Proposal Title | Author(s) | Phase | Type | Date Created |
---|---|---|---|---|
RFP: AI-Agent-Driven MEV and Transaction Ordering Simulator on Gnosis Chain | brainbot gmbh | I | On-chain | 06.06.2024 |
Joint Call for Development: OLAS x Shutter DAO 0x36 Collaboration on Gnosis Chain
Proposal
If this proposal passes, Shutter DAO 0x36 in collaboration with OLAS issues a request for proposals (RFP) to the developer community. This RFP aims to attract developers and teams to build an AI-agent-driven simulator for MEV and transaction ordering strategies on Gnosis Chain. The focus is to leverage the shutterized, encrypted mempool and integrate OLAS autonomous agents, establishing a playground for the practical exploration of MEV solutions and transaction ordering strategies.
With the shutterized Gnosis Chain going mainnet within the next couple of weeks, we’re excited to share this collaboration, which proposes a blend of OLAS’s autonomous agents and Shutter’s L2 encrypted mempool to create a dynamic testbed for MEV and transaction ordering strategies.
The idea is that LLM-powered autonomous agents are interacting in a low-stakes, low cost, yet mainnet environment and with real funds. Some of these agents would use the encrypted mempool, some would not. We can then monitor and analyze the economic and technical implications of this behavior and use the feedback from it to improve the system and parameters.
Successful applicants will share rewards up to 50,000 USDC, 500,000 SHU and can expect additional rewards through the OLAS developer revenue share program.
Scope of Work
Set Up of OLAS Autonomous Agents Framework
- Development of Autonomous Agents: Modify OLAS’ already existing suite of trading agents to create and deploy autonomous agents capable of simulating a range of behaviors within the MEV ecosystem, from normal user trading to front-running strategies.
Creation of OLAS Agents for Simulation
- MVP Implementation: a) Simulate normal user trading behavior b) Implement standard MEV/front-running strategies c) Operate (or ensure the operation of) the agents
Sidenote: The agent system could already be tested on the shutterized Chiado testnet (The First Shutterized Testnet Is Now Live on Chiado!) and the Swapr V3 deployment which is live on top of it.
- Dashboard:
Develop a simple dashboard which can be used to supervise the state of the autonomous agents, including their individual P&L and the amount of front-running that they engaged in or were a victim of.
- Optional Enhancements: a) Liquidity Providing (LPing). b) Minting new tokens.
Encrypted Mempool Testing
- Performance Comparison: Set up a longer term experiment where, e.g. 10 agents utilize the Shutter encrypted mempool and 10 do not, to observe and compare their trading performance.
Once the more technical aspect of this experiments are set up, a follow-up proposal could be issued to Shutter DAO 0x36 to fund and further incentivize the autonomous trading agents and liquidity.
Rewards and Incentives
Successful applicants will share rewards up to 50,000 USDC, 500,000 SHU (subject to 1 year vesting), distributed among all grant recipients based on the completion and success of the proposed projects.
Sidenote: OLAS has a native dev rewards mechanism for several 100k $ per epoch (~1 month) to developers. Any agent use case minted on the OLAS registry would qualify for these rewards.
Motivation
The primary motivation behind this RFP is to bridge the theoretical and practical aspects of transaction supply chains, specifically in the areas of MEV and transaction ordering. By fostering a hands-on exploration environment, the collaboration seeks to enhance understanding, security, and efficiency within the DeFi space.
Pre-requisites
- Proficiency in blockchain development, particularly within the Ethereum, Gnosis Chain, and Optimism ecosystems.
- Experience or a strong interest in MEV and transaction ordering strategies.
- Commitment to maintaining operational aspects of the deployed systems for the agreed period.
Platform
Snapshot
Voting Options
“YES”
Approve the launch of the RFP and allocate the proposed rewards for project development and completion.
“NO”
Reject the proposal.
“ABSTAIN”
Choose not to vote on this proposal.
License
CC0: This work is marked with CC0 1.0 as dedicated to the public domain.