Kōsōsumi is a research-driven repository focused on building a clear and structured understanding of Artificial Intelligence, from foundational concepts to modern systems such as large language models and autonomous agents.
The name Kōsōsumi (構想墨) represents conceptual system design preserved in writing. This repository serves as a space to think through ideas carefully, study influential research, and document understanding in a deliberate and organized manner.
The purpose of this repository is to structure the AI learning process with intention and clarity. It aims to move beyond fragmented learning by organizing concepts, research papers, and reflections into a coherent progression.
This repository is designed to:
- Define a clear learning path from fundamentals to advanced AI systems
- Ground learning in both foundational and modern research papers
- Encourage depth of understanding rather than rapid or trend-driven coverage
- Support a gradual transition from learning concepts to reasoning about real-world AI systems
Kōsōsumi is a living project and will evolve as research focus and understanding mature.
This repository is focused on learning and research rather than production-ready code.
It is intended to support:
- Conceptual understanding of artificial intelligence and machine learning
- Reading, analyzing, and summarizing influential research papers
- Developing intuition about modern AI systems such as transformers, agents, and evaluation frameworks
It does not aim to be a complete course, a tutorial collection, or a finished curriculum.
kososumi/
│
├── README.md # Project overview and intent
├── ROADMAP.md # Structured AI learning roadmap
│
├── research/ # Curated research papers and analyses
│ ├── Devin's 2025 Performance Review.md
│ ├── Introducing SWE-1.5: Our Fast Agent Model.md
│
├── notes/ # Learning notes and reflections
├── projects/ # Practical experiments and implementations (planned)
├── resources/ # Courses, blogs, and reference material (planned)
│
└── .gitignore # Repository hygiene