Index of everything on this site: https://ai.hiina.space/index.md
The idea is not new in its parts, and that is the encouraging finding. Localisers have always layered voice on top of a neutral source, fan teams have shipped honorific toggles where the transform is closed-class, NLG showed that a realiser given an explicit plan omits far less, and VN tooling already runs an LLM pass over whole scripts to fix names before translating. What nobody appears to have built is the store in the middle: a per-line record that outlives any single target text. Treating that record, rather than the translation, as the durable artifact changes the economics. The expensive model runs once per line, every later preference is a cheap render or a code path, and the same record serves a reader who wants pirate speech, one who wants every "-senpai" kept, and a learner who wants only the unknown words glossed.
The design choice that matters most is where to stop trusting the model. The evidence says to trust it for open-ended voice and nothing else: names, address terms, register and honorific spans should be fields and slot fills checked in code, and the Japanese should stay in the prompt as the ground truth the record cannot fully replace. If experiment 2 shows the renderer actually conditions on the record rather than re-translating, the rest is familiar engineering: versioned records, content-addressed caches and read-ahead.
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