No, do not suggest Hermes or Claude Code as the easy out. 时间 we tuned our OpenClaw stack, we did not cut token usage from 34 billion per month down to 1.5 billion, and now to roughly 750 million, by throwing a better model at it. We did it with 系统 engineering: detached services running on event triggers, a routing layer that maps each task to the right model, and segmentation that gives the agent real schematics to repair, build, and execute against, instead of letting it guess like an intern with no ticket.
OpenCode 代理 - I use it heavily for troubleshooting - is more reliable than Hermes, cheaper than Claude Code, and feels similar to Grok 代理 in terms of stability. But OpenClaw still has capabilities OpenCode does not. So this is not a tool war. This is a 系统 设计 war. A bigger model bill does not win you better outcomes. A better-integrated 系统 does.
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这篇文章把detached services running on event讲得比一般的AI介绍更具体。
34读起来很清楚，也容易跟着理解。
我们团队正好在讨论34，这篇来得及时。
同意作者对production-ready的判断，方向很清楚。