AI ネイティブな開発プロセス、フルスタック SaaS、DX/AX 自動化を中心に、企画から実装・品質ゲート・運用までを高速に回すプロダクトビルダーです。日本語・英語・ロシア語のトリリンガルとして、国内外のチーム、顧客、AI エージェントをつなぐ開発コミュニケーションを得意にしています。
現在は GoDD (Governance-orchestrated Driven Development) を軸に、人間と AI エージェントが協調して開発するためのワークフロー、品質保証、仕様駆動の開発体験を磨いています。
| Project / Organization | What it is | Focus |
|---|---|---|
| AutoDevJapan / GoDD | Governance-orchestrated Driven Development を軸に、AI ネイティブな開発・品質ゲート・納品プロセスを設計 | AI agents, DX/AX, quality gates, delivery automation |
| BM1314 | 3D 体験を含む Web プロジェクトと、業務アプリ / SaaS / Web 機能のビルダー群を展開 | Interactive web, builder systems, product experience |
| NewTuber | YouTube 動画の取得・自動アップロードに関する自動化ツール領域 | Creator automation, media workflow, tooling |
| RealizeLearning | 学習・教育領域のプロダクト開発 Organization | EdTech, learning experience, product delivery |
| GovNoa | ガバナンス、業務設計、AI 活用を中心にした実験・開発 Organization | Governance, AI operations, workflow design |
| AI workflow experiments | ComfyUI などを含む生成 AI / 自動化ワークフローの検証 | Generative AI, workflow design, tooling |
GitHub README cannot run JavaScript, so the language "buttons" above jump to each language block instead of toggling the page dynamically.
仕様整理、顧客折衝、開発チームとの調整、AI エージェント運用まで、日本語での要件定義から実装完了までを一気通貫で進めます。
I build AI-native product workflows, full-stack SaaS systems, and delivery processes that connect product intent, engineering execution, and quality gates.
Я использую русский язык для коммуникации в международных командах, уточнения требований и сопровождения AI-native разработки от идеи до поставки.
Publicly shared GoDD case studies include:
- Large enterprise ERP delivery compressed from multi-month estimates to 7-8 day delivery windows
- Mid-sized AI / SaaS projects delivered by compact teams with AI-assisted development workflows
- Quality-first development through automated checks, spec alignment, and repeatable delivery processes
- DX/AX acceleration across product planning, implementation, review, and release operations
AI-native development systems
Full-stack SaaS products
Agentic coding workflows
Spec-driven / test-driven delivery
DX and AX automation
Interactive web experiences
RAG / LLM application foundations
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- Spec is the source of truth: requirements, acceptance criteria, and implementation stay aligned.
- AI should be governed, not improvised: speed only matters when quality and traceability survive.
- Small teams can ship big outcomes: strong process, automation, and review loops compound quickly.
- Products should feel alive: useful systems deserve sharp UX, clear feedback, and fast iteration.
- Agent orchestration for full development cycles
- Quality gates for AI-generated changes
- Faster handoff from idea to spec to implementation
- Generative AI workflows and ComfyUI-based experimentation
- Rich, interactive product experiences for the web