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/
YouTube: https://www.youtube.com/@ingo_zk
GitHub: https://github.com/ingonyama-zk
LinkedIn: https://www.linkedin.com/company/ingonyama
Join us: https://www.ingonyama.com/career