openclaw - 💡(How to fix) Fix [Show & Tell] CrewHiveClaw — An AI-Native Organizational Collaboration Framework on OpenClaw [1 comments, 2 participants]

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openclaw/openclaw#77273Fetched 2026-05-05 05:50:17
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Fix Action

Fix / Workaround

  • 8-file identity system: Full agent self-definition (SOUL / AGENTS / MEMORY / IDENTITY / TOOLS / USER / HEARTBEAT / SESSION) — not system-prompt patchwork
  • Gateway + hooks: Full information lifecycle capture, continuous immersion in organizational channels
  • Self-authoring workspace: Agent modifies its own config, takes effect next session — L1 autonomous evolution path
  • Evergreen MEMORY.md: Core memory that never decays
  • Layered Skills: Workspace-layer skills override framework-layer, highest priority
  • Heartbeat + cron: Proactive behavior clock — doesn't wait for commands

Code Example

Frontend Agent — immersed in org comms, catches fuzzy requests
        ↓ triggers
Designer Agent  — reads code first, designs with tradeoffs
        ↓ hands off
Implementer Agent — precise coding, self-validates, escalates blockers
        ↓ delivers
Frontend Agent — validates, returns to the human
RAW_BUFFERClick to expand / collapse

CrewHiveClaw: Give Any Organization Its Own AI R&D Team

Not an API wrapper. Not a chatbot. A truly present AI member — one that continuously understands your organization, autonomously delivers capabilities, and evolves alongside you.

GitHub: https://github.com/neovial/HomeAI


What It Does

Members chat in their usual channels — ideas, complaints, wishlist items. The system listens. It extracts valuable needs and automatically builds the software to fulfill them.

Someone says "I wish I had a homework mistake tracker" → The system designs a solution, writes the code, delivers a working app. Medication reminders, expense reports, business dashboards — same logic. Nobody needs to know how to code.

Over time, the system gets to know every person — how they talk, what they care about, the things they leave unsaid. Trust deepens. Delegation increases. The system grows alongside the organization.

Architecture: Three-Role V-Shaped Collaboration Chain

Frontend Agent — immersed in org comms, catches fuzzy requests
        ↓ triggers
Designer Agent  — reads code first, designs with tradeoffs
        ↓ hands off
Implementer Agent — precise coding, self-validates, escalates blockers
        ↓ delivers
Frontend Agent — validates, returns to the human

Catch the vibe at the entrance, deliver harness at the exit. Most of the time, humans don't have clear specs — just "I want to do something." The system's job is to receive that fuzzy intention, help clarify it step by step, and produce something the requester didn't even know was possible.

Three Design Principles

Augment, Never Replace. The system never tries to replace anyone. It enhances existing members' capabilities and fills roles no one currently occupies. This is the fundamental dividing line from every "AI replaces humans" approach.

Sidecar, Never Disrupt. The system hooks into existing communication channels — chat groups, DMs, existing software — without asking anyone to change their habits. It's slow, but it creates zero resistance, which makes it irreversible.

Judgment Transfer. Every person in the organization contributes judgment from different angles — what "done" means, what pitfalls to avoid, why we do things this way. The system accumulates not just data, but the organization's unique judgment. Features can be copied. Judgment cannot.

Dual-Layer Self-Evolution

Local Layer (CrewClaw): Grows inside the organization, understanding it more deeply over time. Memory spans four dimensions: semantic, temporal, entity, and causal — all four are necessary.

Cloud Layer (HiveClaw): De-identified experience aggregates across instances, trains master models, feeds back to every instance. New organizations start from an increasingly higher baseline.

Why OpenClaw

OpenClaw provides the complete Agent infrastructure we needed:

  • 8-file identity system: Full agent self-definition (SOUL / AGENTS / MEMORY / IDENTITY / TOOLS / USER / HEARTBEAT / SESSION) — not system-prompt patchwork
  • Gateway + hooks: Full information lifecycle capture, continuous immersion in organizational channels
  • Self-authoring workspace: Agent modifies its own config, takes effect next session — L1 autonomous evolution path
  • Evergreen MEMORY.md: Core memory that never decays
  • Layered Skills: Workspace-layer skills override framework-layer, highest priority
  • Heartbeat + cron: Proactive behavior clock — doesn't wait for commands

These mechanisms turn "continuously understand an organization" from a concept into an engineerable path.

Current Status

HomeAI is the first validation instance (family scenario, 4 core members + extended network). A second instance (business scenario) is in preparation.

We believe the family is the smallest organizational unit — tightest relationships, highest trust, most natural information flow. If AI can't evolve from "tool" to "member" in a family of four, it certainly won't in a larger organization.

Learn More

Feedback, questions, and roasts welcome 🦾

extent analysis

TL;DR

The issue lacks a clear problem statement, but a potential fix or workaround could involve reviewing the Agent infrastructure and its self-evolution mechanisms to ensure they are functioning as intended.

Guidance

  • Review the 8-file identity system and Gateway + hooks to ensure full information lifecycle capture and continuous immersion in organizational channels.
  • Verify that the Self-authoring workspace and Evergreen MEMORY.md are correctly configured to enable L1 autonomous evolution and prevent memory decay.
  • Investigate the Layered Skills and Heartbeat + cron mechanisms to ensure proactive behavior and priority overrides are working as expected.
  • Examine the instance config and pipeline to ensure they are correctly set up for the specific organizational scenario (e.g., family or business).

Notes

The issue does not provide a clear problem statement, so it is difficult to provide a specific solution. The guidance provided is based on the architecture and design principles described in the issue.

Recommendation

Apply workaround: Review and verify the Agent infrastructure and its self-evolution mechanisms to ensure they are functioning as intended, as this may help resolve any potential issues with the system.

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