Forget DAOs, we need autonomous, real-time reporting for decentralized blockchain networks 

Let’s humor ourselves a bit. 

In a previous blog post, an SEC conundrum was exposed about expected disclosures meant to protect the consumers: if decentralized protocols have no central teams, who would be responsible for preparing and providing disclosures to the public? 

Of course, the extreme case of centerless decentralized blockchain consensus protocol is Bitcoin, closely followed by Ethereum. 

Transparency and disclosures are important. It’s a point the SEC has been harping on, and rightfully so. It is one of the key tenets of their raison d’être, “to require public companies, fund and asset managers, investment professionals, and other market participants to regularly disclose significant financial and other information so investors have the timely, accurate, and complete information they need to make confident and informed decisions about when or where to invest.” The objective of such disclosures is to prohibit deceit, misrepresentations, and other potential fraud.

Unfortunately, for many token-based projects, even some of the popular and centrally-managed ones, there are no transparency reporting standards, let alone plain transparency, or even any formal reporting. Information opacity and dissymmetry abound. 

However, most blockchain protocols have a variety of performance & operations-related dashboards and blockchain explorers that are rich with data, analysis, historical trends, and a variety of publicly or privately assembled valuable information. 

What if there was a way to string these information sources together intelligently, pluck out the most relevant data into a meta layer of sorts, and make that available in a format that would be digestible for interested “investors” or “token holders” and would give them an informed and accurate view about the network performance in a normalized manner?

Let’s take this concept further. 

That first meta layer could be fed into an AI layer that creates the narrative around the data.

Then, one could feed that narrative in a text-to-speech conversion later, and make that available to anyone who wants to obtain a voice update on how a particular project is doing. 

And since everything is real-time, that process could run as a continuous loop, and it could even be provided on-demand, at any point in time. 

Finally, another AI-driven query layer would be able to take human prompts and generate the right responses. 

There we have it. Autonomous reporting. There is no need for end-of-quarter reporting in blockchain networks. They run non-stop, so their performance indicators should be read non-stop. 

We have been advocating DAOs for a while, with no visibly spectacular examples to point to. 

How about we start with Autonomous Reporting?