5 Things I Learned Running Multiple OpenClaw Bots on My MacBook

Dev.to / 4/4/2026

💬 OpinionDeveloper Stack & InfrastructureTools & Practical Usage

Key Points

  • OpenClaw updates ship frequently and can break gateway/config/memory behavior, so the article recommends pinning a specific version (or Docker image tag) instead of using @latest.
  • To avoid config, port, and shared-state collisions, each bot should run in its own isolated container rather than sharing one OpenClaw installation.
  • The author finds the documented ~1.5GB RAM idle requirement per bot is accurate, with practical performance depending on additional processes like Chromium inside containers.
  • Output quality is driven more by character design (e.g., SOUL.md personality, expertise boundaries, and constraints) than by only swapping LLM model choices.
  • Because updates and skill/character changes can reset memory or break the gateway, the article stresses taking snapshots beforehand (via ClawFleet “Save Soul” or manual backups) to enable recovery.

I've been running three OpenClaw bots on my MacBook for the past month. Here's what I wish someone had told me before I started.

1. Don't Run @latest

OpenClaw releases every 1-2 days. Some updates break the gateway, change config formats, or modify plugin behavior. I learned this after a bot crashed mid-conversation because an update changed how memory persistence works.

Fix: Pin a specific version. If you're using ClawFleet, it pins a tested version automatically. If you're running Docker directly, tag your image with a specific version instead of latest.

2. Each Bot Needs Its Own Container

Running multiple bots in the same OpenClaw installation causes config conflicts, port collisions, and shared memory states. I tried it — two bots started responding to each other's channels.

Fix: One Docker container per bot. Isolated filesystem, isolated ports, isolated data. ClawFleet does this automatically, but you can set it up manually with Docker Compose if you prefer.

3. 1.5 GB RAM Per Bot Is Real

The docs say 1.5 GB idle per instance. This is accurate. On a 16 GB Mac:

  • 1 bot: fine, barely notice it
  • 3 bots: ~4.5 GB, still comfortable alongside normal work
  • 5 bots: you'll feel it, especially if Chromium is active inside the containers

Tip: Monitor with docker stats. Kill Chromium processes inside containers you don't need desktop access for.

4. Character Design Matters More Than Model Choice

I spent hours comparing Claude vs GPT vs DeepSeek for my bots. Turns out the personality definition (SOUL.md) has more impact on output quality than the model.

A well-written character with clear expertise boundaries, communication style, and topic constraints produces better results on GPT-4o than a vague character on Claude Opus.

Tip: Spend time on the character bio, not just the model selection. Define what the bot should NOT talk about, not just what it should.

5. Save Snapshots Before Every Change

Experimented with a new skill installation and it broke the bot's memory? Changed the character and the bot's personality reset? Update the OpenClaw version and the gateway won't start?

All of these happened to me. All of them were recoverable because I had snapshots.

Tip: ClawFleet has a one-click "Save Soul" feature that snapshots personality, memory, config, and conversation history. Use it before every experiment. If you're managing manually, back up ~/.openclaw/ before changes.

Running a fleet of AI bots is surprisingly practical on consumer hardware. The key is treating it like infrastructure — version pin, isolate, monitor, back up.

If you haven't started yet: one command gets you a browser dashboard for managing OpenClaw instances. Ten minutes, no config files.

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