Beyond the AI Dead Zone
The AI Dead Zone 1: “Wrappers”
Some AI builders boast about their technology, but in reality, most AI apps face a challenging landscape. Within a 2-4 month window, they must establish a competitive moat to differentiate themselves from competitors who can rapidly copy their innovations. And, a single tweet from Sam Altman about the next release can eradicate their market.
These ‘wrappers’ around existing platforms often carry significant platform risk, because the core value stems from the underlying APIs rather than the startups’ unique offerings. As major platforms flex their muscles—leveraging vast infrastructure, data, and capital—they can easily expand features, potentially rendering these wrapper startups obsolete.
Wrappers with App Layer Data Loops
There’s still room for optimism. While large models have made significant inroads into the application layer—such as Adobe-Odyssey, ChatGPT-Canvas-Cursor, and ChatGPT-Grammarly—startups can still carve out a competitive edge by creating unique data loops at the application level.
By developing deep expertise in niche industries or specific use cases, startups can leverage domain knowledge to establish a sustainable competitive advantage through innovative data loops.
Ask these:
- Does this AI application have unique and direct access to untapped data?
- Can your app convince users to legally opt in to provide their data, and is that data being refined and improved?
- For B2B, do they have exclusive contracts that grant them market superiority? A unique defensive data moat that no one else can replicate.
The essay is still in process and will be released on 11/20.