We're cohosting @mevday_ at Breakpoint again this year, with @jito_sol and @triton_one. December 9th in Abu Dhabi. Register below 👇

The biggest advantage of CLOBs is that they are easily interpretable. Every price level has a fixed supply: removing lots by crossing is similar to buying items from a vending machine. You can reasonably explain the mechanics to a sharp high school student. This simplicity is one reason CLOBs dominate traditional finance. But it also means many talented young people spend their prime years cracking the queue games of FIFO matching engines rather than reimagining new market structures. Crypto introduces a paradigm shift. Programmable asset ledgers enable experimentation with matching engine design itself—not just strategies within existing systems. @Uniswap pioneered this shift by bringing automated market makers to scale. While vanilla AMMs excel at price discovery for long-tail assets, they struggle with highly liquid markets that demand tighter spreads and deeper books. Today's builders are addressing these limitations with purpose-built solutions. @gavelxyz's sandwich-resistant AMM is a highly opinionated extension of the vanilla xy=k model that is specifically catered to Solana's block production and leader rotation. @SolFiAMM chooses a different set of tradeoffs than traditional CLOBs to provide competitive on-chain prices for liquid spot assets. Crypto's permissionless nature enables rapid iteration on market microstructure in ways traditional finance never could. These next-generation matching engines represent a fundamental shift: instead of one-size-fits-all solutions, we're seeing purpose-built market designs that optimize for specific assets, chains, and use cases.

Beat the NYC heat, join us for happy hour this Thursday with @LoopscaleLabs!

Beat the NYC heat, join us for happy hour this Thursday with @LoopscaleLabs!

The CT conversation about designing infrastructure for orderbooks is eerily similar to the AMM discourse in 2021. These are complex systems with tons of emergent properties that are difficult to predict from first principles. Winners test in prod to tighten feedback loops and learn the truth. But if you have to get your opinions from somebody, listen to experienced practitioners. Don't listen to anyone who hasn't built or interacted with these systems in a production setting. And definitely do not listen to theorists.

If you missed @jarxiao at Accelerate last week, here he is explaining how we’re scaling verifiable finance. He breaks it into: Scaling reads—web2 vs crypto solutions Scaling writes—through opinionated sequencing Scaling replication—via real time state root calculation

.@ellipsis_labs is happy to work with any launchpad on any blockchain to integrate Gavel's sandwich-resistant AMM.

.@CertoraInc let's get it done.