The Ownership Economy: Crypto & The Next Frontier of Consumer Software – Variant

The Ownership Economy: Crypto & The Next Frontier of Consumer Software – Variant

In today's digital landscape, the concept of ownership is taking on new meaning. With the rise of cryptocurrencies and blockchain technology, individuals are now able to not only participate in the creation and operation of software platforms but also own a stake in them. This shift towards user ownership is a powerful motivator for users to contribute to products in deeper ways, whether it be through ideas, computing resources, code, or community building.

Traditional internet platforms often prioritize the economic interests of their founders and investors, leading to misalignment with their most valuable contributors – the users. However, user ownership models help ensure better alignment over time, resulting in larger, more resilient, and more innovative platforms. By allowing users to earn the majority of the value generated from their contributions, platforms like Bitcoin and Ethereum have successfully harnessed the power of user ownership.

The history of protocol adoption follows a pattern where early adopters leverage new technologies to do things that were previously impossible. To drive widespread adoption, founders should focus on building products that make these new models more accessible to a wider audience. By creating products and protocols that offer better economic alignment with users, startups can bootstrap adoption and participation.

On the other hand, the rise of artificial intelligence (AI) is transforming the creation and distribution of content. Just as the internet eliminated distribution costs, AI is pushing creation costs towards zero. The economic value derived from AI is not distributed linearly along the value chain but is subject to consolidation and power law outcomes among infrastructure players and end-point applications.

While many AI models train on similar data sets and the underlying math is widely available, compute power becomes the differentiating factor. Any company with sufficient skills and resources can build a copycat AI model. However, the real differentiator lies in factors such as developer community, ease of use, UI/UX, and network effects around the ecosystem.

Open source also plays a significant role in the AI landscape. It exerts downward pricing pressure on model providers who sell access to their models via API. Competing with free forces companies to compromise by being cheap. In the long run, model differentiation comes from data-generating use cases, and AI startups often turn into consulting shops rather than SaaS companies.