Introduction to Gemini
1. Introduction to Gemini
2. Introduction to Gemini
Hi, welcome to practical AI with Gemini and NotebookLM. In this course, our mission is to give you tools and techniques to save you time, automate the boring repetitive stuff, and improve the quality of your output with AI. My name is Cezary Jaroni, and I work as a product marketing manager for consumer AI products at Google. In this course, you will also meet my colleague from Google, Michal Domagala. Just a quick disclaimer before we dive in: while we both work at Google, the tips, techniques, and opinions that we'll be sharing are our own. Okay, let's start. In this course, we'll show you how you can save five to 10 hours next week with valuable outcomes. What else will you learn in this chapter? You'll learn how to prompt effectively for your personal productivity. In the next chapter, you'll learn how to use AI for research, task planning, image generation, and video generation. We'll cover Gemini Deep Research, Gemini Live, Nano Banana, and Veo. And you'll also learn how to use and create your AI assistants with Gems. In the third chapter, you learn how to leverage Gemini in the Google ecosystem, meaning Slides, Gmail, Docs, and Google Sheets. And wait for it, you also learn how to set up your AI agents to help you manage your inbox perfectly. And finally, in the last chapter, you will get familiar with the amazing tool for research and managing your knowledge, which is NotebookLM. But before we dive in, let's start with the basics. What is Gemini? It is an AI assistant from Google. And while it might be obvious for most of you, we just want to make sure that we level the knowledge for everyone. We think of Gemini as a partner that can do three things. First, it can read and synthesize massive amounts of information. Second, it can write almost anything, from code to a marketing strategy. And critically, Gemini can reason. It helps you solve complex problems, but it can hallucinate. It can prioritize pleasing you rather than providing factual answers. So you need to control it. Some people think of AI tools as more advanced search browsers. We like to think of Gemini as your creative and productive partner that can help you analyze, strategize, give feedback, and co-create. So how do you partner with it and how do you control it? It's about smart delegation. In my own workflow with AI, I split my tasks into two categories. First are repetitive tasks. Think of a 50-page consumer feedback report that's just a messy, unstructured PDF, and you need to quickly find key complaints. Or think about taking meeting notes and sending follow-ups. Those are repetitive tasks, and we'll learn how to automate them with Gems in Chapter 2. The second category is high-value tasks. This is where you're creating a new strategy document or where you're preparing for that critical client presentation. Here, we should use AI to help us bring more value and deliver better insights. How do we do that? By asking AI to give us feedback on how we can improve our presentation, asking to spot logical errors in our documents, or asking how the client could challenge our material. AI shouldn't do our job here, but it should augment it. But this augmentation comes with a risk. Risk of generating a piece of work that looks professional but lacks substance and value. A study from BetterUp Labs and Stanford Social Media Lab shows that 40% of analyzed corporate workers in the US received such an output. Meaning, the output generated by AI looked professional but lacked substance, and it has a name, it is called "AI workslop," and this can lead to actually working more, not less, due to AI. And beyond that, it can lead to an erosion of trust in the workplace. Why is this happening? A study from KPMG and the University of Melbourne shows that 66% of analyzed corporate workers in the US do not verify AI output. What can we do with it? Whenever we receive an output from AI, we should always question it. A quick test to ask is to ask ourselves, "If someone sent this output to me via email, would I think of it as a valuable work or would I think of it as a generic AI output?" And it's a good test to ask ourselves before sending any output generated by AI because our credibility depends on that critical review. And based on the answer to that question, you can tweak the output and maybe supplement it with your domain expertise until the output is satisfactory. And this is what we are going to learn and cover in this course: The right tools and best practices for automating and generating real value with Gemini and NotebookLM. In the next video, we'll dive into the art of prompting and context defining.3. Let's practice!
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