Dagdao is a DAO collaboration mechanism characterized by openness, agility, and efficiency. Currently, Dagdao is still in the ideation stage, with some key issues unresolved, and we need to find a suitable way forward.

Background

DAO stands for Decentralized Autonomous Organization, where the members can be likened to nodes in a network. However, compared to nodes in a blockchain, human participants are undoubtedly more complex, leading to the complexity of collaboration within DAOs. For simplicity's sake, we describe the functionality of DAO as follows: participants collaborate to complete a task. In this context, several questions arise:

1. Is the task worth completing?
2. Are the collaborators reliable?
3. What do participants gain upon completion?
4. How do we evaluate the task's progress?

Typically, we can address the complexity of collaboration within DAOs by introducing delegated agents. Delegated agents serve as intermediaries and decision-makers who assess the value of tasks, evaluate team capabilities, ensure appropriate rewards and incentives, and oversee task execution and evaluation. This mechanism helps improve collaboration efficiency, reduce risks, and promote the development and success of DAO organizations. This committee-based mechanism is commonly used in DAOs and its effectiveness depends on the competence of the committee members.

However, the committee-based model has limitations as it demands high requirements from committee members. They need to understand various types of information, possess insights, execution capabilities, etc., and evaluating a project incurs significant costs. Therefore, an excellent committee usually has a small radius of service.

Another solution is decentralization, which is adopted by many DAOs. For questions 1 and 2, community discussions, proposals, and voting mechanisms are often employed. However, Dagdao focuses on addressing questions 3 and 4. Some DAOs evaluate participants' contributions and project completion by defining detailed metrics. Yet, quantifying contributions is challenging, as explained by Goodhart's Law. If we decentralize everything and rely on the community without detailed evaluation criteria, new problems arise: How can we prevent collusion? How can we prevent negative work attitudes? How can we prevent bribery?

Dagdao is a mechanism that aims to solve the delegation agent problem within DAOs in a decentralized manner while reducing collaboration costs among DAO members.

Solution

1. Users stake the skills of the target users, forming a skill pool for the target user.
2. When a user's skill pool exceeds the cost of a project under review and shares the same semantic label, they can initiate a "peer review" of that project. At this time, the Skill Pool will lock funds equivalent to the cost of the project under review.
3. After the peer review is completed, the project enters a pending state, awaiting reference reviews from other projects. In other words, when publishing a review, one needs to roughly review several other projects first, assuming 10% responsibility. This approach draws inspiration from DAG (Directed Acyclic Graph) consensus in blockchain to ensure the discoverability and thorough review of each project.
4. When the pledged review funds for a project exceed a certain threshold, the system will distribute funding to the project party after a specified period.
5. Any misconduct during this process will result in the confiscation of the staked ORS (Responsibility Sharing) tokens, such as incorrect reviews or collusion.
6. Evaluate project performance within the agreed retrospective period and provide additional rewards to trustees and label staking pools.

Drawback