55a80ce6e3
- Add ai-core/ — Chief, Scout, Scribe OpenClaw agents + shared knowledge base - Consolidate research/reference docs and the sns.md brand foundation under ai-core/knowledge/ - Repoint every sns.md reference (business branding, divisions, root README) to ai-core/knowledge/sns.md - Update root + ai-core READMEs to reflect the new structure
107 lines
4.7 KiB
Markdown
107 lines
4.7 KiB
Markdown
# AI Core — SnS Network Solutions
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The holding company's internal AI team. A **strict hierarchy**: one leader agent
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(**Chief**) is the single point of contact and routes work to a lean set of
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specialists. Nothing runs unless it's necessary to the business.
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> **Goal:** all services eventually run on AWS (EC2 + Bedrock). **For now** it runs on
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> the home server `ws` in a VM. The stack is containerized so it moves between the two
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> **unchanged** — the VM is disposable; this git folder is the source of truth.
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## Chain of command
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```
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SAM (owner / CEO — final authority, approval gates)
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│ you talk to ONE agent
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CHIEF (team leader — routes, decides, aggregates, enforces gates)
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│ specialists report UP only, never to each other
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┌─────┼─────┐
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SCOUT SCRIBE (LEDGER — add when billing starts)
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research docs
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```
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- You only ever message **Chief**. Specialists have no direct channel to you.
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- Specialists only talk to **Chief** — no lateral messaging (enforced by config).
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- Chief cannot send external comms, move money, or make legal promises — those
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escalate back to you. Chief runs the team; you stay CEO.
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## Roster (lean — only what the business needs now)
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| Agent | Role | Status |
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|-------|------|--------|
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| **Chief** | Team leader / orchestrator. Single point of contact, routing, aggregation, approval gates. | Active |
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| **Scout** | Research & competitive intel. Read-only, informational. | Active |
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| **Scribe** | Documents — proposals, SOWs, NDAs, SOPs — from templates, held for review. | Active |
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| Ledger | Bookkeeping/billing prep. Generates, never sends or pays. | Add when invoicing starts |
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Add specialists *under* Chief as the business creates work for them. The command
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structure never changes — that's the point.
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## Layout
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```
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ai-core/
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├── docker-compose.yml OpenClaw gateway (image ghcr.io/openclaw/openclaw, :18789)
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├── .env.example config template — copy to .env, fill in, never commit .env
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├── .gitignore
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├── agents/ canonical agent definitions (version-controlled)
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│ ├── chief/ team leader
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│ ├── scout/ research specialist
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│ └── scribe/ document & visual specialist
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│ each agent folder holds its OpenClaw workspace:
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│ SOUL · IDENTITY · USER · AGENTS · TOOLS · HEARTBEAT · MEMORY
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│ + skills/ knowledge/ projects/
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├── knowledge/ shared knowledge base — sns.md (brand foundation) + research/reference docs
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└── state/ runtime state + sessions (gitignored, created on first run)
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```
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## Run it (on the `ws` VM)
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Prereqs: a Linux VM with Docker + Docker Compose, and ≥4GB RAM (OpenClaw OOMs under 2GB).
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```bash
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cp .env.example .env # then fill in your OpenAI API key + model refs
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docker compose up -d
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docker compose logs -f gateway
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```
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The gateway binds to `127.0.0.1:18789` only — it is **not** exposed to the internet.
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Reach the web UI over Tailscale or an SSH tunnel:
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```bash
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ssh -L 18789:127.0.0.1:18789 <user>@ws # then open http://localhost:18789
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```
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**Register the agents** (first run) — the canonical SOUL.md files live in `agents/`;
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register each with the gateway so it picks them up:
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```bash
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docker compose exec gateway openclaw agents add chief
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docker compose exec gateway openclaw agents add scout
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docker compose exec gateway openclaw agents add scribe
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docker compose exec gateway openclaw agents list --bindings
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```
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> ponytail: exact `agents add` workflow + workspace path (`~/.openclaw/agents/<id>/workspace/SOUL.md`)
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> should be confirmed against https://docs.openclaw.ai on first run — ceiling: this is a
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> one-time manual registration step, not yet automated. Upgrade path: a bootstrap script
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> that syncs `agents/*/SOUL.md` into the state volume on `up`.
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## LLM backend — OpenAI / ChatGPT (current)
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OpenClaw talks to OpenAI via an **API key**.
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- **On `ws` now:** put your `OPENAI_API_KEY` in `.env` (see `.env.example`) and set the
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model refs. Route routine work to a small/fast model and reasoning to a strong one to
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control cost.
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- The key is the only credential needed — no cloud account required to run on `ws`.
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## Move to AWS + Bedrock (future goal)
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The end goal is to run this same stack on AWS with Amazon Bedrock. When we migrate, run the
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*same* `docker compose up` on an EC2 instance (t3.large, 8GB): drop the `OPENAI_*` keys,
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attach an **IAM instance role** so OpenClaw uses Bedrock via the AWS credential chain, put a
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Bedrock VPC endpoint in front, and reach the gateway over Tailscale/SSM. **The agents,
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skills, and compose file are identical** — only the provider config changes. That backend
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portability is the whole point of this design.
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