Here is a fascinating look into how a professional translator uses LLMs to help with his job. His specific approach (multi-layer/multi-pass with human-in-the-loop) is a good proxy for how most knowledge workers ought to use AI these days:
- In the prompt, I explain where the source text came from, how the translation will be used, and how I want it to be translated. Below is a (fictional) example, prepared through some metaprompting experiments with Claude:
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- I run the prompt and source text through several LLMs and glance at the results. If they are generally in the style I want, I start compiling my own translation based on them, choosing the sentences and paragraphs I like most from each. As I go along, I also make my own adjustments to the translation as I see fit.
- After I have finished compiling my draft based on the LLM versions, I check it paragraph by paragraph against the original Japanese (since I can read Japanese) to make sure that nothing is missing or mistranslated. I also continue polishing the English.
- When I am unable to think of a good English version for a particular sentence, I give the Japanese and English versions of the paragraph it is contained in to an LLM (usually, these days, Claude) and ask for ten suggestions for translations of the problematic sentence. Usually one or two of the suggestions work fine; if not, I ask for ten more. (Using an LLM as a sentence-level thesaurus on steroids is particularly wonderful.)
- I give the full original Japanese text and my polished version to one of the LLMs and ask it to compare them sentence by sentence and suggest corrections and improvements to the translation. (I have a separate prompt for this step.) I don’t adopt most of the LLM’s suggestions, but there are usually some that I agree would make the translation better. I update the translation accordingly. I then repeat this step with the updated translation and another LLM, starting a new chat each time. Often I cycle through ChatGPT --> Claude --> Gemini several times before I stop getting suggestions that I feel are worth adopting.
- I then put my final translation through a TTS engine—usually OpenAI’s—and listen to it read aloud. I often catch minor awkwardnesses that I would overlook if reading silently.
