In this episode, we spoke with Jonathan Passerat-Palmbach, Senior Research Scientist at Flashbots, about tackling MEV challenges through privacy-enhancing technologies. Main topics we discussed:

- Flashbots' evolution: from MEV mitigation to building block building infrastructure

- The MEV trilemma and why auctions offer a better approach than spam or latency games

- The current MEV landscape and the role of PBS and BuilderNet

- How Flashbots leverages TEEs for pre-trade privacy and integrity guarantees in block building

- Limitations of TEEs and ongoing research to strengthen trust assumptions

- Complementing TEEs with cryptography for stronger defense-in-depth architectures

- Experimental work on encrypted backrunning using MPC and FHE

- The broader Suave vision and decentralized encrypted mempools

- Reflections on federated learning, privacy-preserving ML, and why PETs still struggle for adoption in AI

Links

Flashbots Website: https://www.flashbots.net/

FHE Backrunning Paper: https://fc25.ifca.ai/preproceedings/238.pdf

Buildernet: https://buildernet.org/

Jonathan’s Projects: https://jopasser.at/

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#34 | Flashbots: MEV, Privacy, and Trusted Execution