Hi everyone! My name is Paul Sengh, and I’m a contributor to Delta One (deltaone.xyz).
Thank you to the Steakhouse team for a well-written post to motivate further research on optimizing incentive design. We’ve had a number of fruitful discussions with the team over the past month, and they have done a fantastic job of approaching this core problem. The current incentive budget is a substantial expenditure for the DAO, and primarily stems from subjective decision making rather than quantitative analysis.
First and foremost, liquidity incentives should do more than rent liquidity. They prove to be most effective at bootstrapping a network, but the core product-market-fit of the DAO should sustain the network. Given that 95% of incentives are dumped within 6 months, we fully support the claim around weaning off LDO incentives for established pools, such as Curve’s stETH-ETH. If the Curve pool is not paying for itself, then Lido needs to address the underlying problem: improving real use cases of stETH across the ecosystem to increase velocity, thereby increasing volume and fees for LPs.
Further, it is important for the DAO to calculate––from first principles––exactly how much TVL is needed at any given time. This requires data-driven modeling from historical analytics that inform the incentives distributed per day/week/month. The analytics team has done a tremendous job with creating dashboards related to the problem, and we are miles ahead of most DAOs in this facet. However, given that this is the DAO’s largest expense, it is crucial that we do a better job at consuming and implementing this data by crafting objective-based research frameworks. The PID is a great stepping stone in this direction.
The post mentions delta-neutral LP’ing a few times, and we urge the community to dive deeper into this user profile. As a core contributor to Delta One, we have spent ~2 years exploring the delta-neutral LP space, as it has been our flagship vault since inception. We work with a number of retail and institutional LPs to collect data on optimal LP strategies, putting us in a unique situation to provide some valuable insights here. We will craft our thoughts in a longer form proposal, so stay tuned for that.
Lastly, we support further research into creating a goals-based approach to building liquidity on new domains. The DAO has built robust frameworks for Curve, but how can we scale this to new protocols and blockchains? The DAO is on track to receive large quantities of incentives for new chains, and if those rewards are not managed correctly, future venues will become an expensive liability: new networks may never reach escape velocity, and early LPs will pay the price.
Over the last few weeks, our team has been collaborating with a number of members in the Lido DAO, and we plan to increase bandwidth in supporting the incentive optimization efforts. We look forward to taking an active role in the discussion, and serving as a reliable external team to help the community build a long-lasting, cost-effective liquidity engine.