AI-native 转型路径，端到端

What should my engineering org look like in 12 months? That's the question underneath every AI tool evaluation, every POC, every seat license debate. And it makes sense: the first step to provisioning a team is to understand what their day-to-day looks like and what they need. We can’t buy tools without knowing what shape an org will be.

我的工程组织在 12 个月后应该是什么样子？这是每个 AI 工具评估、每个 POC、每个席位许可辩论背后的潜在问题。这是有道理的：为团队配置的第一步是了解他们的日常工作是什么以及他们需要什么。我们不能在不知道组织将是什么形状的情况下购买工具。

Our CEO Matt wrote about why this age of AI is a transformation problem, not a tooling problem. Our VP Eng Vinay wrote about what breaks when you move fast without solving for confidence. This post is the map. Four stages of transformation, what changes at each one, and what the operating model looks like when you get there.

我们的 CEO Matt 写到 为什么 AI 时代是一个转型问题，而不是工具问题。我们的 VP Eng Vinay 写到 当你快速前进而不解决信心问题时会崩溃什么。这篇文章是地图。四阶段转型、每一阶段的变化，以及到达那里时的运营模式。

Four stages of AI transformation: orchestration is the goal

AI 转型的四个阶段：编排是目标

We see organizations move through the AI-native transformation in four stages. Most are in stage one. The ones pulling ahead have reached stage three. Almost no one is at stage 4, full orchestration, yet.

我们看到组织通过四个阶段进行 AI 原生转型。大多数处于第一阶段。领先者已达到第三阶段。几乎没有人达到阶段 4，完全编排。

The transformation path: from agent adoption to agent orchestration. Most organizations (~70%) are still in stage one — integrating agents into daily workflows. Fewer than 10% have agents owning work autonomously, and almost none have reached full agentic orchestration.

转型路径：从 Agent 采用到 Agent 编排。大多数组织（约 70%）仍处于第一阶段——将 Agent 集成到日常工作流程中。不到 10% 的组织让 Agent 自主拥有工作，几乎没有达到完全的 Agentic 编排。