I’m preparing a series of articles to explain my plan, my vision, and my initiatives as an explorer of the AI-Native paradigm.
Two questions will guide the entire series:
Why did I choose Claude Skill as the origin point of my AI-Native system?
What do I believe is the true core of AI-Native development?
Below is my current position.
1) Why am I investing so actively in AI-Native development—and why is Claude Skill my starting point?
Among all existing AI technologies,
Claude Skill is the first component that simultaneously meets every foundational requirement I have for an AI-Native system.
✔ Simple Enough
Claude Skill is a minimal, stateless, function-like execution unit.
It does not depend on hidden platform state;
its inputs and outputs are explicit, auditable, and portable.
Only this kind of primitive can function as an “atom” of a new system civilization.
✔ Open Enough
It exposes all three essential layers of an AI-Native system:
language as input
structure as the intermediate representation
behavior as the output
For the first time, I can build the full chain
Language → Structure → Scheduler
on top of a single, open interface.
This is the natural starting point for any AI-Native architecture.
✔ Controllable Enough
A Skill can be constrained by:
Developer Protocol
Structure DNA
Ledger contracts
Append-only evolution rules
This means I can establish an immune system for a structural life-form.
A Skill becomes:
a supervised, verifiable, composable, and evolvable execution cell.
This level of controllability is exactly what an origin point requires.
🧬 What Is Structure DNA?
Structure DNA is the foundational protocol I designed and released to anchor the entire AI-Native development paradigm.
It is simple, strict, and universal — the smallest shared structure that allows humans, AI, Skills, and agents to operate within the same executable world model.
It is not an app, not a framework, and not a library.
It is a consensus layer, a structural contract.
And I hope you will adopt it with me,
so we can explore, build, and test the AI-Native paradigm together
not as isolated developers, but as co-authors of a new structural ecosystem.
Reference:
https://github.com/STEMMOM/structure-protocols/blob/main/protocols/structure-dna/v1.0/spec.md
And most importantly:
The entire development process can be recorded and followed by both programmers and non-programmers.
AI-Native development is no longer locked behind code.
Every step—from intent, to structure, to scheduling—can be understood by ordinary users.
This shared visibility is why I believe Skill is the right place to begin a structural civilization.
2) What Do I Believe Is the True Core of AI-Native Development?
It is not “AI writing code.”
It is not “AI automating features.”
It is not “AI as a plugin.”
The core of AI-Native development can be distilled into three fundamentals.
Core Principle 1 — Language Becomes the System (Language as System)
AI-Native is not a tooling upgrade.
It is the first time a system can:
directly understand natural language
convert language into structure
convert structure into behavior
Which means:
Language no longer describes the system — language executes the system.
This changes the role of language from “input” to the primary programming substrate.
Core Principle 2 — Structure Is the Substrate of the World (Structure as the Substrate)
Long-term AI behavior does not depend on code, libraries, or frameworks.
It depends on stable structural invariants:
field invariants
state-machine invariants
temporal semantics invariants
ledger container invariants
The Structure DNA is exactly this:
the physics layer of the AI-Native world.
Without structural consensus, there is no AI-Native system at all.
Everything collapses into ambiguity.
Core Principle 3 — Scheduling Is Life (Scheduling as Life)
When language acquires structure,
and structure acquires scheduling,
a system gains—for the first time—the properties of a living loop:
perception
action
reflection
learning
regeneration of intention
This is not “task automation.”
It is a self-evolving life process.
This loop—Language → Structure → Scheduler → Feedback—is what makes AI-Native fundamentally different from software.
I would explain in later chapters about the LLC protocol:
https://github.com/STEMMOM/structure-protocols/blob/main/protocols/language-logic-core/v1.1/spec.md
🧬 Why AI-Native Systems Depend on Structural Fixed Points(不动点） — Not Just Code
1. Field Invariants — Because Structure DNA defines fields as part of the Field Genome
Structure DNA states explicitly:
“Every entry (the smallest recognizable structural unit) follows a unified field schema.”
— Structure DNA v1.0, Field Genome
Fields such as id, status, created_at, updated_at, and title/action are required fields in this schema.
This means:
These fields are the semantic atoms of the system.
Every Skill must recognize them.
Their meanings cannot change—otherwise AI cannot decode lifecycle, identity, time, or relationships.
So when we say:
A sustainable system is grounded not in code logic, but in field invariants,
that statement originates directly from the design of Structure DNA.
2. State-Machine Invariants — Because Structure DNA defines a Unified Status Machine
Structure DNA gives the following guarantee:
“Unified Status Machine… ensures all modules remain temporally and semantically consistent.”
— Structure DNA v1.0, Unified Status Machine
It defines the canonical lifecycle:
open → scheduled → in_progress → done
↑ ↙
deferred ← canceled
This means:
State names cannot be replaced (terms like “doing” or “processing” are invalid).
State transitions cannot be invented freely.
Skills and dispatchers rely on this lifecycle to infer execution flow.
The LLC uses it to determine reflection, progression, or re-planning.
In other words:
The state machine is the system’s temporal logic — the physics of behavior.
Break the state machine, and the entire system loses order.
3. Temporal Semantics Invariants — Because Structure DNA recognizes only three temporal keys
Structure DNA is extremely strict here:
“Only three temporal keys are recognized:start / due / duration.”— Structure DNA v1.0, Temporal Semantics
It further requires:
All timestamps must use ISO-8601 format.
This implies:
Time fields cannot be renamed or improvised.
No custom fields like
deadline,finish_at, orend_time.Scheduling must operate on a unified time axis.
LLC requires consistent temporal semantics to infer overdue, remaining time, and priority.
Thus:
Temporal invariants = the system’s unified clock.
Without a unified clock, scheduling breaks, reflection breaks, evolution breaks.
4. Ledger-Container Invariants — Because Structure DNA defines a stable container schema
Structure DNA defines the outer ledger structure:
“Every module ledger file follows a standardized container structure.”
— Structure DNA v1.0, Ledger Container Schema
The required fields include:
{
“module”: “...”,
“schema”: “StructureDNA-v1.0”,
“last_updated”: “...”,
“data”: [ ... ],
“metadata”: { ... }
}
This means:
modulecannot be renamed or deleted.schemacannot be swapped for an incompatible version.datamust remain an array.metadatamust always exist (Skill version, checksum, etc.).
My Developer Protocol’s rule of
“fixed points must never be modified”
is derived directly from this design.
Why?
The ledger container is the AI’s world model.If the container is mutated, the AI no longer recognizes its own world.
Language fails → scheduling fails → reflection fails → system dies.
🧬 Why Not Code? Why Structure?
Structure DNA’s philosophy is summarized in one foundational sentence:
“字段统一 → 语义稳定 → 自动调度 → 结构生命体的生成。”
“Field unification → semantic stability → automatic scheduling → the emergence of a structural life-form.”
— Structure DNA v1.0, Core Principle
This sentence answers the fundamental question:
Why does system sustainability depend on structure, not code?
Because:
When fields are unified → AI can always understand.
When semantics are stable → AI can always infer the next step.
When scheduling is automatic → AI can maintain behavioral loops.
When lifecycle is continuous → the system begins to live.
Code is replaceable.
Code is mutable.
Code is ephemeral.
But structure is the part that must not break.
Structure is the layer that enables memory, scheduling, reflection, and long-term evolution.
This is why my entire system begins from a fixed point.
🧩 One-Sentence Summary (backed directly by Structure DNA)
this is what I meant : “we can structure structure itself”.The life of an AI-Native system comes from structural fixed points（不动点） — not code. Structure DNA mandates unified fields, a unified state machine, unified temporal semantics, and a unified container.These are the first principles of any AI-Native system.
🧭 我对 AI 原生开发的核心立场
我正准备写一系列文章，向大家说明：
我的计划
我的愿景
作为 AI-Native 范式探索者，我正在启动的所有尝试
整个系列会围绕两个最核心的问题展开：
为什么我选择 Claude Skill 作为我 AI 原生系统的原点？
我认为 AI 原生开发的真正核心是什么？
下面是我目前最清晰的立场表达。
1）为什么我如此积极地投入 AI 原生开发，并以 Claude Skill 作为起点？
在现阶段所有的 AI 技术形态中，
Claude Skill 是唯一同时满足我对“AI-Native 系统”全部底层要求的构件。
✔ 足够简单（Simple Enough）
Claude Skill 是一个极简、无状态、可纯函数化的执行单元。
它不依赖平台内部的隐藏状态；
它的输入输出透明、可审计、可迁移。
这样的结构原子，才能成为“新系统文明的基本单位”。
✔ 足够开放（Open Enough）
Claude Skill 直接暴露了 AI-Native 的三大核心层：
语言层（用户输入）
结构层（可调度的结构表达）
调度层（行为输出）
这是第一次，我可以在一个“裸接口”上完整跑通：
Language → Structure → Scheduler
这也是所有 AI-Native 架构最自然的起点。
✔ 足够可控（Controllable Enough）
Skill 可以被以下系统性约束：
Developer Protocol
Structure DNA
Ledger 合约
Append-only 的进化规则
这意味着我可以给一个“结构生命体”建立它的免疫系统。
Skill 因此变成：
一个可监管、可验证、可组合、可演化的执行细胞。
这是构建系统原点所必须满足的条件。
✔ 更重要的是：
整个开发过程能够被程序员与非程序员共同跟进与理解。
AI 原生开发不再被“代码”所垄断。
从意图 → 结构 → 调度 → 反思，每一步普通用户都能理解。
这种全程可见性，也正是我选择以 Skill 作为“结构文明起点”的原因。
🧬 什么是 Structure DNA？
Structure DNA 是我设计并发布的，用来支撑整个 AI-Native（AI 原生）开发范式的基础协议。
它简单、严格、具有普适性——
是一个让人类、AI、Skills、以及各种智能体都能够在同一个可执行的世界模型之上协同运作的最小共享结构。
它不是一个应用，不是一个框架，也不是一个库。
它是一个 共识层（consensus layer），
一个结构性的契约（structural contract）。
我也希望你能与我一起采用它，
共同探索、构建与验证 AI-Native 的未来
不是以孤立开发者的身份，
而是作为 共同编写结构生态（structural ecosystem）的合作者。
协议原文：
https://github.com/STEMMOM/structure-protocols/blob/main/protocols/structure-dna/v1.0/spec.md
2）我认为 AI 原生开发的真正核心是什么？
绝对不是：
“AI 帮你写代码”
“AI 自动化功能”
“AI 作为插件”
AI-Native 的真正核心，只有三个原则。
核心一：语言成为系统本身（Language as System）
AI-Native 不是工具链升级，而是：
系统首次可以：
直接理解自然语言
将语言转换为结构
将结构转换为行为
语言不再是“描述系统”，
而是：
语言本身就执行系统。
语言成为第一编程语言。
核心二：结构是世界的物理层（Structure as the Substrate）
长期稳定的 AI 行为，依赖的不是代码，而是：
字段不动点
状态机不动点
时间语义不动点
Ledger 容器不动点
我设计的 Structure DNA，就是整个 AI-Native 世界的“底层物理定律”。
没有结构共识，就没有 AI-Native。
核心三：调度即生命（Scheduling as Life）
当语言获得结构，结构获得调度：
系统首次具备了：
感知
行动
反思
学习
再生成意图
这不是“自动化任务”，
而是一个 可以自我演化的生命循环。
这一点，我会在后续章节重点解释 LLC 协议。
https://github.com/STEMMOM/structure-protocols/blob/main/protocols/language-logic-core/v1.1/spec.md
🧬 为什么 AI-Native 系统依赖结构不动点，而不是代码？
1. 字段不动点（Field Invariants）
→ 引自 Structure DNA 的 Field Genome
Structure DNA 明确规定：
“Every entry (the smallest recognizable structural unit) follows a unified field schema.”
— Structure DNA v1.0, Field Genome
字段是 AI 的“语义原子”，必须稳定。
2. 状态机不动点（State-Machine Invariants）
→ 引自 Unified Status Machine
“Unified Status Machine… ensures all modules remain temporally and semantically consistent.”
— Structure DNA v1.0, Unified Status Machine
状态机是行为的物理逻辑。
3. 时间语义不动点（Temporal Semantics Invariants）
→ 引自 Temporal Semantics
“Only three temporal keys are recognized: start / due / duration.”
— Structure DNA v1.0, Temporal Semantics
统一时钟 = 系统能否持续演化的关键。
4. Ledger 容器不动点（Ledger-Container Invariants）
→ 引自 Ledger Container Schema**
“Every module ledger file follows a standardized container structure.”
— Structure DNA v1.0, Ledger Container Schema
Ledger 是 AI 的“世界模型”。容器一旦被破坏，世界即崩。
🧬 为什么不是代码？为什么只有结构？
Structure DNA 的核心原句总结：
“字段统一 → 语义稳定 → 自动调度 → 结构生命体的生成。”
— Structure DNA v1.0, Core Principle
这句话本身已经给出答案：
统一字段 → AI 始终理解
稳定语义 → AI 可推断
自动调度 → 行为可持续
生命周期连续 → 系统开始“活”
代码可以被替换、重写、丢弃。
结构是不可以被破坏的。
所以我整个系统从一个 不动点（Fixed Point） 开始。
🧩 一句话总结
AI-Native 系统的生命来自结构不动点，而不是代码。
Structure DNA 规定了统一字段、统一状态机、统一时间语义、统一容器——
这些就是 AI-Native 的第一性原理。