Proposal Review: What is Gauntlet?
Introducing Toshokan, a community-first blog for Sushi

Introducing Toshokan, a community-first blog for Sushi

Today we're excited to introduce Toshokan (図書館 Japanese word for library), our new blog that will help keep our community informed about the latest happenings at Sushi.

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Proposal Review: What is Gauntlet?

Concise and insightful reviews of important proposals from the Sushi Forum. This one is about the Gauntlet x Sushi Incentive Optimization [Renewal]
Proposal Review: What is Gauntlet?
Gauntlet x Sushi Incentive Optimization [Renewal]
Summary A proposal to renew Gauntlet’s engagement with Sushi on dynamic incentive optimization to drive efficiency and growth. Background Over the past year, Gauntlet worked with the Sushi team to optimize incentive allocation across pools based on trading volume elasticity. We deployed an optimiz…

For the past year, Gauntlet has been helping Sushi's Onsen manage its incentive rewards program. They have implemented an approach that uses data analysis, simulated models, and machine learning to increase the impact of Sushi emissions on profits for Sushi stakers.

Gauntlet has taken a technical approach to maximizing the power of Sushi's emissions. Instead of just supplying larger liquidity pools with greater amounts of Sushi emissions, they have dug deeper into the available data to increase Sushi's buying power for liquidity pools.

This approach liberates emissions from pools where they have little impact and allows them to be channeled into pools where emission incentives result in greater trading volume. According to Gauntlet, the revenue generated from token emissions has increased from 10% to 133% (revenue/emissions) under their careful watch. Of course, other factors relating to emissions tapering, and whatever else drives trade volume to Sushi are tied into that equation but having active management of emission allocation provides an obvious benefit.

TLDR: Who's Gauntlet?

Gauntlet makes recommendations to the Sushi team telling them how many Sushi tokens to send to each liquidity pool based on data they feed into a computer.

Their goal is to maximize swaps (swaps create fees), while minimizing wastage of Sushi token incentives.

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