Chainfeeds Summary:
Competition between blockchains has escalated to the level of "transaction ranking," which directly affects market makers' order spreads and market depth.
Article source:
https://x.com/GodotSancho/status/2004378829268439069
Article Author:
Godot
Opinion:
Godot: On-chain, user transactions are not immediately written to blocks; instead, they first enter the mempool and wait. At any given time, thousands of transactions may exist concurrently. Ultimately, the sequencer, validators, or miners must decide two key issues: which transactions will be included in the next block, and the execution order of these transactions within the block. This process of "determining the order" is called transaction ordering. Ordering is not a neutral operation; it directly affects user transaction costs, transaction success rates, MEV allocation methods, and the fairness of on-chain transactions. During network congestion, the ordering mechanism determines whether a transaction is quickly confirmed or continuously squeezed in the mempool. For market makers and high-frequency traders, the importance of ordering even surpasses TPS itself: whether order cancellations are prioritized determines whether market makers will be targeted and whether they dare to continuously provide liquidity. In the previous cycle, the industry generally believed that "higher TPS would improve the trading experience," but it has proven that if the ordering rules are unfriendly to market makers, even the fastest chain cannot form a deep and stable market. In centralized exchanges, trade matching follows a strict "price-time priority" principle. Market makers operate in a highly certain environment, providing deep order book liquidity with extremely narrow spreads. However, on-chain, once trades enter the Mempool, they are often sorted by gas cost, creating opportunities for high-frequency traders to "rush the market by increasing gas fees." For example, if a token is priced at $4.5, a market maker might place buy orders at $4.4 and sell orders at $4.6 to provide liquidity. If the external market price suddenly drops to $4, the market maker needs to immediately cancel the $4.4 buy orders to avoid losses. However, under a gas-priority sorting mechanism, arbitrageurs can increase gas fees to execute trades before cancellations, buying at a lower price and then selling back to the market maker at a higher price. Faced with this systemic risk, rational market makers can only widen spreads and reduce order sizes, ultimately resulting in thinner on-chain liquidity, increased slippage, and a worse trading experience for ordinary users. To address these issues, next-generation blockchains and infrastructures are shifting from "general-purpose sequencing" to "application-aware sequencing." One approach is to directly define sequencing rules at the consensus layer, a prime example being Hyperliquid: the system explicitly prioritizes order cancellations and post-only transactions, breaking away from sequencing logic solely reliant on gas. In extreme market conditions, market makers can always exit first, thus encouraging them to continuously provide liquidity. Another approach is to introduce customizable mechanisms at the sequencing layer, such as Solana's ACE (Application Controlled Execution) and Jito's BAM. DEXs can register custom sequencing rules with BAM nodes to implement strategies like market maker priority and conditional liquidity. Simultaneously, some protocols are reconstructing the distribution of sequencing value through private channels and MEV facilities; for example, Chainlink SVR redistributes liquidation-related MEV rewards from miners to the protocol itself. Sequencing is evolving from an invisible detail into a core infrastructure determining the quality of on-chain markets.
Content source 
