Every AI-native company is hitting the same wall: every new agent, every new model, every new tool means re-explaining the company from scratch. Context doesn't compound. It re-evaporates.
The Onboarding Tax
Every prompt is a mini onboarding doc. Every new agent needs the same docs, the same decisions, the same customer history pasted in. Multiply that by the dozens of agents your company runs and you've quietly built a full-time job around re-teaching context that already exists somewhere else.
Memory Trapped In Harnesses
Cursor remembers things ChatGPT can't see. Claude builds context Cursor doesn't share. Your custom agents start blind every run. As long as memory lives inside individual harnesses, agents can't actually collaborate — they just take turns hallucinating.
One Context Graph. Every Agent.
The fix isn't bigger context windows or smarter prompts. It's a shared substrate the whole company operates on:
- 1. One workspace per company A single context graph that humans and agents both read from and write to.
- 2. Knowledge ingested once Docs, decisions, repos, and customer threads land in the graph and become reusable context for every agent that follows.
- 3. Primitives that match your business Decisions, accounts, projects, runbooks — typed records that agents can read, update, and reason over without you having to re-explain how your company works.
- 4. Agents plug in over MCP One endpoint, OAuth, done. Any MCP-aware agent shows up already inside your company's context — and leaves its own work behind for the next one.
- 5. Long-horizon by default Threads, runs, and checkpoints turn multi-day, multi-agent projects from chat-log fragments into resumable work.
CortexGraph is our answer. The context graph for AI-native companies — where every human, every agent, and every tool operate against the same durable, structured reality.