The majority of platforms we use today that are "free" leverage a form of data monetization to generate revenue. Social media enables the monetization of ultra-targeted ad space from the data gathered from platform users. Tesla collects almost every form of user input for the purpose of their proprietary algorithm training and development. Tesla knows who their users are, where they're going, and how they're using their cars to iterate on products in ways previously impossible.
Our world today is defined by data. Our ability to collect and store large amounts of data is what enables us to learn from our mistakes and avoid repeating them. Companies have figured out that they can monetize this data for consumption by others.
The development of AI and AGI enable mankind to make sense of data in novel ways at scale. Technologies like Stable Diffusion and chatGPT opened doors for us to work more efficiently, entirely powered by the data we, ourselves, put on the web.
Produce to compose.
Web1.0 enabled the reading (consumption) of data on the internet. Web2.0 enabled anyone to write (produce) data on the internet. I am not convinced the revolution of Web3.0 is about owning things; I think it's more uniquely suited for composing them.
Composability involves blurring the line between applications and protocols. The best protocols are designed to facilitate permissionless innovation, while the best applications enable permissionless usage. At its core, composability is the idea of creating reusable "Lego bricks" of software that can be integrated as tools within other applications. This approach allows developers to build on top of others' existing functionality, resulting in greater efficiency and scalability. No-code solutions will eventually enable anyone, not just engineers, to produce anything thanks to composability. The more ways we're able to make use of the data we've gathered, the more things we can both produce and consume for the purpose of iterating and evolving as a species.
Open source software is a great example of how composability can be applied to accelerate innovation in software development through package managers and protocols like Git.
Ethereum enables permissionless innovation through the composition of smart contracts. This was made possible by having applications share a compute layer (a type of data layer) and an identity standard (a universal way to interact with the applications). Ethereum also offsets operating costs to end users in the form of transaction fees, removing barriers of entry for developers to build on top of. It seems that many of the most robust financial products and tools were built on Ethereum because of these factors. As of today, nearly all blockchains are focused on enabling, accelerating, and scaling this in finance. This makes sense because many of the clearest use cases for composability currently exist in finance, paired with the economic upsides of building in close proximity to capital in the financial sector.
What I find more interesting, however, is the idea that most are not considering applying these mechanics to many other types of data yet.
This is because most blockchains, where things are composed, are not optimized for the storage of arbitrarily-sized data. Off of blockchains, individuals and organizations don't share aligned incentives for the perpetual storage of data, which can result in sources disappearing at random. People who contribute data to composable systems often have to pay for its storage rather than being rewarded proportional to the value of the contribution. As stated above, our world today is largely driven by the siloing of data, not the sharing of it.
Consider this my thesis on Arweave: Permanent data storage disguises the underlying potential for dynamic and composable protocols, facilitating faster, easier, and more scalable software development. With Arweave, leveraging, extending, or iterating on any data is permissionlessly available to anyone, at any time.
While the long term effects of permanent data storage on our world are uncertain, I am certain that this will switch focus back to individuals contributing valuable data to applications, rather than applications privately extracting valuable data from their users. It also creates new opportunities for developers to incentivize the contribution of data.
With this in mind, the game becomes making it simple to build on top and answering questions about the long-term defensibility of these solutions when data alone is not a sufficient moat.
Regardless, innovation occurs at the intersection, or composition, of two subjects. The easier we make it to innovate, the more innovations we'll see. The more we innovate, the more there is to innovate atop.