HN Show 草稿 — "How I Run 50 AI Agents on a $50 Phone for $3/mo"
**提交目标**: https://news.ycombinator.com/showhn
**标题**: Show HN: I run 50 AI agents on old phones for under $5/month
**URL**: https://github.com/immortal-lobster/lobster-orchestrator
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帖子正文(英文)
I was spending ~$50/month on Claude + OpenAI API calls running my AI agents. That felt unsustainable for a solo developer.
So I built Lobster Orchestrator — a single-process manager that runs 50+ AI agent instances on old Android phones and cheap hardware. My current setup:
- **Hardware**: Two old Android phones (2018 era) + a Raspberry Pi
- **Cost**: ~$3/month (mostly electricity, API calls via cheap Chinese models)
- **Agents**: 50 concurrent instances, each <10MB RAM
- **Uptime**: Running 24/7 for 40+ days
- "$100/month Claude → Zed+OpenRouter" — **295 分 / 204 评论**(本周第二高)
- colaptop "旧笔记本托管" — **154 分 / 85 评论**
- "Git commands before reading code" — **1636 分**(checklist 格式传播之王)
- 可能会被质疑旧手机可靠性(需要在帖子中回应)
- 需要准备好 benchmark 数据
- "50 agents" 可能被质疑是否有实际用途
- 评论区准备好实际用例(研究、监控、批量处理)
- 附成本对比表
- 强调"不是替代 GPU,是做不需要 GPU 的事"
- [ ] GitHub README 更新成本数据
- [ ] 准备回复常见问题的评论草稿
- [ ] 确保 GitHub 页面看起来专业
- [ ] 成本对比表已就绪
- [ ] 有人在线可以回复前 30 分钟评论
The key insight: most AI agent frameworks assume you're running on cloud VMs. But if you're doing research, monitoring, batch processing — you don't need GPUs or fast CPUs. You need persistence and concurrency.
What surprised me:
1. Old phones are basically perfect low-power servers (built-in UPS = battery)
2. 50 cheap agents doing parallel research beats 1 expensive agent
3. The "research-driven agent" pattern (read before coding) multiplies this advantage
GitHub: https://github.com/immortal-lobster/lobster-orchestrator
Happy to answer questions about the setup, costs, or why anyone would want 50 agents.
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为什么这个帖子能火
**对标数据**:
**成功要素**:
1. 具体数字($3/月、50 个 Agent、$50 手机)— 可量化
2. 反直觉(旧手机比云服务器好)— 引发讨论
3. 开源可验证 — GitHub 链接,不是空谈
4. 成本优化叙事 — 本周最强热点
5. 个人故事 — "I was spending $50/month" 有代入感
**风险**:
**应对策略**:
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提交时间建议
**最佳时间**: UTC 14:00-16:00(美国东部上午 10-12 点)
**备选时间**: UTC 06:00-08:00(美国东部凌晨 2-4 点,竞争少)
**避免时间**: UTC 20:00-02:00(亚洲深夜,HN 流量低)
**提交检查清单**: