Please help me understand the company os i’m missing a piece. Is it memory?

Has anyone successfully built a company OS where AI agents and humans work together reliably in production? I’m using Cursor, Cursor Cloud Agents, Claude Code, Claude Desktop, Codex, Claude Cowork, Linear, GitHub, Notion, and various automation tools. The coding side is getting surprisingly good. The part I’m struggling with is everything around it. I can have agents write code, complete tasks, and help with execution, but I haven’t found a reliable way to manage: Long-term company memory Workflow state across days and weeks Agent-to-agent handoffs Human approvals and feedback loops Audit trails and decision history Persistent context that survives sessions I’ve experimented with projects like Hermes and OpenClaw, but I haven’t reached a point where I would trust their memory systems with actual company operations. The issue isn’t whether they can retrieve information—it’s whether they can reliably maintain context, decisions, workflow state, and history over time. When people talk about memory, most discussions seem to focus on RAG and vector databases. But I’m starting to think the problem isn’t retrieval. It feels more like a combination of: State management Event history Orchestration Agent continuity Human-in-the-loop workflows My current thinking is: Linear → tasks, priorities, project state GitHub → code and pull requests Cursor Agents / Claude Code → execution Claude Cowork → orchestration and planning n8n / Temporal → automation and webhooks Slack / Telegram → human approvals and notifications Postgres / Supabase → long-term structured memory and logs Notion → company knowledge and documentation For those who have actually gotten this working in production: What was the missing piece? Was it RAG, event sourcing, workflow orchestration, custom memory systems, or something else entirely? Or are we all still stitching together tools because nobody has really solved this yet?