Agent Col: AI Collaborator with Controlled Continuity

说明与用途

Agent Col 是一个 AI 助手，能够在会话之间保持上下文，但让用户控制记忆内容，解决上下文衰退问题。

问题

AI assistants lose context and become unhelpful over long projects, leading to context rot and continuity issues.

结果

Agent Col demonstrates that an AI collaborator can maintain useful context across sessions while keeping the user in control of what is remembered, solving context rot and continuity problems.

工作流

• 1. User starts a conversation with Agent Col.
• 2. Agent Col captures immediate context and proposes relevant workspace notes or memories.
• 3. User approves or rejects proposals, governing what becomes durable memory.
• 4. Agent Col stores approved data in Firestore under appropriate scopes (user or workspace).
• 5. In subsequent sessions, Agent Col retrieves relevant memories and notes to inform responses.
• 6. Agent Col can ask clarifying questions, suggest next steps, and propose new notes, all subject to governance.

证据

Agent Col uses a layered, multi-tiered memory architecture built around Google Cloud Firestore, with explicit governance controlling what information can become durable memory.

来源

Long-term user memory is governed by contracts defining what Agent Col is allowed to retain, and proposed memories require explicit user approval before becoming authoritative.

来源

Agent Col also maintains a temporary internal working context during conversation.

来源