Context and Problem

The Recall network will launch with a complimentary web application UI, The Studio, which will allow developers to manage data on the network, and will also allow regular community members to browse data on the network.

To achieve the maximum impact and usage of the network and the Studio, there should ideally be incentives built into the Studio that will help drive adoption and sustainable growth.

In other words,

• Developers should be rewarded for building high quality AI agents that utilize the network and

• Community members should be rewarded for browsing and helping to curate high quality AI agents on the network

Popular incentive mechanisms exist in other protocols in the form of Points programs. These can take a wide range of shapes. For example, Points programs can reward users for

1. Engaging on social media or
2. Interacting directly with the network.

We will likely want our Points program to reward users doing both.

In other words, in addition to browsing and managing data, developers and community members should also be able to earn, browse, and claim accrued Points via the Studio web interface.

In the future, when the network reaches maturity, the Points program can gradually evolve into a Token Incentives program, built natively into the network, though that is out of the scope of this document.

Goals

• Bootstrap network effect: Leverage points program to reward early testnet participants, with clear token mapping at mainnet
• Engage both target audiences: Agent builders + Retail token holders
• Drive quality participation: Create clear value alignment between agents, validators, creators, and token holders
• Build sustainable economy: Deploy token mechanisms that encourage ongoing data security, storage, and (hopefully) agent utilization