# I ran OpenClaw and Hermes Agent side by side for two weeks — here's what I learned

> Source: <https://dev.to/liwmj/i-ran-openclaw-and-hermes-agent-side-by-side-for-two-weeks-heres-what-i-learned-1j9c>
> Published: 2026-08-24 09:30:46+00:00

So I spent the last two weeks running two open-source AI agents in parallel: OpenClaw and Hermes Agent (from Nous Research). I went in expecting to pick a winner. I came out realizing it's not really a "pick one" situation at all.

These two projects represent two very different design philosophies — one is built around **connection and control**, the other around **learning and growth**. Which one fits you depends on whether you want an obedient tool or a companion that evolves with you.

Here's my full breakdown after using both for deployment, daily tasks, and the general "living with it" experience.

**OpenClaw takes a gateway-first approach.** It's a persistent controller that handles routing, permissions, multi-channel integration, and skill orchestration, with pluggable models. The core promise: connect everything, execute predictably.

**Hermes Agent is built around a learning loop.** The agent creates and refines its own skills as you use it, and keeps deepening its model of you over time. The core promise: the more you use it, the better it knows you.

A rough analogy: OpenClaw is like a senior assistant who strictly follows the instruction manual — plus a universal adapter. Hermes is more like a teammate who *writes their own manual* after every task and keeps improving it.

OpenClaw's default memory is fine (files and Markdown supported). But Hermes' four-layer memory architecture is noticeably more persistent — the difference becomes very tangible after a couple of weeks of use.

Hermes is extremely strong when the task is clear — it often nails things in one shot. OpenClaw needs more guidance, and occasionally "reinterprets" your instructions in ways you didn't ask for.

But there's a flip side: OpenClaw's permission and approval model is much more explicit. Better controllability, better auditability — which is a hard requirement in team settings.

One signal worth watching: since May 2026, Hermes has overtaken OpenClaw in daily token usage on OpenRouter multiple times.

| Your situation | My suggestion |
|---|---|
| New to agents; want multi-platform integration and fast onboarding | OpenClaw, no contest |
| Want a long-term personal assistant that self-evolves | Hermes — higher ceiling |
| Heavy user | Don't choose. Run both. |

The heavy-user play: **OpenClaw as the gateway and orchestration layer, Hermes as the deep-execution and learning layer.** The official migration tool (`hermes claw migrate`

) also makes switching — or running both — pretty cheap.

One question I'd love to hear your take on: **when it comes to AI agents, do you value "controllable" or "autonomous" more?** Drop your choice (and why) in the comments.