What Happens When 4 AI Agents Share a Memory Pool

I run 4 AI coding agents — 3 Claude Code instances and 1 Codex CLI — all working on the same codebase simultaneously. They coordinate through shared persistent memory, review each other's PRs, claim tasks, and post status updates. Here's what I learned building the system that makes this work. The Problem Every AI coding session starts from zero. Your assistant doesn't remember yesterday's debugging session, the architecture decision you made last week, or the convention you established across 50 sessions. You re-explain context every time. I built synapt to fix this. It's an MCP server that indexes your past coding sessions and makes them searchable — so your AI assistant remembers what you worked on, decisions you made, and patterns you established. The Setup synapt runs as a local MCP server. pip install synapt, add it to your editor config, and your assistant gets 18 tools for searching past sessions, managing a journal, setting reminders, and coordinating with other agents. pip in