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Hermes vs. Claude Code vs. the rest: Best AI agent harness so far?

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I’ve been using Codex, Claude Code, and OpenClaw for different kinds of work:

I know there are many other agent harnesses. Many are open-source, including OpenHands, , and Hermes.

I’m curious. Which agent harnesses are you currently using? How do you use them differently? Am I missing any that you would strongly recommend?

Looking forward to hearing everyone’s thoughts!

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Claude Code is the one that's stuck for me too, mostly for the same reason you're using it as a supervisor - it holds context over a long session better than the others I've tried, so it's the one I trust to actually keep track of what's already been decided instead of re-litigating it every few turns. haven't tried OpenClaw yet, what convinced you to trust it with daily-ops stuff specifically, was it the breadth of integrations or more about how it handles routine multi-step tasks without you having to babysit it?

 I like its heartbeat and scheduled execution. It’s useful for routine operational work like monitoring and summarizing the news without needing constant supervision. That said, I wouldn’t give it tasks where mistakes are unacceptable or irreversible. I think of it more like an intern: helpful with recurring work, but still operating within clear guardrails.

The intern framing matches what I've been running into. The guardrail part is the harder half though - I had a "stop and escalate" gate flag something as broken weeks ago, and every scheduled run after that just re-confirmed the same escalation without re-checking whether the original check was still true. Turned out it wasn't. The gate itself had gone stale and nobody, including me, thought to question it since it kept "agreeing" with itself. Curious if OpenClaw gives you any way to force a fresh look at a standing escalation instead of just re-reading the last verdict.

Claude Code is still my default for implementation and review because it preserves context across longer sessions. I use Codex when I want a more independent pass on a well-scoped task. For me, the real differentiator is how reliably a harness carries decisions across sessions, not just how many integrations it offers. Which one has been strongest at that for you?

 In my experience, the secret sauce is creating agent skills that persist context and decisions in a Git repository so they can be reused across harnesses. That makes continuity portable and narrows the gap between harnesses in how effectively they manage context.

 Storing skills and decisions in Git makes sense, especially when switching between harnesses. How do you prevent stale decisions from being reused after the codebase or requirements change?