🧵 1/3 Vocdoni is part of @OctantApp Epoch 13, the Privacy Round, and the allocation window opens today. This is a another real chance for @ethereum to show it's useful to people, not only to speculators. Private, verifiable voting is one place it can, and we're doing it with DAVINCI.vote: private, receipt-free and verifiable voting as an open-source public good! Support us until 21 Oct: epoch.octant.app/rounds/0x57…

One step closer to 4-8x faster Ethereum finality! It took some time and lots of tokens, but we now have a formally verified proposal for a decoupled consensus protocol in I* (a future Ethereum upgrade)! Not yet a full spec (up next), but it includes all the key consensus-relevant details to become one. Since Ethereum aspires to be live without most of the stake online, the protocol involves many more components than a normal BFT protocol, and its correctness involves much more than standard safety and liveness. Those nuanced properties are now verified! What's more, I came away convinced that all protocol design will involve AI-assisted Formal Verification in the future, both for correctness and iteration speed. The work wasn't limited to just: Design the protocol -> Formally verify it Instead, the loop became more like: Design -> Formal Model -> Find exactly what breaks and why -> Redesign it. For a fairly complicated protocol like this one, I think having the Lean model be part of the design loop played a big role in accelerating the process. A future with agents paired with formal models is a superpower for Ethereum development, because they can then use those models to find exactly where an argument breaks down, formalize counterexamples, test proposed fixes, iterate on the protocol. Many details that would slip under the radar when asking agents (and indeed, humans) can now be specified exactly and checked by the Lean kernel. This then forces agents to be more precise and lets them make verifiable progress on their own. It's been incredible to see this play out, seeing agents find gaps and propose protocol changes to fix them. In other words, autoresearch can speed up protocol design, formal verification is here to stay, and Ethereum Finality will get faster.

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Most SSZ libraries are tested against the spec. I built one where the core properties are formally proved, in Lean 4. It also passes the full upstream test corpus. SSZ is how Ethereum serializes and Merkleizes its data — if hash_tree_root or deserialize is wrong, you get the kind of bug that can split the chain. For this reason I wanted something that is not only tested against the spec, but also proved. Formal verification. The library is called SizzLean. I proved three theorems: roundtrip (decode after encode returns the same value), non-malleability (two different values cannot produce the same encoding), and a size bound. They hold for the fixed-size SSZ types: the integers, bool, fixed vectors and lists, and containers built from those. I have not proved them yet for bitvector, bitlist, and variable-size containers. So this is a base, not a finished proof. Trust boundary. The only thing I assume without proof is the C SHA-256 function, declared as three named Lean axioms. You can list the full trust footprint with one grep, or with #print axioms on any theorem. Nothing else is taken on trust. Two backends. The same spec runs on a fast cached backend, used for execution and for running the test vectors, and on a pure backend, used for the proofs. I put the hash function behind a typeclass, so SHA-256 can be replaced by Poseidon2 or a post-quantum hash without changing the containers, the proofs, or the cache. Conformance. On top of the proofs, it runs the official ethereum/consensus-spec-tests on both presets: ssz_generic: 2188 / 2188 ssz_static (mainnet): 1585 / 1585 ssz_static (minimal): 38991 / 38991 This covers every fork from Phase 0 to Gloas, including the new ePBS containers. I also commented the code to be read. If you want to learn how SSZ works, or how to do this kind of work in Lean 4, you can follow it from top to bottom. The verification was done with heavy help from an AI coding agent. With Lean this does not change the result: the kernel checks the proof, independently of who wrote it. I work on specs and test vectors at the Ethereum Foundation, on the STEEL team. This is a personal project. The next step is to widen the proofs toward the remaining types. Repo and full details: github.com/etheorem/etheorem…