介绍 Paseo 这个开源的多供应商 AI coding agent 编排工具，从实际使用场景出发，说明它解决了什么问题、怎么工作的、以及还有哪些不足。

在 AI platform adoption 之后，整理 Requirement Impact Analysis、CI Failure Triage、Release Evidence Summarization 的 workflow、task、context、tool、policy 全量清单。

A story about how policy and access control were actually adopted in the AI platform, when the policy engine was invoked, and how we kept tools and writes under control.

从 Requirement Impact Analysis 这个 case 出发，比较 LangChain/LangGraph 与 CrewAI 在企业原型速度、状态管理、审批治理和长期维护上的取舍。

A follow-up case story on how the primitive model changed after feedback, why workflow and agent were merged into one orchestrator layer, and how three enterprise cases shaped the platform contract.

A case story about how we defined reusable AI platform primitives across departments - task, context, tool, model, policy, evaluation, and workflow.

从一次反复“失忆”的协作经历出发，讲清 OpenClaw 的短期记忆、长期记忆、/new、MEMORY.md 和 Memory Search 应该怎么配合。

A short manifesto from several months of enterprise AI adoption work, explaining why predictability, AI-native design, precise execution, and accountability matter more than raw model capability.

通过一个真实案例，拆解跨端 AI 协作中的统一记忆设计：为什么不能同步聊天记录、为什么要以任务为中心建模、以及如何在权限可控的前提下实现可恢复工作流。

结合一个通用的内部项目经验，说明如何用同步层、ontology 层和轻量 CLI 组织数据驱动的代码库。