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.

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.

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。

从 ERP 到 AI Platform 的建设脉络看，企业级 AI 落地的真正前置条件不是模型和 Agent 框架，而是可计算、可治理的数据与业务建模体系。

用一个代词指代的例子，从 RNN 的局限性讲到 Transformer 如何通过"同时看所有词"来解决问题。