延续层：智能为何需要承载信息的架构基础
The Continuity Layer: Why Intelligence Needs an Architecture for What It Carries Forward
April 19, 2026
作者: Samuel Sameer Tanguturi
cs.AI
摘要
人工智能领域最核心的架构问题并非模型规模，而是缺乏承载模型认知延续性的结构层。会话会终止，上下文窗口会饱和，记忆接口返回的扁平化数据迫使模型每次读取时都需重新解析。这导致智能体在单次会话中表现卓越，却无法实现跨时间维度的记忆延续。本文主张：解决这一问题的连续性层级是本领域尚未构建但最具影响力的基础设施，其工程实践已进入公开实施阶段。
针对该特性的正式评估框架ATANT基准（arXiv:2604.06710）已单独发布，包含对250篇故事集的评测结果；配套论文（arXiv:2604.10981）将该框架与现有记忆、长上下文及智能体记忆基准进行对比。本文明确定义连续性作为系统属性的七大特征（区别于记忆与检索功能）；阐述通过写时分解与读时重构实现该特性的存储原语（解构轨迹收敛记忆）；将工程架构映射至神学的虚己模式与符号学的阿尔法-欧米伽范式，论证这种映射属于结构同构而非隐喻类比；提出从外部SDK到硬件节点再到长期人类基础设施的四层发展路径；解析当前制约模型层的物理极限如何凸显连续性层的关键意义；并论证治理架构（以物理机制而非政策条款实现隐私保护，创始人通过不可协商的架构承诺持有特别股权）与产品本体不可分割。
English
The most important architectural problem in AI is not the size of the model but the absence of a layer that carries forward what the model has come to understand. Sessions end. Context windows fill. Memory APIs return flat facts that the model has to reinterpret from scratch on every read. The result is intelligence that is powerful per session and amnesiac across time. This position paper argues that the layer which fixes this, the continuity layer, is the most consequential piece of infrastructure the field has not yet built, and that the engineering work to build it has begun in public. The formal evaluation framework for the property described here is the ATANT benchmark (arXiv:2604.06710), published separately with evaluation results on a 250-story corpus; a companion paper (arXiv:2604.10981) positions this framework against existing memory, long-context, and agentic-memory benchmarks. The paper defines continuity as a system property with seven required characteristics, distinct from memory and from retrieval; describes a storage primitive (Decomposed Trace Convergence Memory) whose write-time decomposition and read-time reconstruction produce that property; maps the engineering architecture to the theological pattern of kenosis and the symbolic pattern of Alpha and Omega, and argues this mapping is structural rather than metaphorical; proposes a four-layer development arc from external SDK to hardware node to long-horizon human infrastructure; examines why the physics limits now constraining the model layer make the continuity layer newly consequential; and argues that the governance architecture (privacy implemented as physics rather than policy, founder-controlled class shares on non-negotiable architectural commitments) is inseparable from the product itself.