The Ownership Economy: Crypto & The Next Frontier of Consumer Software – Variant
Hatched by Kazuki Nakayashiki
Jul 12, 2023
4 min read
5 views
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.
When it comes to AI adoption, rapid success is often followed by the emergence of copycats. The purchasing decision is driven more by go-to-market (GTM) strategy and sales and marketing prowess than pure vendor comparison. AI becomes a marketing tool, and the winners are determined by software questions rather than AI capabilities.
For startups competing in the SaaS space, the advantage lies with companies that already possess inherent distribution or product capabilities. Integrating AI into existing products is easier for large companies than building competitive full-suite AI products from scratch.
In a world where content creation is essentially free, distribution becomes the key differentiator. Creators who leverage AI tools to produce better content at a faster pace will be able to build a critical mass of fans. However, the digital media landscape already exhibits a dynamic where only a small fraction of creators capture the majority of revenue, and AI will further exaggerate this disparity.
Finally, the concept of invisible AI is gaining traction. Companies are utilizing AI to create products that were previously unimaginable, without explicitly mentioning the use of AI. These products delight users by offering something truly unique and innovative, all thanks to the power of AI.
In conclusion, the ownership economy and the rise of AI are shaping the future of consumer software. User ownership models in the cryptocurrency space are fostering better alignment between platforms and users, leading to larger and more innovative platforms. On the other hand, AI is revolutionizing content creation and distribution, allowing creators to reach new heights in terms of quality and speed. To thrive in this evolving landscape, startups and companies must consider factors such as economic alignment, distribution capabilities, and leveraging AI tools effectively.
Actionable Advice:
- Embrace user ownership: Consider incorporating user ownership models into your software platforms to ensure better alignment with users and foster innovation.
- Focus on distribution: In the AI space, prioritize distribution capabilities and go-to-market strategies to outperform competitors. Distribution is often the key to success.
- Leverage AI effectively: Explore AI tools and technologies to enhance content creation and distribution. Utilize AI to create unique and delightful experiences for your users.
By understanding the potential of the ownership economy and the transformative power of AI, businesses can position themselves at the forefront of the next frontier in consumer software.
Sources
Hatch New Ideas with Glasp AI 🐣
Glasp AI allows you to hatch new ideas based on your curated content. Let's curate and create with Glasp AI :)
Start Hatching 🐣