When will DAOs overtake Traditional Orgs?

With exponential learning, Efficiency Parity might be sooner than we think

Top Reading Summaries

Here are some timely pieces about the DAO ecosystem, along with our top highlights from each one.

1. The Dao of DAOs — Not Boring

Packy McCormick introduces DAOs and their history. If you’re just scratching the surface of learning about DAOs, this is the perfect place to start.


  • DAOs are a new way to finance projects, govern communities, and share value.

  • The first DAO launched on Ethereum April 30, 2016. It raised $150 million from 11k people. Then, it was hacked 6 weeks after launch, which was so substantial that it caused the Ethereum community to reset the network with a hard fork.

  • In contrast to traditional organizations, DAO structures incentivize protocols and platforms to remain interest-aligned with stakeholders over time.

2. What is a DAO? Mapping Out the Ecosystem — The Defiant

Kevin Nielsen describes the importance of DAOs, the different categories of DAOs, and the stack of tools be used to build them. Plus: killer diagrams.


  • Categories of DAOs include: Protocol, Project, Investor, Creator, Curator, Community, Guild

  • Protocols have the most traction right now, expanding on the success of DeFi. The decisions that these DAOs need to make are easier to automate, given the objective nature of adjustments to financial parameters.

  • There's already a variety of tools being used to create and run DAOs, including options for DAO Frameworks, Controllers (UIs), Treasury Management, and Decentralized Collaboration

3. Wyoming DAO Bill passes — Aaron Wright (twitter thread)

Aaron Wright (Professor at Cardano Law and Co-founder of The LAO, a venture capital DAO) writes about the implications on Bill 38 passing in Wyoming.


  • Starting July 1, you can register a DAO as a new kind of legal entity in Wyoming that is similar to an LLC. WY is the first state to pass this type of legislation.

  • There is no restriction in the statue about the management of these DAOs. They can be flat and democratically managed or algorithmically managed.

  • The long-term vision: anyone can set up a legally recognized DAO from the command line (via API) for less than $1k.

This Issue’s Main Takeaway

These are the biggest learnings from our recent research on the DAO ecosystem and decentralized governance.

Governance structures are an open challenge for DAOs

Every DAO we’ve talked to or heard about is thinking about governance right now. Here are four major themes of problems within DAO governance:

  • Opportunity to draw knowledge from other fields. There is a huge amount of knowledge in the history of governing human organizations, politics, and economic incentive design. However, much of this still needs to be synthesized and incorporated into the design of governance experiments that DAOs will conduct. It should and will be a widely multi-disciplinary effort, but isn’t there yet.

  • Low Voter Participation is an acute pain point. Many people (especially investors) have tokens that grant them voting power, but they are not reading DAO proposals or voting on them. On the micro level, this means the incentive to vote is not outweighing the opportunity costs. On the macro level, I’m guessing that the existing mechanisms for distribution of voting power are not efficient yet.

  • How much decentralization, and when? Although DAOs have “decentralized” in their name, they are figuring out how much decentralization is right for them, and at what milestones. There’s a fantastic playbook on “progressive decentralization” from a16z, and it’s been expanded on by founding teams in the space. But ultimately, getting off the ground takes concerted effort from a small number of people, which feels a lot like a centralized startup. Navigating the precariousness of decentralizing at the right time, while updating governance structures along the way, will be a challenge to many DAOs.

  • Fair compensation based on value created. Many DAOs are evolving models of how to pay their members. Compensation standards currently consist of grants (voted on and paid out before work is completed) and bounties (voted on and paid out after the completion of work), and is typically made up of tokens, reputation, and voting power. The challenge is around measuring how much value a member creates from their work, especially if it is small or hard to quantify. This is stacked on top of a wicked problem in all organizations: how to measure skills. I anticipate seeing some very interesting experiments in this space in particular.


The Efficiency Parity Hypothesis

The crypto ecosystem has been talking about DAOs since 2014. DAOs are even highlighted in the Ethereum whitepaper. But how will we know when they are ready for prime time?

I think the most important dynamic to look at is how efficient DAOs are at accomplishing their goals in comparison to traditional organizations (TradOrgs). Secondarily, I would look at the Learning Rate for each of these types of organizations.

There are three properties of DAOs that stand out to me as I reason about their Learning Rate:

  1. Experimentation Rate: Following lots of activity in DeFi and NFTs, there’s a lot of new capital in crypto that people are excited to put to work. DAO experimentation is attracting that capital. Simultaneously, the tooling and infrastructure to launch DAOs (as mentioned in the piece from The Defiant above) is becoming increasingly robust, making DAOs less expensive to launch.

  2. Propagation of Successful Experiments via Forking: The ecosystem of crypto protocols is largely open-source, both technologically and philosophically. Across currencies and DeFi, we have already seen forks of massive projects (e.g. Bitcoin → Bitcoin Cash; Uniswap → Sushiswap). These forks have been able to take what works, make opinionated changes, then quickly attract capital and usership. The same dynamic will play out in DAOs for governance and compensation structures. This means successful DAO experiments will spread across the ecosystem quickly, and fewer projects have to fail in order to achieve a high Learning Rate.

  3. DAO Ecosystem Network Effects: Much like a Web2 marketplace or platform, DAOs have internal network effects. But unlike Web2, interoperability is a core philosophy of many DAOs. For example, there are a number of DAOs that allow you to gain membership either as an individual or as another DAO. Today, DAOs are holding each other’s tokens, working on each other’s infrastructure, and partnering to build projects. This leads me to believe that the network effects of the DAO ecosystem will be even more robust than what we’ve seen in Web2.

These three factors add up to an exponential Learning Rate for DAOs. The DAO Ecosystem is a network of networks that is highly capable of propagating and utilizing the latest knowledge created anywhere in the network.

In contrast, the Learning Rate for TradOrgs seems to be linear growth at best. Sure, companies today learn quickly about how to operate their particular business. But there isn’t rapid iteration in these TradOrgs in organizational design, decision-making, or compensation. The Learning Rate for TradOrgs is more like the pace of organizations undergoing Agile Transformations (years), or slowly cycling in and out of the S&P500 (decades).

The organizational efficiency of linear growth TradOrgs will be overcome (quickly) by exponential growth DAOs. I call the moment when this happens “Efficiency Parity.”

This is why it’s interesting to dig in and learn about DAOs now — we are still pre-Efficiency Parity.

Before Efficiency Parity, there is an opportunity cost associated with choosing to operate as a DAO instead of a TradOrg. As such, the people starting DAOs now are either: 1) philosophically aligned with DAOs, 2) betting on the future of DAOs, or 3) enabled by DAOs to do something they otherwise couldn’t.

However, as we approach Efficiency Parity, it will make more sense for more organizations to be DAOs. And my guess is that soon after, it will make very little sense to be anything but a DAO, for most organizations.

It’s hard to say how long this will take, but it seems to me like we’re on the precipice of a Cambrian explosion of organizational experiments. And I’m very excited for what’s to come.

Thanks for reading!

We’re just ramping up, so please reply with your feedback. Coming in Governors #2: the history of DAOs, a breakdown of current best practices, and featured DAO profiles.