Most people are stuck on the wrong side of using AI without realizing it because AI model change new features every week. So people try everything and eventually get overwhelmed. I have been there before using ai, but never felt like I was truly getting the most out of it. So in this video, I'll share the path to get started with AI and which transform completely how I use it. Let's. The first part is learning how to communicate with AI and communication all starts with effective AI prompting. After spending two years prompting AI every day, the most critical components for an effective prompts are really these three. Clear tasks. The whats what exactly do you want? Is it a proposal, a landing page, a social visual? If you're confused, AI will get confused too. Relevant context, the why. What are the background details AI needs to understand your situation. Instead of brain dump everything to ai, think about why this context matters. Output format, the how, how a good output should look like for your task. A table? A word document file? Bullet points? So like this example about a performance review conversation, ChatGPT is still able to give us a decent response, but if we intentionally mention the clear tasks, the relevant context, the output format, you will see the response improved dramatically. Bonus tip is you can always let AI to ask you question to uncover what are the context that you should give in order for it to do its job. You can also add enhancement prompt elements like persona, examples, constraints for more precision control. But the core three elements I mentioned are all you need for 80% of task. Besides these core components, here are four more techniques, which are my favorite, and they apply to all sorts of tasks. Technique number one, few-shot prompting, giving examples. So when I ask Gemini to build a landing page with just a copy, it creates something decent, but looks standard. But what if I give two style screenshot examples this time to output transform dramatically capturing the exact premium aesthetic that I want and stand out. Technique Number two, perspective shifting, asking AI to shift its perspective and give you multiple angles on the same task, like this marketing landing page copy. We can ask AI to critique the same copy from the perspective of a business owner or from an enterprise executive. And then immediately you can identify weak points and compelling angles to emphasize Technique number 3, self evaluation loop. Like this task about a content strategy task. After AI give you a response, ask it to think deeply and create an internal quality rubric and critique the output against the standard. Immediately AI will return back a total of 10 pages, really detailed strategy document instead of a standard draft. Technique number four, reverse prompting. So give AI your desired output, and let it write the prompt for you. Like I can show Gemini a social visual that I love and ask it to reverse engineer the visual formula, and then I can reuse that prompt to generate new visuals in the same style. So instead of guessing what to ask for, show the results that you want. Another bonus tip. Use the official prompt optimizer. So different AI models have their own prompting rules. So you can go to the official prompt generator. Just describe what you want in plain language or your initial prompt so it would generate and optimize the prompt that works best with that model. I'll put all the links below. Now that you can communicate with AI. But here's where most people waste the time. They treat every AI the same. The truth is, yes, you don't need 20 AI tools, but you do need to choose AI models strategically. ChatGPT, Claude, Gemini, anyone of these models already handle 70% of what you need. So master one core model first and that expand when you actually need more specialized capabilities From my experience for ChatGPT is like your all-in-one AI assistant with generous usage limit that let you iterate without hitting capacity. It handles a right range of daily tasks from deep research, copywriting, creative idea generation, image generation, and even have a built-in agent mode for autonomous multi-step work, I find it best for high volume iteration and general purpose tasks where you don't need to worry about hitting the limits. As for gemini, I found it excels when things get big and when you need more visual impact. Its huge token context, window handles, super long reports, hour long recordings. It also has deep integration with Google Workspace and products. Just one click import and export. Its multi-model capability is also superior than other models, analyzing both visuals and audio at the same time. gemini image and video generation models also produce some of the most realistic outputs on the market at speed So I find it best to do large document analysis, building Google Workspace workflows, and create data visualization when you need both visual beauty and analytical