围绕 Jev 搭 24/7 交易系统的 15 条架构原则
拆解交易 bot 分层架构：状态引擎、Jev 判定窄问题、策略层、风控引擎、执行层，并强调过期答案直接跳过。
This is straight f*cking gold for anyone building trading bots. 15 principles for building a 24/7 trading system around JEV. From market data to decisions, risk checks, and execution. Asking AI “should I buy?” skips almost everything that makes a trading system work. This breakdown gets into the actual architecture: State engine — calculates the market snapshot. JEV — evaluates narrowly defined questions. Policy layer — turns those answers into allowed actions. Risk engine — blocks orders that breach hard limits. Execution — places orders and handles failures. One important detail: a late answer gets skipped. A decision based on an outdated order book can already be useless. The framework also covers confidence calibration, fallback behavior, and testing against simpler rules with trading costs included. Fast decisions are only one part of the build. The real test is whether the whole system holds up when data goes stale, requests fail, and fees eat into the spread. JEV handles the judgments. Code enforces the limits. The strategy still has to earn its edge.
这条是引用着另一条写的：「Jev + GPT-6 Astra 七步搭建 Agent 路由系统」