← 대시보드로
2026-05-24
2개 영상
2026-06-19 05:50 생성
해외에서 꿀통으로 난리남
AIMAX_PD 2026-05-24
해외에서 꿀통으로 난리남
↗ 유튜브에서 보기

핵심 요약

Etsy에서만 7억+ 매출을 올린 헤더의, 클로드로 블루오션 디지털 상품을 만드는 3전략.

주요 포인트

  • 가계부를 마이크로니치로 쪼개기(결혼준비용·식비관리용 등, Etsy 트래픽 활용)
  • 1달러 PNG 번들 20개+로 대량 판매(연 13억 사례)
  • AI 디자인+프린트온디맨드 결합(재고 없이 자는 동안 수익)
이 여자는 디지털 상품의 신입니다. 시에서만 7억 원 이상의 매출을 올리고 디지털 상품 하나로 수십억 원을 벌어들인 비즈니스 천재 헤더. 그녀가 공개한 클로드 AI로 블루오션 상품을 만들어 돈을 복수하는 세 가지 전략. 저장하고 끝까지 보세요. 첫째, 가게부 스프레드시트를 마이크로 니치로 쪼개세요. 단순한 가게부가 아니라 결혼 준비 전용이나 식비 관리 전용처럼 아주 구체적인 목적을 가진 가게부를 만드세요. 클로드로 수식을 짜고 시에 강력한 트래픽을 활용하면 광고이 한 푼 없이도 매달 수백권의 판매가 저절로 일어납니다. 둘째, 1달러짜리 PNG 번들로 방담의 시장을 점령하세요. 제품 하나를 비싸게 팔기보다 20개가 넘는 디자인을 묶어 단돈 1달러에 판매하는 전략입니다. 실제로이 방식으로 연간 13억 원에 매출을 올린 사례가 있는만큼 고객이 거절하기 힘들 정도의 압도적인 가치를 제공하는 것이 핵심입니다. 셋째, AI 디자인과 프린트 온 디맨드 시스템을 결합하세요. 클로드로 뽑아낸 고퀄리티 디자인을 제고부담 없이 주문이 들어올 때마다 제작해서 배송하는 구조를 만드세요. 당신은 디자인만 등록해 두면 제작부터 배송까지 시스템이 알아서 처리하며 잠자는 동안에도 수익이 쌓이는 무자본 창업이 완성됩니다. 38분짜리 영상 내용을 다 정리하기엔 너무 짧습니다. 본문에 정리했으니 확인해 보세요.이 채널을 구독하세요. 더 많은 AI 수익화 사례를 공유합니다.
Claude and ChatGPT Got More Literal. Your Old Prompts Are Backfiring
Dylan Davis 2026-05-24
Claude and ChatGPT Got More Literal. Your Old Prompts Are Backfiring
↗ 유튜브에서 보기

핵심 요약

GPT-5.5·Opus-4.7 같은 최신 모델은 단어를 더 문자 그대로 받아들이기 때문에 작년에 통하던 프롬프트 습관이 오히려 결과를 해친다. 역할 부여 제거·참조 파일 명시·작업 후 보고 요구라는 세 가지를 고쳐야 한다.

주요 포인트

  • 역할(role) 빼기: "당신은 전문가" 같은 역할을 붙이면 모델이 페르소나 연기에 집착해 작업 자체에 집중하지 못한다. 한 연구에서 역할 없이 작업만 준 프롬프트가 정확도가 더 높았다. 대신 원하는 것과 "좋은 결과"의 기준을 구체적으로 적는다(예: 가격 옵션 3개, 각각 트레이드오프 제시, 숫자엔 출처 명시).
  • 파일 명시: 예전엔 프로젝트 내 컨텍스트 파일을 AI가 알아서 참조하기도 했지만, 이제는 문자 그대로 받아들여 명시하지 않으면 보지 않는다. "브랜드 보이스 파일은 톤, 과거 제안서는 구조, 가격 파일은 숫자 참조"처럼 어떤 파일을 언제 볼지 명시한다.
  • 보고(audit) 요구: 모델이 50~100단계의 긴 작업을 하게 되면서 50개 항목 중 8개를 빠뜨리고도 "완료"라고 할 수 있다. 처리한 항목 수를 정확히 보고하고, 건너뛴 항목은 이름과 이유를 대고, 모두 처리했을 때만 "완료"라고 말하게 시킨다.
  • 이 변화들은 다운그레이드처럼 느껴지지만 실제로는 더 신뢰성 높은 방식이다. 모델이 지시를 잘 따르므로 명확히 요청하면 실행 확률이 훨씬 높아진다.
  • 단, 이 프롬프트 수정만으로는 한계가 있고 브라우저를 넘어선 작업은 Codex·Claude Co-work 같은 desktop agent로 옮겨야 한다.
The prompts that worked last year are quietly backfiring on newer models like GPT-5.5 and Opus-4.7. Most people haven't caught it yet. If you're new here, I'm Dylan. I run an AI consultancy, and prompting comes up in almost every single client coaching call that I have. I've been running both models against client workflows since they came out. The habits everyone picked up over the last year are now hurting your output, not helping it. I see the same three habits over and over. Let me show you what they are and how to fix them. Let's get into it. There are many things that have changed between the previous models and the newest models today like GPT-5.5 and Opus-4.7. But, the primary thing that's changed that's impacting a lot of people's prompts is the fact that these models take you more literally, which means the words that we provide to these models are more important than ever. And the fact that these models take our words more seriously is what's impacting these three things I'm going to walk you through. So, here are the three prompt changes we need to make to ensure we're getting the most from these models. I'll walk you through each one of these more detail in a second, but as a quick overview, the first thing, which is really hard for me to change, is the fact that you need to stop telling the AI it's an expert in whatever field that it's working on for you. After that, we need to be explicit to the AI if there are specific files it needs to reference to achieve a task. We need to tell it what files to look at instead of assuming it's going to look at those files without us stating anything. And finally, with these new models, they can take many steps to achieve really complex tasks now, more steps than they could ever in the past. So, it's important that we ask the AI to tell us how many steps it's taken to ensure it's not skipped anything. So, those are the three fixes. We'll start with the first one, which is honestly probably one of the hardest for me to change because I've been doing it for so long. And that's simply dropping the role at the beginning of your prompt. And why does this matter? Well, there was a study done recently on GPT-5.5 and Opus-4.7. And what they did is they took the same AI with slightly different prompts on the same task. And all they changed in the prompts were adding a specific role at the beginning with the same task. In the second prompt, they just removed the role and had the task alone. The AI itself achieved the task at a much higher accuracy without the role. Now, the theory here is that when you add a role to an AI saying you're an expert writer, an expert strategist, or a salesperson, whatever else, it gets hyper-fixated on that role and spends a lot of time thinking about how it's going to convey that persona to the user instead of focusing on the the task at hand. And that's one way that this whole AI focusing on things literally is impacting the quality of the output you're getting from the AI. Quick pause in your regular programming. This video is brought to you by me, as always. Two quick things. First off, below is a 30-day AI Insight series, completely free. You'll get 30 insights in your inbox of how you can apply AI to your business and your work. The second thing is if you'd like to work with me, below are a series of offerings to see if there's a good fit between the two of us. Now, let's get back to the video. And the fix for this is simple. So, this here is a prompt that you would probably give to an older model. But with models like GPT-5.5 and Opus-4.7, you want to change this. Reason being is in this prompt, you're spending half of the time asking the AI to think about being a world-class expert in the specific field. And you've only given half of the space for the task, which is help me figure out my pricing strategy. A better prompt here would be something like this, where we remove the role completely and we focus more time on what we want and what good looks like. And that matters most for these models now. So, we need to be specific on the goal and the AI will figure out how to get there. So, here instead of saying it's a expert in given field, what we're doing instead is we're saying give me three pricing options. Each one should lead with a trade-off and cite the source for any numbers that you used. So, this is very specific on what good looks like and what we want from the AI, not worrying about the role at all. So, this is the first thing that we need to change is removing the role. The next thing we need to change in our prompts for these new models is naming the files when relevant. What do I mean by when relevant? Well, if you're doing something inside of a project, so many of you are using GPT projects, cloud projects, Gemini gems, or Copilot agents, they're all the same thing. You have a given AI that's targeted on a specific task that you want it to do over and over and over again. Well, in the past with these older models, yo