交易 bot 用 Jev 做策略与执行间的决策闸门
在 Claude 出策略、Minara 跑回测与自动交易的流程里，用 Jev 处理 TEST/REJECT/REVIEW 等边界判断，作者注明这是设计提案而非已验证集成。
your AI trading bot can write a perfect thesis and still execute a terrible trade. the missing piece is the gate between “this looks good” and “send the order.” that’s what caught my attention in the Claude + Minara setup. the useful part is separating the strategy from the machinery that tests and executes it. Minara documents live market data, backtests that account for trading costs, paper trading, and an Autopilot that follows the strategy and scope you authorize. here’s where I’d add Jev: the small contextual decisions between those stages. → strategy proposed: TEST / REJECT / REVIEW → inputs look incomplete: FETCH MORE / STOP / ESCALATE → conflicting test results: INVESTIGATE / PARK / REVIEW → paper run changes behavior: CONTINUE OBSERVING / PAUSE / REVIEW picture a strategy with a beautiful equity curve. then costs eat the edge, a different market regime breaks the setup, or the data feeding it goes stale. the workflow needs somewhere to stop, gather evidence, or ask a human. a persuasive explanation can’t substitute for those checks. Claude develops the thesis. Minara supplies the trading tools. Jev could route bounded judgments using the current state and the last observed result. code enforces exposure limits, permissions and execution rules. a human authorizes the strategy before it touches live capital. important distinction: Minara’s Autopilot runs authorized rules; it doesn’t need a fresh human approval for every fill. the Jev layer here is a proposed design, not a native integration I’ve verified. the attached video shows that design as an original HTML animation, with synthetic states and no live orders. that’s the Jev angle I care about: give the agent a place to say “not enough evidence yet,” then make the next allowed step explicit. I break down the decision layer in my Jev article below ↓
这条是引用着另一条写的：x.com/0xkurt/status/2103410921892618651