The Architectural Gap Between Hermes and OpenClaw

Andy Stewart — Tue, 21 Apr 2026 08:58:53 +0000

Building a cross-platform solution that supports multiple AI Agents sounds easy on paper. In reality? The underlying directory structures and versioning logic are worlds apart. After deep-diving into both Hermes and OpenClaw, here are the technical nuances you need to know.

State Management & Workspace Persistence

OpenClaw: Extremely clean. Everything lives in ~/.openclaw/workspace. It’s a dream for backup scripts and containerization.

Hermes: A bit more "wild west." Memories and configs are scattered. If you’re looking for a stable backup, start with ~/.hermes, but keep an eye on external paths.

Model Adaptation: Ease vs. Extensibility

OpenClaw: Straightforward support for domestic and international LLMs. It’s "plug-and-play" for the most part.

Hermes: Offers a shiny GUI with a long list of models, but don't let that fool you. To get them working correctly, you must follow the Hermes-specific adaptation rules. It's more powerful but requires more "glue code."

Versioning & Deployment Workflows

OpenClaw: Leverages npm for seamless version switching. Standard and predictable.

Hermes: Requires a more manual "DevOps" approach. I recommend downloading specific GitHub tags/zips and using symbolic links (symlinks) to manage version swaps safely.

Compatibility isn't just about API calls; it’s about managing the filesystem and lifecycle differences. Hope this saves you some debugging time!

Why I Returned to Coding After 7 Years as a "Pure" CEO?

Andy Stewart — Tue, 21 Apr 2026 07:39:41 +0000

In the Pre-AI era, a responsible CEO had three jobs: Raise money, recruit talents and set the vision. If you spent your day writing code, you were "irresponsible." You were indulging in your own joy while neglecting the ship's direction. I followed this rule and stopped coding six or seven years ago to focus entirely on strategy.

The AI Pivot:
Late last year, I went All-in on AI. Everything changed. I’ve been a dev for 20+ years, and my core strength is understanding users. Previously, building a "polished" software product required 100% of my energy—leaving zero room for leadership.

Now? I use AI as my force multiplier. I can "code" while walking the kids, waiting for a green light, or shopping with my wife. I spend 10% of my time building high-quality software and 90% on high-level thinking.

The Organizational Insight:
CEO-coding isn't just about output; it's about AI-First intuition. By being in the trenches, I’ve realized:

The New MVP: The most valuable engineers aren't just "technical geniuses." They are the ones who love the customer, push for progress, and ask "Why?"

The Risk: Knowledge is no longer the bottleneck—execution and empathy are. Highly skilled devs who refuse to talk to users will be replaced by AI-augmented "Product Engineers."

My Advice:
Stop asking what AI is for. Start coding. The moment you understand the AI workflow, your anxiety will vanish, and your passion will return. The steam engine era for startups is here.

DEV Community: Andy Stewart

The Architectural Gap Between Hermes and OpenClaw

Why I Returned to Coding After 7 Years as a "Pure" CEO?