Using WoClaw to Solve Shared Memory for Multi-Agent Workflows: OpenClaw, Codex, Claude, and Gemini on the Same Table

Sun, 05 Apr 2026 20:10:00 +0800

What matters most in a multi-agent system is often not “which model is smarter”, but “which agent still remembers what happened five minutes ago”.

When I put OpenClaw, OpenAI Codex, Claude, and Gemini into the same workflow, the most painful problem was not raw answer quality. It was context fragmentation:

OpenClaw remembered scheduling decisions, Codex remembered implementation details, Claude remembered review conclusions, and Gemini remembered external references, but none of them knew what the others knew.
Each tool had its own session lifecycle, so yesterday’s discussion was often gone by tomorrow.
As soon as a project entered a multi-round, multi-tool stage, repeating the same background became more expensive than solving the problem itself.
Without a shared memory layer, the final result was not collaboration, but several partial answers that looked similar and still failed to line up.

This post is about how I used WoClaw to place all of those tools on the same shared memory layer, so they could stop talking past each other and start working from the same state.

To avoid leaking private information, all examples below are abstracted. They do not include real hostnames, account names, addresses, tokens, or internal project codes.

Shared-Memory on Margrop Blog

Using WoClaw to Solve Shared Memory for Multi-Agent Workflows: OpenClaw, Codex, Claude, and Gemini on the Same Table