Agentic AI Translate: An Agentic Translator Prototype for Translation as Communication Design
For translation studies and machine translation practitioners, this work proposes a new paradigm shift from text conversion to communication design, but it is currently an untested prototype.
The paper introduces Agentic AI Translate, a prototype that replaces the text-in/text-out machine translation paradigm with a four-stage agentic cycle (Identify, Prompt, Generate, Verify) preceded by an interactive specification phase for structured translation briefs. The contribution is conceptual and architectural, with empirical validation left for future work.
We present Agentic AI Translate, an agentic translator prototype that operationalises the thesis of Yamada (forthcoming) -- that the metalanguage of Translation Studies has become an instruction code for generative AI. The system replaces the dominant text-in / text-out paradigm of machine translation with a four-stage agentic cycle (Identify -> Prompt -> Generate -> Verify), preceded by an interactive specification phase in which the user composes -- through model-assisted dialogue -- a structured translation brief grounded in skopos theory, register, audience, and genre conventions. The verification stage adopts the GEMBA-MQM error-span protocol (Kocmi & Federmann, 2023) for evidence-grounded scoring, and document-level coherence is preserved through a DelTA-lite memory of proper nouns and a running bilingual summary, after Wang et al. (2025). We describe the philosophical motivation, the architectural commitments, the four reference-material categories the system consumes, and the principal design tensions the architecture makes explicit. Empirical validation is left for future work; the contribution here is conceptual and architectural -- an executable embodiment of the position that translation in the GenAI era is communication design, not text conversion.