π¬π§ English | π―π΅ ζ₯ζ¬θͺ
After 12 years running a cram school (from founding the LLC to winding it down), I moved into engineering. I now work at an SES company, leading development standardization β CI/CD, IaC, testing, and unified documentation β as part of an engineering team on contract projects. In parallel, I serve as an external CTO for a condominium management company, driving DX on-site. Having watched tools get introduced only to fall out of use in management settings, my approach centers on leaving existing operations untouched while inserting automation behind the scenes.
| nfc-attendance-kit | Auto-aggregates NFC time clock punches into a spreadsheet, running in production for a real client (β5h/month) |
| excel-kanri | Retrofits existing Excel-based paperwork operations with a web form, PDF conversion, and full-text search, running in production for a real client |
| bt-lab | An 8-stage pipeline that cross-validates multiple strategy candidates and automatically selects among them by drawdown and Recovery Factor |
| bt-dynamic | A backtesting core that switches regimes across 9 cells (trend strength Γ volatility), distributed on PyPI |
| live-dynamic | An execution layer that runs validated strategies unattended via systemd timer with the same config, live. Published as a reference implementation for safety design covering idempotent order gating, OCO, and kill switches |
| folio-agent | A CAG-style portfolio chat that bundles all knowledge inline, published on npm and running on Cloudflare Workers |
| order-system-migration | Migrated WinForms to .NET 10 Web API + React, with an integrated AI agent |
| attendance-system-migration | Migrated WebForms to .NET 10 + React, with real-time monitoring via SignalR |
| order-system-rag | Structures paperwork PDFs and automatically routes questions between Text-to-SQL and RAG based on their nature |
| wiki-guessur | A benchmark for identifying Wikipedia articles with their defining sentences removed. Measures MRR across 4 methods (formula / GBDT / LLM re-ranking) Γ 5 seeds |
Development runs in two phases. In the startup phase, spec documents (PLAN.md / JUDGE.md) drive development, then get distilled into the README at release and retire. In the maintenance phase, the driving documents hand off to a guarantee ledger (guarantees.md) β humans authorize only "what must never break," while AI and CI own test implementation and enforcement (Guarantee-Driven Development).
The execution mechanism is issue-driven, separating design (conversational AI), implementation (autonomous AI), and authorization/verification (human merge). Dangerous operations are blocked not by operational rules but by deny entries in .claude/settings.json, and the execution environment is declaratively unified with Nix Flakes and continuously verified in CI.
This entire system is published as dotfiles-public, and the general-purpose skills can be installed as a Claude Code plugin marketplace. The process is left as-is in each repository's issues and PRs.