In fact, Ethereum is also researching parallelization solutions, but the progress speed will be much slower. In next year's Glamsterdam upgrade, it is highly likely to include EIP-7928 (Block Level Access Lists), which is the first step towards parallelization. This scheme forces the collection of a complete and verifiable BAL (Block Accessible List) at the block layer, which includes "all read and write boundaries of this block", so that there is a chance to know which transactions are completely conflict free and can be executed in parallel. Next, it depends on the development progress of the execution layer client, such as Reth (maintained by Monad's investor Paradigm), Nethermind, Erigon, etc., all of which are actively researching parallelization, but there is still some distance to go before production launch. And Monad's technology, on the other hand, has landed faster. They have completely restructured the technical architecture of the entire chain from bottom to top: What if the consensus is slow? A low latency BFT consensus protocol MonadBFT has been improved based on HotStuff, which makes consensus into a pipeline and reduces fork and confirmation time. What should I do if the block is transmitted slowly in the network? Using RaptorCast: First, use erasure coding to cut the block into many small pieces, and then transmit them through layered broadcasting. As long as enough small pieces are collected, the complete block can be restored without bursting the bandwidth of individual nodes. What should I do if EVM has slow single thread speed? Parallel execution of transactions within the same block, running multiple transactions simultaneously and recording their respective read and write states; Finally, submit in the original order, and any conflicting transactions will be rolled back and recalculated, while ensuring that the results are consistent with the single thread and consuming multiple cores. What if consensus and execution are squeezed into the same time window? Disassemble them into asynchronous pipelines: the consensus layer quickly determines the transaction order and basic legality, while the execution layer performs parallel calculations in sequence a few beats later, which not only generates blocks frequently but also leaves enough time for execution. 5. What should I do if my status reading and writing are lagging behind? Monad has developed its own state database MonadDb, which directly stores EVM states in KV storage optimized for blockchain access mode, and cooperates with asynchronous I/O to minimize disk bottlenecks during each execution. 6. What should I do if EVM execution is slow or not? JIT is applied to high-frequency contracts to compile EVM bytecode into local machine code, which is then directly executed using native instructions when calling these contracts, further reducing CPU overhead. Overall, Monad is not creating new languages or virtual machines, but exploring the physical limits of existing EVM standards. It leads to the same destination as Ethereum, but chooses a different engineering path: Ethereum needs to replace its engine while carrying a huge amount of assets, and stability is inevitable; As a newly launched Layer 1, Monad has the advantage of being a latecomer, able to completely rewrite every line of code at the bottom layer with the latest achievements in modern databases and distributed systems. But what happens to Monad ultimately depends not on TPS benchmark data, but on whether this high-performance engine can truly grow killer ecosystems that cannot run on old architectures. Or in the short term, it depends on the arbitrage space and whether there is a liquidity premium.