Where does the difference come from between people who use AI well and those who do not? Many answer, “Do they know good prompts?” In reality, the issue is different. The core is not a few prompt sentences, but whether I can say what I want with context and criteria included.

The Ildangbaek video “Human intelligence expressed delicately through language: the beginning of AI prompt engineering” shows this point well. The starting point is the book *AI Language Lessons for Intellectual Conversation*, but the conversation is less a book introduction than a question about language sense in the AI era. For Korean users, the question is even more important: when talking with AI in a language rich in omission and nuance, what must we make clearer?

## The AI-use gap comes from “language resolution,” not tool operation

Many people first say to AI: “Organize this for me.” “Do not make it too long.” “Do not sound stiff.” “Do not draw an image; just show the prompt.”

Between people, this often works because we read surrounding context, facial expressions, previous conversations, organizational culture, and tone. AI, however, guesses context the user did not provide. When the guess is right, it is convenient; when it is wrong, the result goes off track.

Prompt guides from OpenAI and Anthropic commonly emphasize clear instructions, enough context, and the desired output format. A good prompt is not a magic sentence. It is a sentence that reduces what AI must guess.

The key difference appears here. People who use AI well do not simply write longer questions. They structure context: purpose, reader, constraints, examples, preferences rather than bans, output format, and verification criteria.

## Why Korean is harder for AI

One of the video’s most interesting points is the high-context nature of Korean. Korean often omits subjects and objects. A single particle changes focus. Honorifics may be processed on the surface, but sarcasm and irony are different issues.

For example, sentences equivalent to “Cheolsu went to school” with different Korean particles may look similar but have different focus. “It is okay” may mean acceptance or refusal. Mixed emotions such as relief and regret vary by context.

Humans read these differences from the situation. AI mostly receives text. Korean users therefore need to provide more context. “Do it appropriately” is convenient for humans but information-poor for AI.

This also appears in translation. Anthropic’s interpretability research suggests large language models can connect multilingual inputs to shared internal concept spaces. But that does not mean Korean nuance is perfectly preserved. Emotion, omission, irony, and speaker intention can be lost when moving between languages.

## Prompt engineering is not “asking well”; it is operating a system

The video distinguishes prompts from prompt engineering. Everyday users can ask AI conversationally. But business systems, customer service, automation, and content pipelines are different.

Prompt engineering is not simply “the skill of asking beautifully.” It examines how models differ in response tendencies, analyzes why wrong answers appear, designs structures that reduce cost, connects multi-step work reliably, and controls consistency.

Writing may require creativity, but customer notices or legal and policy guidance should not vary every time. In such cases, generation settings like temperature, example-based output, verification steps, and retry conditions are needed.

Prompt engineering is therefore both a language skill and an operations skill. It starts from an individual’s questioning habits, but in organizations it expands into quality and cost management.

## “Do this” is stronger than “Do not do that”

One practical tip repeated in the video is to use positive statements rather than negatives. “Use everyday words” is better than “Do not use technical terms.” “Write within three sentences per paragraph” is better than “Do not make it long.” “Write as a short explanatory passage” is clearer than “Do not use a list.”

AI does not always handle negative instructions reliably. In image, video, or multimodal models, negative words can blur the desired result. Even in text models, “do not” can place the banned element at the center of context.

| Common request | Better request |
|—|—|
| Do not write too difficultly | Use everyday words a middle-school student can understand |
| Do not make it long | Explain only three key points within 600 characters |
| Do not sound like AI | Mix short and long sentences and reduce repeated expressions |
| Organize it for me | Organize it in the order of background, key issue, and action items |
| Do not include subjective opinions | Separate confirmed facts from interpretation |

This difference looks small, but the result changes greatly. Reducing the space for AI to guess reduces revision time.

## The productivity debate is about what you delegate, not how much you use AI

Opinions differ on whether AI truly improves productivity. Some research already observes concrete effects. NBER’s “Generative AI at Work” found that generative AI tools increased average productivity in customer support and especially helped less-experienced workers.

The ILO’s analysis of generative AI and jobs, by contrast, suggests many jobs are more likely to have some tasks automated or assisted than to be fully replaced. This matches the video’s conclusion: AI does not simply eliminate all work; it redistributes components of work.

The question is not “How much do you use AI?” It is whether you can decide what to delegate and what humans should judge. Simple summarization, drafting, format conversion, and repetitive replies are easy to delegate. Reading customer anxiety, judging field context, and cautiously confirming unspoken needs still remain heavily human.

## Five prompt principles for Korean users

### 1. Restore omitted subjects and objects

Before writing “organize it,” state what should be organized, for whom, and for what purpose. Omission is natural in Korean conversation, but it becomes a blank for AI.

### 2. Turn negative statements into positive ones

Say “Use a friendly but not exaggerated tone” rather than “Do not sound stiff.” Goals are more stable than bans.

### 3. Decide the output format first

A table, list, paragraph, report, blog post, email, and presentation script are different outputs. Without a format, AI gives an average answer.

### 4. Separate context and criteria

Give background as background, requirements as requirements, and verification criteria as verification criteria. If everything is mixed into one sentence, AI may miss priorities.

### 5. Do not try to finish in one turn

Good AI use is closer to multi-turn collaboration than a single command. Receive a draft, strengthen criteria, revise again, and verify at the end.

## A prompt is ultimately a conversation habit, not just a technique

UNESCO’s AI competency framework treats AI-era capability not as mere tool operation but as human-centered thinking, ethics, critical judgment, and practical use. Prompts are similar. They are not shortcuts to memorize.

Talking with AI is a process of making your own thinking clearer. If you do not know what you want, AI does not know either. If you do not give criteria, AI produces an average. If you omit context, AI guesses.

That is why the video’s core is deeper than “write better prompts.” Competitiveness in the AI era belongs not to people who know many technical tricks, but to people who can examine their own language and design context.

In that sense, future AI literacy may be a language issue before it is a coding issue, especially for Korean users. The words we naturally omitted, the atmosphere we relied on, and the “do it appropriately” we handed over must all become sentences again in front of AI.

## Further reading

– [Metacognition in the AI Era](https://www.thinknote.co.kr/metacognition-ai-thinking-checklist/)
– [In the AI Agent Era, How Knowledge Workers Must Change](https://www.thinknote.co.kr/ai-agent-valuable-education/)
– [Six Habits of People Who Get Smarter the More They Use AI](https://www.thinknote.co.kr/ai-smarter-use-six-habits/)

## References

– [Ildangbaek video](https://youtu.be/OcmSp1Cn5rg?si=LQk_SQmJmDuqaETH)
– [OpenAI, Prompt engineering](https://platform.openai.com/docs/guides/prompt-engineering)
– [Anthropic, Prompt engineering overview](https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview)
– [Anthropic, Tracing the thoughts of a large language model](https://www.anthropic.com/research/tracing-thoughts-language-model)
– [Brynjolfsson, Li, and Raymond, Generative AI at Work](https://www.nber.org/papers/w31161)
– [International Labour Organization, Generative AI and Jobs](https://www.ilo.org/publications/generative-ai-and-jobs-global-analysis-potential-effects-job-quantity-and-quality)
– [UNESCO, AI competency framework for teachers](https://www.unesco.org/en/articles/ai-competency-framework-teachers)

## FAQ

### Are Korean prompts disadvantaged compared with English prompts?

Not always. But Korean relies heavily on omission, particles, honorifics, and context, so AI often has to guess intention. When writing in Korean, it is better to state situation and criteria more clearly.

### Do I have to learn prompt engineering?

Everyday users do not need grand engineering. But if you use AI for work, you need the basic habit of giving purpose, context, output format, and verification criteria.

### Why does “do not do this” often fail with AI?

Negative statements place the prohibited object inside the context. Some models do not reliably reflect the ban. It is usually better to specify the desired behavior in positive terms.

### Can AI writing be made to feel human?

To some degree. Adjusting sentence length, repeated expressions, omissions, rhythm, and concrete situations can reduce a mechanical feel. But AI does not possess real experience or judgment.

### What should humans do in the AI era?

Humans must interpret context, set criteria, and make final judgments. Customer emotion, field situations, organizational tacit knowledge, and ethical judgment remain difficult to standardize fully.

[Original Korean article](https://www.thinknote.co.kr/ai-korean-prompt-literacy/)