Organizational memory for SaaS teams
AI onboarding for engineering-led companies — built on Claude Code + open-source memory + CLO
An AI operating stack for SaaS teams is the combination of a personal agent (like Claude Code), an organizational memory server (mem0, memory-mcp, or a Karpathy-style markdown wiki), and a pedagogy layer (Cognition CLO) that models what each engineer knows and what they're about to forget.
The problem
- New engineers take 8 weeks to ship meaningfully — most of it spent re-learning context that already lives in a senior's head.
- Your staff engineers are your best teachers and your most expensive bottleneck. Every hire costs them 20+ hours of hand-holding.
- Architectural decisions made in 2024 get relitigated in 2026 because the 'why' didn't make it out of a Slack thread.
A company like yours
Devon's team ships a Next.js / Go / Postgres product. They hire 4 engineers in Q2. Onboarding currently eats a staff engineer for a full week per new hire, then two more weeks of scattered questions in #eng-help. By day 10, the new hire has asked the same five architectural questions across three seniors and a dozen Slack threads. The information exists — in a PRs, an old Notion doc, and two people's heads. It's just not retrievable at the moment of need.
Before vs after
- ~8 weeksRamp to first meaningful PR
- 20–30 hrsSenior eng hours per new hire
- $18K+Fully-loaded cost per hire's first month
- ~10 daysRamp to first meaningful PR
- 3–5 hrsSenior eng hours per new hire
- ~$14K / hireFully-loaded cost reclaimed
The stack, in plain English
For SaaS: Claude Code as the personal agent, memory-mcp or mem0 for org memory (plug your GitHub, Notion, and Slack MCPs straight in), and Cognition CLO on top modeling which concepts each engineer is about to forget. The .mcp.json lives in your repo — every engineer who clones gets the whole stack.
What day one looks like
FAQ
Do I have to use Claude Code? What about Cursor or Aider?
Any MCP-speaking agent works. Cursor, Aider, Zed, Gemini CLI, OpenCode all support the same .mcp.json. The stack is agent-agnostic by design.
Which memory tool should a 20–100 person SaaS company start with?
If you want the official, never-breaks option: Anthropic's memory-mcp (one line, zero infra). If you want production-grade with user scoping: mem0. If your staff engineer wants to fork a markdown-native brain like Garry Tan's: gbrain. See the full registry at cognitionus.com/memory.
Does this replace our engineering docs?
No — it makes them retrievable at the moment of need. Your existing Notion/Markdown/ADR docs become the agent's long-term memory. CLO tracks which concepts your engineers keep vs. forget, so doc decay becomes visible.
What data leaves our infrastructure?
The memory tools are all self-hostable. CLO stores engagement events (concept, timestamp, engagement type) — not your source code or ADRs. Your IP stays in your repo.
How long does it take to set up?
Pick memory-mcp: under 10 minutes. Pick mem0 or gbrain: 45–60 minutes for a staff engineer. CLO's API key drops into .mcp.json — done.