2026
| Date | Kind | Event | Category | Title | Summary |
|---|---|---|---|---|---|
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2026-03-30 |
Article |
New |
SimpleModeling integrates BoK, literate models, DSL, and execution platforms to extend Harness Engineering into a foundation that governs execution based on meaning. It reduces gaps between specification and implementation and enables consistent quality and reproducibility required in the AI era. |
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2026-03-23 |
Article |
New |
The Philosophy of 1.5hop+: Meaning-Oriented Concept Neighborhoods |
1.5hop+ is a knowledge graph exploration approach that constructs concept neighborhoods based on semantic structure rather than fixed traversal distance. By leveraging CML/UML metamodel structures, it provides sufficient semantic context for generative AI, balancing accuracy and efficiency. |
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2026-03-16 |
Article |
New |
In the previous article, we organized the development process for the AI era by positioning the Unified Process as the structural backbone of the process and Component-Based Development as the central structure of development. The Unified Process defines the software development process through three core principles: Iterative & Incremental development, Architecture-Centric design, and Use-Case Driven development. These principles remain valid even in the age of AI. However, in an environment where AI-based code generation has become commonplace, the meaning and role of each principle need to be understood somewhat differently from how they were interpreted in the past. In this article, we revisit the three fundamental principles of the Unified Process as a guide and re-examine the nature of the development process in the AI era. |
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2026-03-09 |
Article |
New |
In the AI era of software development, the design of system structure becomes more important than the capability of code generation. This article organizes a basic framework for AI-assisted development, using the Unified Process (UP) as the backbone of the process and Component-Based Development (CBD) as the central architectural structure. |
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2026-03-02 |
Article |
New |
While AI accelerates software development, it has also introduced a new challenge: structural instability. This article revisits the contemporary value of CBD by examining not only its original structural strengths, but also its role in the AI era—through structural constraints that improve generation accuracy, boundaries and specifications that suppress instability, and reusability enhanced by AI. CBD should not be regarded merely as a reuse technique, but rather be re-evaluated as a foundational technology that stabilizes development in an AI-first era. |
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2026-02-23 |
Article |
New |
CBD Enabled by DSL and Execution Platform: Implementable Component Structure |
This article argues that through the combination of a DSL and an execution platform, CBD becomes an implementable structural reality. By rigorously defining analysis models as a DSL in Cozy and structurally guaranteeing those specifications at runtime through CNCF, components become not merely design concepts but concrete entities that can be registered, discovered, and connected. Furthermore, by integrating a cloud-native architecture centered on CQRS, the externalization of quality attributes, and asynchronous abstraction, CBD is redefined as an executable architectural unit suited for the AI era. |
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2026-02-16 |
Article |
New |
This article integratively organizes the development process, CBD, DSL, code generation, and execution platform (CNCF)—previously discussed separately—into a single vertical stack. In SimpleModeling, knowledge organized in the BoK is reflected in the literate model, defined structurally as a DSL, and guaranteed by the CNCF execution platform, forming an end-to-end architecture. AI not only supports understanding, structuring, generation, and validation at each layer, but also functions as a mediating device that connects them across layers. When this vertical continuity is established, the natural language world and the implementation technology world are no longer divided, enabling an evolvable development stack that preserves structural integrity. |
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2026-02-09 |
Article |
New |
This article uses the Unified Process (UP) as a guiding framework to reorganize software development processes and project management in the AI era. In particular, it clarifies how the role of AI changes across the phases of inception, elaboration, construction, and transition. |
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2026-02-09 |
Glossary |
New |
The phase in which the system is implemented at scale through iterations, based on the architecture baseline established during the elaboration phase. In the AI era, this phase refers to the stage where AI becomes the primary implementation agent, generating large volumes of code and tests with consistent quality under given structures and constraints. |
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2026-02-09 |
Glossary |
New |
The phase in which the developed software is transitioned into actual operation and delivered to users. In the AI era, it is positioned as a context-update phase that captures insights from usage and operation and feeds them into the next inception phase. |
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2026-02-09 |
Glossary |
New |
The phase in which the system’s structural backbone is established by advancing analysis and design based on the requirements and directions defined in the inception phase. In the AI era, its most critical role is to refine context, boundaries, and assumptions, eliminating ambiguity and contradiction, and to establish the architecture baseline referenced by the AI. |
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2026-02-09 |
Glossary |
New |
The phase in which the project’s goals, problem domain, and scope are defined, and the value and feasibility to be validated are clarified. In the AI era, its central role shifts from fixing detailed specifications to defining the outline of the context shared between humans and AI. |
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2026-02-02 |
Article |
New |
This article examines how the premises of development processes are changing with the advent of generative AI, using the characteristics of the Unified Process as a comparative axis against agile development. In the AI era, not only programs but also natural-language artifacts such as models, specifications, and design documents become primary sources of truth. Under this premise, the Unified Process—designed as a model-centric framework—serves as a valuable reference for rethinking development processes that collaborate with AI. |
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2026-01-26 |
Article |
New |
SimpleModeling is a development methodology based on component-oriented principles. To make component-oriented development viable, an execution system for components is required in addition to the definition of conceptual models. For this purpose, the Cloud Native Component Framework has been developed as a component framework for cloud applications that run on cloud platforms. In this article, we will explore the execution model of the Cloud Native Component Framework through a HelloWorld example. |
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2026-01-19 |
Article |
New |
The shortest path to understanding CNCF is to actually run it first. By starting with command execution and moving on to server, client, and custom components, you can confirm that the internal execution model remains the same even when the execution form changes. |
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2026-01-19 |
Glossary |
New |
Cloud Native Component Framework (CNCF) is a framework for executing cloud application components using a single, consistent execution model. Centered on the structure of Component, Service, and Operation, it enables the same Operation to be reused across different execution forms such as command, server (REST / OpenAPI), client, and script. By centralizing quality attributes required for cloud applications—such as logging, error handling, configuration, and deployment—within the framework, components can focus on implementing domain logic. CNCF is designed as an execution foundation for literate model-driven development and AI-assisted development, separating what is executed from how it is invoked. |
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2026-01-12 |
Article |
New |
In the AI era of software development, it is essential to cultivate specifications, design, and implementation together without isolating them, allowing continuous movement between these activities. This article organizes a practical SimpleModeling approach centered on executable specifications (Executable Specifications), including up-and-down movement of analysis models and pair analysis / pair design with AI. |
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2026-01-12 |
Glossary |
New |
Verification is the activity of confirming that an implementation conforms to its specified design or requirements. |
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2026-01-12 |
Glossary |
New |
Test Driven Development (TDD) is a development practice in which tests are written before implementation, and the code is evolved by repeatedly making tests pass and refactoring. |
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2026-01-12 |
Glossary |
New |
Behavior Driven Development (BDD) is a development approach that focuses on specifying system behavior through scenarios written in a shared language. |
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2026-01-12 |
Glossary |
New |
An executable specification is a specification expressed in a form that can be executed to determine correctness. |
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2026-01-12 |
Glossary |
New |
Validation is the activity of confirming that a system or product fulfills its intended use and stakeholder requirements. |
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2026-01-05 |
Article |
New |
This article summarizes the current state of my personal AI-driven development approach, in which ChatGPT and VS Code Codex are used selectively to rapidly iterate through specification, design, implementation, and verification. |