How Things Work

On this episode of "How Things Work", we chat with Jack Kearney, Arnaud Brousseau, and Zeke Mostov from Turnkey about architecting secure TEE-based applications (yes, there are insecure ones).

We start by discussing why and where TEEs are used (and how they can play a role even when MPC and ZK are employed). Next, we explore the foundations you need to build before deploying a TEE (assuming you don't want to use Turnkey's OSS tools for doing so). Last, we cover how to safely update code running in TEEs and how to safely interact with external state.

On this episode of "How Things Work", we chat with Ryan Zarick (raz), Isaac Zhang, and Thomas Kim from LayerZero about scaling blockchain throughput with their new authenticated database (QMDB) and a new approach to pre-block packing (FAFO).

We first discuss the Quick Merkle Database (QMDB) and the insights that drive it state-of-the-art performance. Next, we discuss why the proof structure of QMDB works great with ZK and how to extend the (optional) compaction algorithm to apply changes to state. Last, we cover how Fast Ahead-of-Formation Optimization (FAFO) leverages QMDB to hit the mythical 1M TPS mark on a single machine.

On this episode of "How Things Work", we chat with Kushal Babel and Babak Gilkalaye from Category Labs (the team building the Monad reference client) about their research into scaling blockchain broadcast.

We first discuss the techniques existing blockchains (like Bitcoin, Ethereum, and Solana) use to disseminate data across p2p networks. Next, we dive into the "broadcast stack" (Data Transmission, Encoding, System and Broadcast Strategy) and explore how Monad is employing Raptor Codes to balance low latency with high throughput. Last, we discuss the tradeoffs (and open questions) of deploying pre-consensus broadcast instead of "in the hot path" broadcast.

In this episode of "How Things Work", we chat with Grigore Rosu about the 20+ year history of runtime verification and how his latest project, Pi Squared, is using Executable Semantic Frameworks (via K) to create a new type of blockchain execution environment that supports any programming language (including ones you write yourself).

For the second episode of "How Things Work", we chat with Shresth Agrawal about pod's recent work into Partially Ordered Datasets and how they can be used to deploy low-latency blockchain applications.

We first discuss where pod originated and how different applications can be built without relying on total order. Then, we discuss how pod's recent work (Pod: An Optimal-Latency, Censorship-Free, and Accountable Generalized Consensus Layer) can provide the properties most applications want without running traditional consensus. Lastly, we explore how pod can be used as the backbone of complex gadgets that rely on censorship-resistant auctions.

For the pilot episode of "How Things Work", we chat with the Alex Evans and Guillermo Angeris (from Bain Capital Crypto) about their research into blockchain scaling.

We first pull back the curtain on Data Availability Sampling (DAS) and explore how systems today encode data for light client sampling. Then, we discuss how their recent work, ZODA (Zero-Overhead Data Availability), promises to make this process more (or even optimally) efficient by transforming the encoding of some data into a proof of its correctness. After that, we dive into a discussion about The Accidental Computer (Polynomial Commitments from Data Availability), a surprising result that shows that succinct proof systems can reuse work already done during data availability encoding to reduce (or wholly remove) work associated with the proof system's polynomial commitment scheme. Last, we chat about implementation progress (in Julia) and how blockchains could be designed to take advantage of this work.