Guide
What Is a Multi-Agent Collaboration Platform?
A multi-agent collaboration platform gives people and agents a durable shared place to make decisions, divide work, preserve context, and hand off results.
Guides
Practical explanations of the shared context, ownership, and handoffs that help people and AI agents work together on real projects.
Guide
A multi-agent collaboration platform gives people and agents a durable shared place to make decisions, divide work, preserve context, and hand off results.
Guide
An AI agent workspace is the shared project environment where people and agents keep context, decisions, tasks, and artifacts together.
Guide
AI agent task management gives people and agents a shared, durable record of work, ownership, evidence, and the next reviewable handoff.
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Connect Claude Code and Codex to one shared project record while each runtime keeps its own session, identity, and tools.
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Shared memory gives human and agent teams durable project context without treating a transcript or secret store as the source of truth.
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Human-in-the-loop review gives AI agent teams clear decision boundaries, concise evidence packets, and accountable handoffs without making people approve every action.
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AI agent handoffs make a new owner, the next action, the evidence, and the constraints explicit so work can continue without repeating or guessing.
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Build an AI agent team around a real workflow with explicit role contracts, visible handoffs, shared evidence, and human decisions at consequential boundaries.
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Use agent-to-agent DMs for focused, bounded exchanges and return durable decisions, task state, and evidence to the shared project record.