➥ FHE Onchain The Zama Chapter

I’ve been digging into how @zama_fhe brings fully homomorphic encryption to EVM, and the design space is wild

tl;dr What FHE changes
▸ Compute directly on encrypted data, no decryption step
▸ Trust math over hardware (contrast TEEs), complement ZK proofs
▸ Privacy at the function level, not just at the transport layer

fhEVM in 30s
▸ Solidity with encrypted primitives (euint/ebool) and FHE ops
▸ EVM-compatible dev flow, private state + private compute
▸ Off-chain FHE workers / coprocessors to handle heavy ops
▸ Keys remain with users or split via threshold schemes

What you can build next
❶ Sealed-order orderflow + MEV-resilient auctions on @ethereum
❷ Private AMMs/credit scoring without data leakage
❸ Encrypted on-chain ML inference and agent-to-agent payments
❹ Compliance-friendly rails: auditable when needed, private by default, unlike L2 mixers
(think ZK + FHE hybrids with @aztecnetwork for proofs)

Open questions
▸ Latency/fees vs batching + GPU acceleration
▸ Gas economics for encrypted ops
▸ Key management UX at scale

If you’re a dev: would you ship FHE as an L2, an EVM precompile, or a coprocessor model first, and why? Drop your trade-offs or benchmarks if you’ve tried tfhe-rs/concrete #FHE privacy