous web3 software, investors can discover promising startups that have the potential to disrupt the industry and generate significant returns. Happy hunting!
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