Serious People: Proposed KPIs for Arbitrum Grant Programs (LTIPP)

Grants Discussions
21

Yes
Very nice :+1:
Mooreā€¦

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Very interesting thread.

I believe that, in case, projects self report they should be incentivized to provide multiple estimates. For example, worst case and best case scenario estimate. And the average or median gets plugged into the formula.

This should provide room for human error and uncertainty that @thedevanshmehta mentioned in a slightly different context.

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First - we would like to thank everyone for all the kinds words, positive feedback and constructive criticism on this post. When we initially posted this to kickstart the KPI conversation (as we noticed it was a hot topic on calls, but didnā€™t have a tangible framework being worked on) we were not expecting this much feedback and engagement!

Seeing everyone build on this idea we started is incredibly exciting and rewarding. Itā€™s also the whole point of DeFi in our eyes and something we highly value at Serious People, for everyone to come together with different pieces of the puzzle and collaborate to build something beautiful. This has really made us feel like Arbitrum is a home and a place we want to continue to invest time into as we deeply believe this DAO can be #1 in the next bull run. We are thrilled to continue to be a part of this growing ecosystem!

With that - we want to propose taking all of the above to a working group to try and punch a first cut over the finish line together as LTIPP is quickly approaching. All are welcome, we are tagging as many people as we can (it limits at 10) who interacted wit this post to hopefully engage further on this call together

@thedevanshmehta @paulsengh @aj_eth @shutsuwei @danielo @maxlomu @Englandzz_Curia @DisruptionJoe @pfedprog @sajjad_sbr

Please invite anyone else who you think would bring value to this conversation!

Meeting Details

Arbitrum KPI Working Group
Thursday, January 18 Ā· 18:00 ā€“ 19:00
Time zone: UTC-0

Google Meet joining info
Video call link: https://meet.google.com/snv-phck-adw
Or dial: ā€Ŗ(NL) +31 20 708 8560ā€¬ PIN: ā€Ŗ770 706 312 0921ā€¬#
More phone numbers: https://tel.meet/snv-phck-adw?pin=7707063120921

PS - if we skipped some process by pushing this to a working group please let us know! Was not our intent and we are happy to comply with the proper order of operations. Our main goal is simply to drive tangible output and with the LTIPP fast approaching we need to keep moving on this.

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24

I completely agree,Very wise approach .projects self report they should be incentivized to provide multiple estimates.

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I think this is worth moving forward. We, Plurality Labs, are waiting for our milestone 2 proposal to begin working group grants. You can also put up a proposal directly to the DAO. I really like the idea of separating the operations/executive function of a long term incentive program from the analytic component.

The issue with the current LTIPP for anything past a pilot is that by bundling the research and oversight payments in with the incentives and operational cost we create a perverse incentive.

Iā€™m very supportive of this effort to define objective functions.

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Thank you for the invite, I have added to my calendar and look forward to chatting this Thursday

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Optimizing Long-Term Incentive Allocation in Arbitrum: A Synergistic Approach Using Grant Ships and Numerai Frameworks

Abstract:

This research paper explores the integration of the innovative mechanisms from Grant Ships and Numerai into the Long-Term Incentives Pilot Program (LTIPP) proposed for Arbitrum. Our focus is on optimizing the allocation of LTIPP incentives to foster sustainable growth and value creation within the Arbitrum ecosystem. We propose a model where data scientists compete to develop AI algorithms that effectively allocate LTIPP funds, ensuring long-term benefits over short-term gains. This approach is critically evaluated against the backdrop of the proposed Key Performance Indicators (KPIs) for Arbitrumā€™s user incentive grant programs.

1. Introduction

1.1 Grant Ships

Grant Ships introduces an ā€˜evolutionary grants gameā€™ within a DAO framework, where subDAOs, termed Grant Ships, compete to allocate capital efficiently. The effectiveness of these Grant Ships is gauged through community votes, rewarding successful strategies with additional capital for subsequent rounds.

1.2 Numerai

Numerai represents a paradigm shift in hedge fund management, utilizing crowdsourced AI models for stock market predictions. Data scientists globally contribute models built on obfuscated data sets, with performance directly influencing rewards based on how well their algorithm performs in simulated stock market trading of a long/short neutral fund.

1.3 LTIPP for Arbitrum

The LTIPP for Arbitrum seeks to distribute incentives to protocols built on the Arbitrum network. This program aims to address the limitations of short-term incentive programs by establishing a sustainable, long-term framework.

2. Proposal: Integrating Grant Ships and Numerai Mechanisms in LTIPP

Our proposal involves leveraging the competitive and collaborative elements of Grant Ships and the AI-driven, crowdsourced model of Numerai to optimize the LTIPP allocation process.

2.1 Objective Function and KPIs

Drawing from the ā€œProposed KPIs for Arbitrum Grant Programs,ā€ we suggest a multi-faceted objective function that encompasses user acquisition, liquidity measures, volume generation, sequencer fees, and innovation indices.

2.2 Mechanism Design

Data scientists would compete to develop models that predict the most effective allocation of LTIPP funds based on the predefined KPIs. These models would be evaluated periodically, with successful strategies receiving more data or computational resources.

3. Methodology

3.1 Model Development

Participants will access a dataset representing various aspects of protocol performance on Arbitrum, anonymized to focus purely on pattern recognition and predictive accuracy.

3.2 Evaluation and Reward Structure

Model effectiveness is measured based on the Return on Emissions (ROE) metric, aligning with the LTIPPā€™s KPIs. This approach ensures a focus on long-term ecosystem health and value creation.

4. Analysis

4.1 Expected Outcomes

The integration of Grant Ships and Numerai frameworks is anticipated to lead to more efficient and impactful allocation of LTIPP funds. This method encourages innovative approaches while aligning with the overall objectives of the Arbitrum ecosystem.

4.2 Challenges and Considerations

Challenges include ensuring data integrity, maintaining a fair and transparent evaluation process, and aligning diverse stakeholder interests. A robust governance structure is crucial to address these challenges.

5. Conclusion

The proposed integration of Grant Ships and Numerai mechanisms into the LTIPP represents a novel approach to decentralized fund allocation. By leveraging competitive AI model development aligned with strategic KPIs, this methodology promises to enhance the long-term effectiveness and sustainability of the LTIPP in the Arbitrum ecosystem.

6. Future Work

Further research is needed to refine the model, develop more comprehensive datasets, and explore additional KPIs that could enhance the LTIPPā€™s effectiveness.

Acknowledgments

We acknowledge the contributions of the Serious People team, the Arbitrum community, and various working groups for their insights and foundational work in developing the KPI framework and LTIPP proposal.

Note: This paper serves as a conceptual framework, combining elements of the discussed projects for academic exploration. It does not represent an implemented solution but rather proposes a theoretical approach for optimizing LTIPP incentives.

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This is a work of art

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