{"id":205,"date":"2026-06-11T11:30:00","date_gmt":"2026-06-11T03:30:00","guid":{"rendered":"https:\/\/imtiajwrites.com\/blog\/?p=205"},"modified":"2026-06-11T14:48:54","modified_gmt":"2026-06-11T06:48:54","slug":"prompting-in-your-first-language","status":"publish","type":"post","link":"https:\/\/imtiajwrites.com\/blog\/prompting-in-your-first-language\/","title":{"rendered":"Prompting in Your First Language: A Technique Most Non-Native Writers Miss"},"content":{"rendered":"\n
\n\n\n\n

Prompting in your first language is the technique most non-native writers reach for last, even though research suggests it should be one of the first. The default move is to type your prompt in English, even when English is your second or third language. It feels professional. It feels like the obvious choice. It also leaves sharper output on the table, especially for the kinds of cultural and creative work non-native writers are uniquely positioned to do.<\/p>\n\n\n\n

This post is about a small switch with bigger results than its size suggests. You don’t change the model. You don’t change the writing you produce in English. You just change one stage of the prompting process, deliberately, and the output that comes back gets better.<\/p>\n\n\n\n

Two reasons it works. One reason it sometimes doesn’t. And a four-step method to use it cleanly without burning extra time.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

What the research actually says<\/strong><\/h2>\n\n\n\n

Two findings worth knowing before we go further.<\/p>\n\n\n\n

The first comes from a 2024 paper by Reusens et al., “Native Design Bias”<\/a>, which collected over 12,500 unique prompts from 124 annotators around the world. The researchers found that LLMs, including GPT-5o, Claude Sonnet, Haiku, and Qwen, generate measurably less accurate responses for non-native English speakers on objective tasks. Even when the message is the same, the model often performs worse if the phrasing is non-native. There is a real bias built into how these models read English, and you have likely felt it without naming it.<\/p>\n\n\n\n

The second comes from a 2024 study by Liu et al., “Is Translation All You Need?”<\/a>. After running tests across 24 languages, the authors concluded that for culture-related tasks needing deep language understanding, prompting in the native language proves more effective than English, because it better captures the nuances of culture and language. That finding flips the default assumption most non-native writers carry, which is that English is always the smart choice.<\/p>\n\n\n\n

Together, the two findings tell a useful story. English-prompting has a quiet quality penalty for non-native users on subjective tasks, and a real quality gain for cultural and creative tasks when you switch to your first language at the right moment. The gap is not huge. It is also not zero. For a working copywriter producing 20 prompts a day, the cumulative difference adds up.<\/p>\n\n\n\n

The pattern most non-native writers fall into<\/strong><\/h2>\n\n\n\n

The pattern I see most often when reviewing prompt logs from non-native writers is this. They open ChatGPT, they switch their brain to “professional English mode,” and they stay there for the entire session. Every prompt in English. Every output in English. Every refinement in English.<\/p>\n\n\n\n

That is fine for grammar checks and rewrites. It is leaving real value on the table for ideation, cultural angle work, emotional positioning, and any task where the thinking<\/em> matters more than the wording<\/em>. Those are the tasks where your first language is doing more work in your head than you realise, and shutting it out of the prompt cuts you off from your own best thinking.<\/p>\n\n\n\n

The fix is not to switch fully to your first language. The fix is to use it at the stage of the prompting process where it actually helps, then switch back to English where English is the better tool.<\/p>\n\n\n\n

\n