Combination Method (Ko Method) — A Discovery.

An LLM workflow pattern for precision design tasks, discovered 2026-06-01 during deLight house Phase 03 CAD work. This deposit contains bilingual versions of the same canonical document: · Korean original (...A Discovery.pdf, 13 pages) · English translation (...A Discovery (EN).pdf, 15 pages)Both versions are content-identical and use the formal academic tone. Core principle: Aggregation + Combination. The methodology compresses scattered domain knowledge into structured categories (Phase A: Aggregation), then algorithmically combines those categories to explore candidate solutions filtered by a numeric-then-semantic compound threshold (Phase B: Combination). The LLM is used as aggregator + refiner only — combinatorial search is delegated to deterministic algorithms (Python) and semantic evaluation to lightweight models (Haiku). Four stages + Human gate:1. Data Acquisition (Sonnet)2. Decomposition into categories (Sonnet → Haiku when ontology cached)3. Combinatorial Sampling + Compound Threshold (Python numeric → Haiku semantic)4. Refinement (Sonnet)+ Human Confirmation Gate Six derived sub-principles:- LLM as aggregator-refiner, not generator- Complexity-to-capability matching (model routing)- Determinism where possible- Compound threshold (cheap-first filtering)- Cumulative memory (ontology caching, amortized inference)- Human-at-confirmation, not generation First case validated: deLight house interior stair (14 risers × 178.57 mm rise × 280 mm tread). Cost ~10% of single-pass Opus generation, with improved accuracy, reproducibility, and debuggability. This is v1.1 (2026-06-05) — formal academic tone with theoretical foundation, case-study trace, and six derived sub-principles. Document is also publicly anchored via:- GitHub commit 27ee91e (2026-06-05) at https://github.com/vycanisko/DSI- OpenTimestamps Bitcoin blockchain anchor (commit 3c539c0)- dsi.run/research/combination-method- dsi.run/research/combination-method-en.pdf (English version)