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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 30NICKSARAEV)
🧑🏽💻 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
Why watch?
If this is your first view—hi, I’m Nick! TLDR: I spent six years building automated businesses with Make.com (most notably 1SecondCopy, a content company that hit 7 figures). Today a lot of people talk about automation, but I’ve noticed that very few have practical, real world success making money with it. So this channel is me chiming in and showing you what *real* systems that make *real* revenue look like.
Hopefully I can help you improve your business, and in doing so, the rest of your life 🙏
Like, subscribe, and leave me a comment if you have a specific request! Thanks.
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