After last week’s newsletter, one of you reached out to push back on my idea about selling raw MT. He took issue with my suggestion that a translator should aim for 30,000 words an hour for raw machine translation.
The question was simple: why not just set up the anchor prompt once and automate the rest with programming? Wouldn’t that mean you could translate gobs of content overnight, segment by segment, with no effort at all?
It almost seems too easy… and it is.
The key point he missed here are the unique advantages you bring to the process by staying engaged.
The biggest one is context leverage. Even if your anchor prompt isn’t perfect, you can already achieve noticeably better translation quality and internal consistency just by handling multiple segments at a time. Keeping translations within the same context window helps you produce a more coherent final product. This is a huge quality boost, and it simply can’t be automated. Especially if you’re using your CAT tool (which you should be for many reasons) you’ll need to babysit the AI or risk real chaos.
There’s another challenge as well: as you make the most of context, the context window grows, and eventually the AI will start losing reliability. When that happens, you’ll need to transition to a new context window, and this is the perfect time to update your anchor prompt to reflect what you’ve learned in the first cycle. Layering this in means each new content block has the highest shot at both consistency and quality.
Throughout the process, there are other touchpoints where your engagement adds value. Sometimes you’ll notice the anchor prompt no longer matches the kind of content that’s coming through, or you’ll spot something odd in the output that needs intervention. Even if you aren’t checking every word, your presence and strategic tweaks keep the process aligned and humming.
And here’s a practical concern: if you’re just running the workflow fully automated, segment by segment, you lose out on consistency, context, and, ironically, you’ll likely spend more on tokens if your prompt is robust. By following manual GAIT workflow principles, you can actually use the top models while still keeping your costs down.
Finally, remember that automating the whole thing with your own programming is not a unique value proposition… this is precisely what the Localization Illuminati are doing, and they’ll always have more resources than you to keep this cycle going. You can’t win by playing their game.
Maybe you think the difference in cost or quality is small, maybe not. But your only real value as a human translator is the value you add… the things that automation can’t deliver. That’s the only way forward if you want to keep doing what you love on your terms.
Keep your eye on human value, or it might be time to find something else to do. To me, those are the only real options on the table.