Launching a MEV Research and Development Working Group

Maximal Extractable Value (MEV) represents the profit that can be extracted from block production by including, excluding, or reordering transactions. As MEV strategies become more sophisticated, they pose systemic risks to blockchain networks, including increased transaction costs, network congestion, and centralization pressures. A dedicated MEV Research and Development (R&D) Working Group is essential for any protocol or ecosystem aiming to understand these dynamics, develop mitigation strategies, and foster a fairer transaction ordering environment. This guide outlines the steps to launch such a group effectively.

The first step is to define a clear mission and scope. A successful working group needs specific, actionable goals. Common objectives include: - Analyzing on-chain data to quantify MEV across different protocols (e.g., Ethereum, Solana, Cosmos). - Researching and prototyping solutions like fair ordering protocols, encrypted mempools, or SUAVE-like shared sequencers. - Developing educational resources and standards for builders and validators. - Engaging with the broader community through workshops and open-source contributions. A focused charter prevents scope creep and aligns all participants.

Next, assemble a multidisciplinary team. Effective MEV research requires diverse expertise. You'll need researchers with backgrounds in cryptography, game theory, and economics to model incentives. Data scientists are crucial for parsing terabytes of blockchain data to identify MEV patterns. Protocol engineers can implement and test proposed solutions in environments like a fork of go-ethereum or a custom testnet. Including representatives from validator operations, application developers, and community governance ensures the group's output is practical and widely applicable.

Establish a structured workflow for collaboration. Adopt tools and processes common in open-source development. Use GitHub for code and paper repositories, Discord or Telegram for real-time discussion, and regular video calls for syncs. Implement a lightweight governance model, perhaps using a Snapshot space for major decisions, to manage proposals and funding allocation. Publishing findings in public repositories, like the Flashbots Research repo, and presenting at conferences builds credibility and attracts further collaboration.

Finally, secure sustainable funding and measure impact. Initial funding can come from ecosystem grants (e.g., from the Ethereum Foundation or Protocol Treasuries), but long-term sustainability may require a dedicated budget line. Define clear Key Performance Indicators (KPIs) to track progress, such as the number of research papers published, prototypes deployed to testnets, or reductions in quantifiable MEV (like arbitrage profit) on a target network. Regularly publishing transparency reports on findings and fund usage is critical for maintaining trust and demonstrating the group's value to the ecosystem.

Before forming a group, define its core mission and scope. Is the focus on public goods research like PBS (Proposer-Builder Separation), mitigating negative externalities for users, or developing new extraction strategies? The scope determines the required expertise, which typically spans cryptography, consensus algorithms, game theory, and smart contract security. A clear charter aligns members and sets expectations for deliverables, whether they are research papers, protocol designs, or open-source software.

Assemble a team with complementary skills. Essential roles include protocol researchers to analyze Ethereum's execution and consensus layers, data scientists to parse mempool and on-chain data using tools like EigenPhi or Flashbots' mev-explore, and software engineers to build prototypes. Consider including an economist for incentive design and a project manager to coordinate efforts. Prior experience with MEV concepts like arbitrage, liquidations, and sandwich attacks is a prerequisite for meaningful contribution.

Establish a research and development environment. This includes access to historical and real-time blockchain data, a private testnet (like a devnet from Geth or Nethermind) for simulating strategies, and secure infrastructure for sensitive code. Familiarity with MEV-related codebases such as Flashbots' mev-boost, mev-geth, and the ethers.js library is crucial. The group should also decide on collaboration tools (e.g., GitHub, Notion) and communication channels that ensure productive, asynchronous work.

Navigate the legal and ethical considerations inherent to MEV work. Research into extraction techniques can border on market manipulation; it's vital to establish ethical guidelines, potentially focusing on neutrality and transparency. If the group's output includes software, decide on a licensing model (e.g., GPL for copyleft, MIT for permissive use). For groups within larger organizations, ensure alignment with compliance teams regarding the nature of the research.

Finally, plan for sustainability and impact. Determine a funding model, which could be grants from entities like the Ethereum Foundation, internal corporate R&D budgets, or protocol treasury allocations. Define key performance indicators (KPIs) such as published papers, contributions to core protocols, or the adoption of developed standards. A successful MEV R&D group not only advances knowledge but also translates research into tangible improvements for the ecosystem.

An effective MEV research and development team requires a blend of two distinct but complementary skill sets: research and engineering. Researchers focus on the theoretical and economic aspects of MEV, such as identifying new extraction vectors, modeling auction dynamics, and analyzing the long-term implications for network security and fairness. They often have backgrounds in cryptography, game theory, distributed systems, or economics. Engineers, on the other hand, build the practical tools and infrastructure. This includes writing searcher bots, developing block builder software, creating simulation environments, and implementing protocol-level mitigations like PBS (Proposer-Builder Separation).

When recruiting researchers, prioritize candidates with a proven ability to publish or contribute to foundational work. Look for experience with Ethereum's execution and consensus layers, familiarity with flashbots research, and a deep understanding of Auction Theory. For engineers, seek out those with hands-on experience in Go or Rust (the primary languages for Ethereum clients and MEV infrastructure), smart contract development, and low-latency systems. Practical knowledge of the Ethereum JSON-RPC API, mev-geth, and the mev-boost relay architecture is highly valuable.

A common pitfall is building a team skewed too heavily toward one discipline. A group of pure researchers may produce excellent papers but struggle to implement or test their ideas on a live network. Conversely, a team of only engineers might efficiently build tools but lack the strategic direction to tackle novel problems or anticipate second-order effects. Aim for a core team where these roles can collaborate daily, with researchers proposing models that engineers can stress-test in simulation, and engineers surfacing on-chain data that inspires new research questions.

To source talent, engage with the existing MEV community. Key venues include the Flashbots Research Forum, EthResearch forum, and academic conferences like FC (Financial Cryptography) and WEIS (Workshop on the Economics of Information Security). Open-source contributions to projects like mev-inspect-py, Reth, or EigenLayer are strong indicators of both skill and genuine interest. Be prepared to offer competitive compensation, as MEV expertise is a high-demand specialization within the already competitive crypto talent market.

Finally, establish clear initial objectives for the working group. Are you focusing on public goods research to mitigate negative externalities? Building proprietary infrastructure for extraction? Or contributing to core protocol development like EIP-4844 or PBS? Defining a north star will not only guide your recruitment but also help attract mission-aligned individuals who are passionate about the specific problem space your group intends to address.

Begin by conducting a landscape analysis of existing MEV research and development. Identify the most pressing open questions and technological gaps. Key areas to audit include: - Protocol-level MEV (e.g., PBS, crLists, SUAVE) - Application-layer MEV (e.g., DEX arbitrage, liquidations) - Infrastructure & tooling (e.g., block builders, searcher SDKs, simulation environments) - Economic & game theory (e.g., validator incentives, long-term sustainability). Resources like the Flashbots Research Repository and academic papers from venues like FC, WEIS, and AFT are essential starting points.

Based on the landscape, formulate specific, answerable research questions. Avoid overly broad topics like "solving MEV." Instead, define scoped inquiries such as: "What are the latency-robustness trade-offs in a decentralized block builder network?" or "How does the adoption of ERC-4337 account abstraction impact the profit distribution of searchers?" Each question should have a clear success metric (e.g., a prototype, a simulation model, a formal proof, or a published paper) and a realistic timeline for exploration.

Explicitly define the scope and constraints of the group's work. Decide on the primary blockchain ecosystems (e.g., Ethereum, Solana, Cosmos) and the layer (L1, L2) you will focus on. Determine if the group will prioritize theoretical research, applied protocol design, or open-source tool development. Establishing these boundaries early prevents scope creep and ensures the team can achieve meaningful depth within its chosen domain.

Finally, document this agenda in a living document, such as a GitHub README or a shared notion page. This public charter should include: the core research questions, defined scope, intended outputs, and a roster of initial contributors. A clear, accessible agenda serves as a north star for the group and a compelling recruitment tool to attract experts aligned with your specific mission.

A working group requires capital to fund research, development, tooling, and community initiatives. Initial funding can be sourced from several avenues. Many successful groups begin with a grant from a relevant DAO or ecosystem fund, such as the Ethereum Foundation, Optimism Collective, or Arbitrum DAO. These grants are often awarded for public goods research that benefits the broader network. Alternatively, a consortium of protocols or L2s that directly benefit from MEV mitigation may provide collective funding. A clear, detailed proposal outlining the group's mission, deliverables, and budget is essential for securing these grants.

Once capital is secured, managing it transparently is non-negotiable for trust and accountability. The treasury should be deployed as a multi-signature (multisig) wallet on-chain, governed by the working group's core contributors or a designated council. Popular solutions include Safe (formerly Gnosis Safe) on Ethereum or its deployments on L2s. The multisig configuration (e.g., 3-of-5 signers) should be documented publicly. All expenditures—compensation for researchers, funding for bug bounties, tooling infrastructure costs—should be proposed and ratified via transparent governance processes, with transactions visible on a block explorer.

For ongoing sustainability, the working group should develop a recurring funding model. This could involve applying for retroactive funding rounds like those run by Optimism or Arbitrum, where work is completed first and rewarded based on proven impact. Another model is establishing a streaming vesting contract using tools like Sablier or Superfluid, where a grant is disbursed continuously over time, contingent on periodic milestone reviews. This aligns long-term incentives and reduces administrative overhead compared to lump-sum distributions.

Treasury management also involves asset strategy. While initial grants may be in a stablecoin like USDC or the network's native asset (ETH), the group may decide on a conservative treasury diversification policy. This could involve using DeFi primitives on Ethereum L2s for yield generation, such as depositing funds into Aave or Compound via safe vault strategies, ensuring liquidity is preserved while earning a return to extend the runway. All investment decisions must be ratified by the multisig and align with the group's risk tolerance.

Finally, maintain radical transparency. Publish regular treasury reports detailing balances, inflows, outflows, and runway projections. Use tools like Dune Analytics or DeepDAO to create public dashboards. This transparency builds credibility with current funders, attracts future contributors, and aligns with the Web3 ethos of verifiable, on-chain operations. A well-managed treasury is not just a bank account; it's a foundational piece of operational legitimacy for a technical working group.

Define a clear execution model for your working group. Common models include a centralized lead for focused sprints, a decentralized collective for broad exploration, or a hybrid approach. For example, a group might have a lead researcher coordinating a 6-week sprint on PBS analysis while other members independently probe specific protocol vulnerabilities. Establish primary communication channels—a dedicated Discord server with separate channels for #research-papers, #data-requests, and #code-review is standard. Weekly syncs should be mandatory to maintain momentum and unblock researchers.

Implement a structured research workflow to standardize output. A typical pipeline begins with problem scoping and literature review, proceeds to data collection using tools like EigenPhi or the Flashbots MEV-Share dataset, followed by analysis and modeling. The final stage is artifact creation: a research brief, a proof-of-concept script, or a contribution to an open-source project like the Flashbots mev-inspect-py suite. Using a shared GitHub organization with issue templates for research proposals ensures consistency and tracks progress.

Prioritize actionable output and knowledge dissemination. The goal is not just internal understanding but producing artifacts that benefit the wider ecosystem. This could be a new detection heuristic for predatory trading, a simulation of validator economics under different PBS designs, or a security audit of a novel DEX mechanism. Schedule regular write-up and review cycles to prepare findings for publication on forums like the Flashbots forum, EthResearch, or as academic pre-prints. This external validation is crucial for establishing the group's credibility and attracting talent.

Foster a culture of open collaboration and safe experimentation. MEV research often involves analyzing live chain data and potentially interacting with testnets. Establish guidelines for ethical research, especially concerning the use of mainnet data. Encourage the use of forked test environments (using Foundry's anvil or Hardhat) for simulating attacks or new extractor logic. Creating a shared repository of anonymized datasets and analysis notebooks accelerates onboarding and enables reproducible results, which is a cornerstone of credible research.

Finally, establish metrics for success and iterative improvement. Track key outputs: number of research publications, code contributions, novel MEV vectors identified, or successful integrations of mitigations into partner protocols. Conduct quarterly retrospectives to assess what processes worked, what blocked progress, and adjust the workflow accordingly. A successful MEV R&D group is a learning organism that evolves its methods alongside the fast-paced MEV landscape it studies.

The primary goal of publishing your working group's findings is to drive concrete protocol upgrades and policy changes. Begin by structuring your final report to align with governance processes. This includes a clear executive summary for busy delegates, a detailed technical analysis with data visualizations, and one or more specific on-chain governance proposals. For example, a report on PBS inefficiencies should conclude with a concrete proposal to adjust the builder selection algorithm or validator client configuration, referencing specific commits like ethereum/consensus-specs#PR_NUMBER. Publish this report on platforms like the Ethereum Magicians forum, the relevant protocol's research forum (e.g., Lido Research, Uniswap Governance), and arXiv for academic credibility.

Effective influence requires targeted outreach. Identify and engage key stakeholders: core protocol developers, major DAO delegates (e.g., entities like Lido, Coinbase, Figment), and governance forum moderators. Present your findings in dedicated community calls, such as Ethereum Core Devs meetings, Aave's Risk or Gauntlet forums, or Optimism's Governance Working Group. Frame the discussion around shared incentives; for instance, demonstrating how a specific MEV mitigation can increase validator rewards or improve user experience directly addresses delegate priorities. Provide clear, auditable code snippets or simulation results, like a Foundry script showing the gas cost impact of a new transaction ordering rule.

To formalize the change, you must navigate the proposal lifecycle. This typically involves a Temperature Check (informal sentiment poll), a Consensus Check (refined proposal discussion), and a final On-Chain Vote. Use tools like Snapshot for off-chain signaling and Tally or the protocol's native governance portal for on-chain execution. For a complex upgrade like modifying a DEX's swap function to include a fair ordering mechanism, you may need to deploy and verify a new smart contract as part of the proposal. Ensure all voting instructions and parameter changes are unambiguous. Successful proposals, such as Flashbots' integration of MEV-Boost or Uniswap's introduction of a fee switch, followed this path from rigorous research to coded implementation and community ratification.

Launching an MEV R&D working group transforms ad-hoc analysis into a structured, continuous process. The core mandate should focus on three pillars: monitoring MEV activity on-chain, researching its long-term economic and security impacts, and developing mitigations like encrypted mempools or fair ordering services. A successful group requires cross-functional membership, including protocol researchers, core developers, and data scientists. Initial resources like the Flashbots Research repository and EigenPhi's analytics provide essential starting points for data and methodology.

The first operational phase should establish a baseline. Deploy mev-inspect-py or similar tools to index historical data from your chain, categorizing transactions into known MEV strategies like arbitrage, liquidations, and sandwich attacks. Quantify the extracted value, its sources (e.g., which DEX pools are targeted), and its beneficiaries. This data informs the threat model. For example, you might find that 80% of arbitrage profit comes from latency advantages on a specific AMM, indicating a need for a commit-reveal scheme or a threshold encryption design for its mempool.

With a baseline established, the group's research agenda should tackle protocol-specific questions. How does MEV affect validator decentralization and staking economics? Does your consensus mechanism (e.g., Tendermint vs. Gasper) create unique extraction opportunities? Development efforts can then prototype solutions. This could involve forking and modifying a client like Geth to test a private transaction pool, or building a smart contract for fair ordering, such as a simplified version of the SUAVE concept. Regular internal reports and threat model updates are crucial outputs.

The final, critical step is governance and community integration. Research findings and proposed protocol changes must be socialized through forums and improvement proposals. For public chains, consider establishing a grants program to fund external researchers, similar to the Ethereum Protocol Fellowship. The working group should also maintain a public-facing dashboard, like those from EigenPhi or ChainEye, to build transparency and trust. The goal is to evolve from a reactive posture to setting the standard for MEV-aware protocol design, turning a potential threat into a managed aspect of the system's economics.