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Explore $2.4M of Prompt Engineering Hacks in 53 Mins (GPT, Claude) with 349,365 views, 12,060 likes, and 262 comments. Experience the impact of this video content that has captured audience attention.

Join Maker School & get automation customer #1 + all my templates ⤵️ https://www.skool.com/makerschool/about?ref=e525fc95e7c346999dcec8e0e870e55d ➡️ If this is your first video: I'm Nick Saraev. I run LeftClick, an AI growth agency. We've done work for large brands you're likely familiar with, like Mr. Beast, Anthropic, OpenAI, and a few others. In plain English: I help people build systems that generate leads, close deals, and scale businesses, mostly using new AI models like Claude. I also make videos about how to do all of that here on YouTube. It hasn't always been this way. My family immigrated from a Soviet bloc country (People's Republic of Bulgaria) in the 90s. They worked extremely hard, and we were broke for a very long time. I grew up wishing for more security, stability, and freedom over my own life. I don't have a programming degree, and never took formal education for IT or workflows. I learned it all myself from YouTube videos like you're watching now. As for my path: I started my first business at 19 in college. We threw events (mostly parties) at campus bars, and charged people for entry. That failed to provide me enough money to pay my bills, so at 21, I started another business, a door-to-door marketing agency. From there, every year, I would start several companies, over 10 in total. I did this in a variety of industries, like e-commerce, photography, videography, SaaS, credit repair, etc. Each grew slightly more profitable, until, at 25, I would start 1SecondCopy, a content writing company. A friend and I eventually scaled that to over $90,000/m. It was my first taste of financial independence, and the reason I'm here today. Since starting my journey, I've grown a fair bit of capital. To diversify my income, at 30, I began investing in other businesses and advising companies on how to grow in the AI era. These include SaaS businesses, like Clairvo, agencies like Dental Connect, and more. Collectively, the businesses that I own outright or are a part of generate over $10 million per year. This returns far more than the 5-10% you would get in the stock market, but also requires a lot of my active time. There's a tradeoff there, but I greatly prefer active investing, where I have control over the entities I'm a part of. It wasn't easy to get here. But I did in the end! For anyone on their own entrepreneurial journey: I wish you luck, happiness, and perseverance. You can make it! Summary ⤵️ In this video I'll run you through over six years (and several million dollars worth) of prompt engineering. I started with GPT-2 back in 2019, and have been using AI to make money ever since—so along the way I've naturally picked up quite a few AI & prompt engineering tips! My software, tools, & deals (some give me kickbacks—thank you!) 🚀 Instantly: https://link.nicksaraev.com/instantly-short 📧 Anymailfinder: https://link.nicksaraev.com/amf-short 🤖 Apify: https://console.apify.com/sign-up (30% off with code NICK30) 🧑🏽💻 n8n: https://n8n.partnerlinks.io/h372ujv8cw80 📈 Rize: https://link.nicksaraev.com/rize-short (25% off with promo code NICK) Other places you can find me 😈 📸 Instagram: https://www.instagram.com/nick_saraev 🕊️ Twitter/X: https://twitter.com/nicksaraev 🤙 Blog: https://nicksaraev.com Chapters 00:00:00 Introduction to Prompt Engineering 00:00:16 Transitioning from Consumer to Playground Models 00:01:52 Optimizing Prompt Length for Better Performance 00:04:59 Simplifying Your Prompts 00:11:32 Understanding Prompt Types 00:15:41 Utilizing One and Few Shot Prompting 00:19:20 Conversational Engines vs Knowledge Engines 00:22:53 The Importance of Unambiguous Language 00:26:24 The Spartan Tone of Voice 00:27:12 Iterating Prompts with Data 00:32:34 Defining Output Formats Clearly 00:35:21 Avoiding Conflicting Instructions 00:36:42 Learning Data Formats: XML, JSON, CSV 00:42:23 Key Prompt Structure for Success 00:46:41 Generating Examples for AI 00:48:37 Choosing the Right Model for the Task 00:51:57 Conclusion and Call to Action

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