여기이 여자는 비즈니스 천재입니다. 대학생 시절 코딩 한 줄 모르는 상태로 앱을 만들어 매달 5억 원이 넘는 매출을 찍어낸 니콜. 그녀가 공개한 광고비 없이 1억명 고객 모으는 세 가지 필승 공식 저장하고 끝까지 보세요. 첫째, 이미 성공한 모델의 주입만 바꿔서 출시하세요. 니콜은 남성들 사이에서 유행하던 외모 관리 앱을 보고 여성들을 위한 피부와 메이크업 관리 앱으로 살짝 들어 시장의 빈틈을 공략했습니다. 거창한 발명보다 이미 검증된 아이디어를 새로운 고객에게 연결하는 것이 훨씬 빠르고 확실한 성공 전략입니다. 둘째, 고객이 스스로 광고하게 만드는 장치를 설계하세요. 앱의 분석 결과를 확인하고 싶다면 반드시 친구 세 명을 초대하게 만드는 강력한 레퍼럴 시스템을 도입했습니다.이 이 전략 하나로 수많은 사용자가 틱톡 댓글창에 자발적으로 앱을 도배하며 엄청난 무료 트래픽을 불러왔습니다. 셋째, 감이 아니라 과학적인 데이터로 영상을 찍으세요. 단순히 열심히 찍는게 아니라 영상 길이는 정확히 6초를 유지하고 시선을 끄는 특정 카메라 앵글과 자막 위치까지 매뉴얼로 만들었습니다. 이렇게 정교하게 설계된 콘텐츠 가이드는 경험 없는 초보 크리에이터들까지 수백만 조회수의 주인공으로 만들어 냈습니다.이 내용을 영상으로만 담기엔 너무 부족합니다. 한시간짜리 원본 영상을 모두 정리했습니다. 본문을 참고해 주세요. 더 많은 AI 정보가 공감하다면이 채널을 구독하세요.

Creating Claude and ChatGPT skills too early can actually make your AI worse. They don't just save your process, they save your mistakes and repeat them faster every time. If you're new here, I'm Dylan. I run an AI consultancy and this exact problem comes up in almost every coaching session that I have. So, I'll show you a four-step loop I use to build skills worth trusting and two steps most people skip. So, let's get into it. There are many different ways to build skills in Claude and ChatGPT and Codex, but this is a specific loop that I recommend all my clients follow. I'm going to walk you through each one of these steps in detail including prompts that you can copy and paste and use for yourself as you work through each stage. As a quick overview before we get into the details, we first start with a mapping. So, we need to map our process before we actually encapsulate it into a skill. After you've mapped it, which is kind of an optional step, you move on to the proof step, which is completely mandatory. And this is where we actually prove the work out with an AI and get an output that we're happy with. Once we've done that, we then capture that proof into a skill. So, it's important to note that steps two and three are absolutely critical to have a high-quality skill. After you've done those two, then we move on to the patching piece because even if you follow these steps, sometimes the skill goes off the rails. And if it does, there's a very specific way you want to go about fixing it so your skill doesn't degrade even further. And those are our four steps. Now, the issue I see with a lot of people is what happens is they skip steps two and four and they tend to bake in an idea of a process into a skill without proving out the process in detail. This tends to create over-bloated skills that never meet your expectations and we want to fix that. But before we create a skill, we need to first ask ourselves, do I even need a skill for this specific process? And there's three questions you can answer before you do that. And you want to answer these questions in succession. So, you go in this order, first, second, third. So, our first question is simply asking, will I do this again? Is this a repeated task that I'll do over and over and over? If so, it might be a skill, but But we need to move on to the next question, Which is does the quality matter each time? Is there a really high quality standard you have for this task? And does it need to be consistent every single time? If yes to this, then you move on to the final question, which is simply understanding is is this specific activity something that can be done across conversations? Now, what do we mean by that? As an example, every company usually has some sort of branding guidelines. So, we have a logo, we have colors, fonts, etc. So, anytime somebody writes a proposal or creates a presentation, they have to be in line with those guidelines. Well, you can bake those brand guidelines into a skill. So, anytime somebody tries to create a presentation, they're going to follow that skill and call it. So, it makes sure that presentation meets the guidelines for the company. So, that's a skill that works across conversations. Those are three questions. So, if we answered yes to all these, we can then move into the loop process. Quick pause and then 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 first step here is mapping. Again, this is optional, but it is a booster if you want to start with a really detailed process to begin the next phase. And my recommendation for mapping out that process is doing an AI interview. If you've watched any of my videos in the past, you've probably heard me talk about this. Where what you're going to do is you're going to have the AI ask you one question at a time. Every answer you provide is going to inform the next question the AI asks. And we want it to do one question at a time. And I usually recommend 13 to 15 questions. This is the happy medium. It's not too many to overwhelm you and not too few to not provide value. And here's a prompt that you can use for this. So, in this prompt, we're asking the AI, "I want you to create a skill for this recurring task." Then you fill in that blank yourself. Then we're saying up front, "I do not want you to create this skill yet. Instead, what I want you to do is I want you to ask me one question at a time. Cap the interview at 15 questions. Your goal for this interview is is understand this specific task and detail associated to the inputs for the task, the outputs, the quality standards, common mistakes, edge case