The emergence of large language models (LLMs) has made it increasingly difficult for businesses to create a pure technology moat. The lower barriers to entry in introducing new products to the market and the constant fear of becoming outdated overnight have made it challenging for existing businesses, startups, and investors to find a path to a sustainable competitive advantage.
A Different Kind of Moat
However, this new landscape also presents an opportunity to establish a different kind of moat, one based on a much wider product offering that solves multiple pain points for customers and automates large workflows from start to finish. The AI explosion, whose blast radius has kept growing since the public launch of GPT3.5/ChatGPT, has been mind-blowing. Businesses in the space are struggling with the realities of creating a defendable product with substantial entry barriers for new competitors or incumbents.
The Democratization of AI and Software
The real revolution also includes open-source models becoming available for commercial use and solutions such as LoRA, which allow anyone to retrain open-source models on specific datasets quickly and economically. The democratization of AI and software means that businesses can listen to their customers on a much broader scale and deliver wide products that solve multiple pains that seemed unrelated only a year ago. When combined with integrations that fully automate customers’ workflows, businesses can achieve a sustainable competitive advantage.
Building a Wide Product
By building a wide product instead of one focused on a single feature, startups can achieve a mythical moat. It simplifies product adoption, creates further barriers to entry, and safeguards against new open-source models that could be released and tear down a business overnight. For example, in the AI transcription market, several providers were in this market with similar price levels and relatively nuanced product differentiations. Suddenly, this seemingly sleepy market was rattled when OpenAI released Whisper, an open-source ASR, which showed immediate potential to disrupt the market but with some substantial gaps.
The incumbents in the market, who faced the above dilemma, decided to each launch a new proprietary model and focused some of their messages on the problems of Whisper. At the same time, others found ways to close these gaps and market a superior product with limited R&D efforts that are receiving incredible enterprise customer feedback and an entry point with happy customers.
Businesses can build rich offerings and, in time, compete head-to-head with market leaders by having the right product vision, agility, and execution. Many of the core principles needed to identify great startups are already inherent in the minds of VCs who understand what it takes to recognize opportunities and grow them accordingly. It’s critical to recognize that today’s castles look different than they did years ago. What businesses protect is no longer the crown jewels, but the whole kingdom.
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