feat: rewrite Poimen system prompt with full story arc + update experience descriptions

- Humble, learning-curious tone throughout
- Chapter arc: AWS (customer obsession) → RBC (IaC/drift) → Homelab (AI at scale) → Poimen (agent system)
- Homelab: hardware journey, etcd latency lesson, GitOps evolution, paperless.riotpiao.com
- RBC: apply resilience (JFrog, plan/apply split) + drift detection (nightly cron → Slack)
- AWS: deployment alignment story, redrive execution, backward compat
- Poimen: memory-augmented routing, skill factory vision
- Updated EN + ZH experience descriptions

lib/translations.json

@@ -227,19 +227,19 @@
           "company": "riotpiao.com",
           "role": "DevOps / SRE / SDE",
           "period": "May 2025 — Present",
-          "description": "Architected and operates a production-grade, self-hosted cloud platform on bare-metal Kubernetes—featuring OIDC SSO with RBAC, GitOps-driven infrastructure, CI/CD with container registry, Kafka message queuing, managed PostgreSQL, S3-compatible object storage, GPU-accelerated LLM inference, and workflow orchestration. Essentially AWS rebuilt from scratch at home."
+          "description": "Wanted to understand how LLM serving works at scale—so built an entire cloud platform from scratch on bare-metal K8s. 4 machines (1 GPU node, 1 Dell PowerEdge R520, 2 mini-desktops), 3 control planes for distributed consensus. Learned etcd needs low-latency the hard way—powerline adapters spiked 200ms with 30+ pods, killing consensus. Ran ethernet to the garage. Purchased riotpiao.com from Cloudflare with wildcard DNS. Evolved GitOps from pure Terraform to Terraform (Talos config, barely changes) + ArgoCD (CRD-driven observer pattern for K8s resources). Unified IAM with Authentik OIDC, deployed paperless.riotpiao.com for document workflow integration. Now building Poimen—an AI agent system where the right context + small model = successful task inference."
         },
         {
           "company": "RBC",
           "role": "Lead Software Engineer",
           "period": "Nov 2024 — May 2026",
-          "description": "Deployments were manual and slow—teams blocked 2+ hours waiting. Chose Terraform for idempotent drift handling, Temporal for multi-cloud orchestration with built-in retry. Cut deploy time to 20min, consolidated public cloud and on-prem into single platform with 99.2% automation and notification-driven operator fallback."
+          "description": "Learned Terraform and Temporal here—tools fundamental for hosting infra at ease. Tackled two big problems: (1) Flaky deployments—500+ resource state files timing out, 503 errors, lock contention. Fixed by migrating to JFrog Artifactory, splitting plan/apply phases with immutable artifacts, throttling parallelism. Zero state corruption after. (2) Configuration drift—engineers hotfixing in cloud console, code detached from reality. Built nightly cron drift detection with Slack alerts, cut drift visibility from 3 weeks to <24hrs. Key takeaway: Terraform shines when things barely change; for K8s resources that churn, you need ArgoCD."
         },
         {
           "company": "AWS",
           "role": "Senior Software Engineer (Step Functions)",
           "period": "2022 — 2024",
-          "description": "Owned Distributed-Map from design doc to production launch across 57+ regions. Full lifecycle: planning, implementation, oncall, status reporting—we built it, we fixed what we broke."
+          "description": "First job out of grad school—learned STAR method and customer obsession at scale. Owned Distributed-Map end-to-end across 57+ regions, sub-100ms P99. Caught a potentially customer-impacting condition field change during code review and coordinated simultaneous frontend+backend deployment—because deployment alignment keeps the business running. Built Redrive Execution for customers to retry from failure point, plus ops tools. Learned backward-compat is critical when frontend consumes latest images. Owned oncall, built CloudWatch dashboards, wrote runbooks."
         },
         {
           "company": "Titus",
@@ -494,19 +494,19 @@
           "company": "riotpiao.com",
           "role": "DevOps / SRE / 软件开发",
           "period": "2025年5月 — 至今",
-          "description": "在裸机Kubernetes上架构并运维生产级自托管云平台——具备OIDC SSO + RBAC、GitOps驱动的基础设施、CI/CD容器仓库、Kafka消息队列、托管PostgreSQL、S3兼容对象存储、GPU加速LLM推理、工作流编排。相当于在家从零重建AWS。"
+          "description": "想理解LLM大规模服务的原理——于是在裸机K8s上从零构建了完整的云平台。4台机器（1 GPU节点、1台Dell PowerEdge R520、2台迷你主机），3个控制平面做分布式共识。经历了etcd延迟的教训——电力线适配器在30+pod时延迟飙升200ms，导致共识崩溃。从实践中学习，GitOps从Terraform演进为Terraform（Talos配置）+ ArgoCD（CRD观察者模式）。统一Authentik OIDC身份认证，部署paperless.riotpiao.com用于文档工作流集成。现在正在构建Poimen——一个AI智能体系统，正确的上下文+小模型=成功的任务推理。"
         },
         {
           "company": "RBC",
           "role": "技术主管",
           "period": "2024年11月 — 2026年5月",
-          "description": "部署流程手动且缓慢——团队等待2+小时。选择Terraform处理幂等漂移，Temporal用于多云编排和内置重试。将部署时间缩短至20分钟，整合公有云和本地部署为统一平台，99.2%自动化，通知驱动的运维人员兜底机制。"
+          "description": "在这里学习了Terraform和Temporal——让基础设施托管变得简单的核心工具。解决了两个大问题：(1)不稳定部署——500+资源的状态文件超时、503错误、锁竞争。迁移到JFrog Artifactory，拆分plan/apply阶段为不可变制品，限流并行度。零状态损坏。(2)配置漂移——工程师在控制台热修复，代码与现实脱节。构建夜间cron漂移检测+Slack告警，漂移可见性从3周缩短到<24小时。核心心得：Terraform适合很少变化的东西；K8s资源频繁变动时需要ArgoCD。"
         },
         {
           "company": "AWS",
           "role": "高级软件工程师 (Step Functions)",
           "period": "2022 — 2024",
-          "description": "负责Distributed-Map从设计文档到57+区域生产发布的全生命周期。完整流程：规划、实现、oncall、状态汇报——我们构建，我们修复。"
+          "description": "毕业后第一份工作——学习了STAR方法和大规模组织中的客户至上。端到端拥有Distributed-Map，跨57+区域、P99<100ms。在代码审查中发现潜在影响客户的条件字段变更，协调前后端同步部署——因为部署对齐是业务持续运行的关键。构建Redrive Execution让客户从失败点重试。认识到前端消费最新镜像时后向兼容至关重要。"
         },
         {
           "company": "Titus",