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refactor: organize agent harness courses
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learn-claude-code/docs/en/s09-agent-teams.md
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learn-claude-code/docs/en/s09-agent-teams.md
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# s09: Agent Teams
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`s01 > s02 > s03 > s04 > s05 > s06 | s07 > s08 > [ s09 ] s10 > s11 > s12`
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> *"When the task is too big for one, delegate to teammates"* -- persistent teammates + async mailboxes.
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>
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> **Harness layer**: Team mailboxes -- multiple models, coordinated through files.
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## Problem
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Subagents (s04) are disposable: spawn, work, return summary, die. No identity, no memory between invocations. Background tasks (s08) run shell commands but can't make LLM-guided decisions.
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Real teamwork needs: (1) persistent agents that outlive a single prompt, (2) identity and lifecycle management, (3) a communication channel between agents.
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## Solution
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```
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Teammate lifecycle:
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spawn -> WORKING -> IDLE -> WORKING -> ... -> SHUTDOWN
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Communication:
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.team/
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config.json <- team roster + statuses
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inbox/
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alice.jsonl <- append-only, drain-on-read
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bob.jsonl
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lead.jsonl
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+--------+ send("alice","bob","...") +--------+
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| alice | -----------------------------> | bob |
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| loop | bob.jsonl << {json_line} | loop |
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+--------+ +--------+
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^ |
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| BUS.read_inbox("alice") |
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+---- alice.jsonl -> read + drain ---------+
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```
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## How It Works
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1. TeammateManager maintains config.json with the team roster.
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```python
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class TeammateManager:
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def __init__(self, team_dir: Path):
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self.dir = team_dir
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self.dir.mkdir(exist_ok=True)
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self.config_path = self.dir / "config.json"
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self.config = self._load_config()
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self.threads = {}
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```
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2. `spawn()` creates a teammate and starts its agent loop in a thread.
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```python
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def spawn(self, name: str, role: str, prompt: str) -> str:
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member = {"name": name, "role": role, "status": "working"}
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self.config["members"].append(member)
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self._save_config()
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thread = threading.Thread(
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target=self._teammate_loop,
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args=(name, role, prompt), daemon=True)
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thread.start()
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return f"Spawned teammate '{name}' (role: {role})"
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```
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3. MessageBus: append-only JSONL inboxes. `send()` appends a JSON line; `read_inbox()` reads all and drains.
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```python
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class MessageBus:
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def send(self, sender, to, content, msg_type="message", extra=None):
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msg = {"type": msg_type, "from": sender,
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"content": content, "timestamp": time.time()}
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if extra:
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msg.update(extra)
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with open(self.dir / f"{to}.jsonl", "a") as f:
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f.write(json.dumps(msg) + "\n")
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def read_inbox(self, name):
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path = self.dir / f"{name}.jsonl"
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if not path.exists(): return "[]"
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msgs = [json.loads(l) for l in path.read_text().strip().splitlines() if l]
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path.write_text("") # drain
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return json.dumps(msgs, indent=2)
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```
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4. Each teammate checks its inbox before every LLM call, injecting received messages into context.
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```python
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def _teammate_loop(self, name, role, prompt):
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messages = [{"role": "user", "content": prompt}]
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for _ in range(50):
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inbox = BUS.read_inbox(name)
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if inbox != "[]":
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messages.append({"role": "user",
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"content": f"<inbox>{inbox}</inbox>"})
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response = client.messages.create(...)
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if response.stop_reason != "tool_use":
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break
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# execute tools, append results...
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self._find_member(name)["status"] = "idle"
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```
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## What Changed From s08
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| Component | Before (s08) | After (s09) |
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|----------------|------------------|----------------------------|
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| Tools | 6 | 9 (+spawn/send/read_inbox) |
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| Agents | Single | Lead + N teammates |
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| Persistence | None | config.json + JSONL inboxes|
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| Threads | Background cmds | Full agent loops per thread|
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| Lifecycle | Fire-and-forget | idle -> working -> idle |
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| Communication | None | message + broadcast |
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## Try It
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```sh
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cd learn-claude-code
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python agents/s09_agent_teams.py
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```
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1. `Spawn alice (coder) and bob (tester). Have alice send bob a message.`
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2. `Broadcast "status update: phase 1 complete" to all teammates`
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3. `Check the lead inbox for any messages`
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4. Type `/team` to see the team roster with statuses
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5. Type `/inbox` to manually check the lead's inbox
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