Problem
AI coding tools (Cursor, Claude Code, VS Code agents, Codex CLI) are stateless.
This leads to:
- lost debugging context
- repeated explanations
- broken multi-tool workflows
- no persistent project memory
Even with large context windows, state is still not preserved across tools.
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Solution: Contorium
Contorium introduces a persistent runtime layer between AI agents and the development workspace.
It enables cross-tool context continuity.
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System Overview
Contorium tracks three core states:
- Current Focus Layer
What the developer is actively working on.
- Workspace State Layer
Includes:
- active files
- git diff state
- recent modifications
- Session Continuity Layer
Restores state across:
- IDE restarts
- model switching
- multi-agent workflows
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Key Insight
AI coding systems are not limited by intelligence.
They are limited by state fragmentation.
Each tool sees only its own session.
Contorium unifies them into a shared runtime state.
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Architecture Concept
Contorium acts as a bridge between:
- IDE extensions
- CLI-based AI tools
- MCP-compatible agents
It synchronizes workspace state into a shared persistence layer.
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Visual Concept
(insert banner image here)
This shows:
- multiple AI tools converging
- one shared workspace state
- continuous context across environments
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Why This Is Important
Without continuity:
- AI tools behave like disconnected chat sessions
- developers re-explain context constantly
- long-term projects break into fragments
With continuity:
- AI becomes a persistent collaborator
- workflows become stateful
- multi-tool ecosystems become viable
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V2 Direction
Current focus:
- stronger MCP integration
- improved workspace graph model
- cross-tool state sync engine
- reducing context reconstruction overhead
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Vision
From:
stateless AI tools
To:
persistent AI development runtime
https://www.contorium.dev/ https://github.com/ContoriumLabs/contorium
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