Learn how to use Zapier and ChatGPT to identify customer pain points from Reddit and automatically generate a report that summarizes and prioritizes key issues. 

Today we often hear about incredible AI advancements that promise to make our lives easier. But besides developing and improving new AI models, we also find new ways to use them and utilize their full potential. One exciting feature of LLMs AI Retrieval-Augmented Generation, or RAG for short. This system connects real time data to the power of AI models. And knowing how RAG works really raises the ceiling of your expertise as an AI engineer. So, in this opening article let's make sure to cover all the core fundamental concepts. And in the upcoming articles we will build exciting applications to apply our knowledge in practice. Large language models (LLMs) generate text by predicting the most probable next word, but without access to real-time or domain-specific information, they produce errors, outdated answers, and hallucinations.

Imagine a world where you could build an entire web application simply by describing it. Well, it’s not a fantasy anymore. Here, I’ll show you how Vercel’s v0 has revolutionized web development. By the end of this article, you’ll learn how to turn your written ideas into production-ready web applications! Vercel’s v0 is a generative AI tool with an ambitious goal – to help people build websites and web applications more efficiently. You can think of it as the ChatGPT for web developers, primarily focusing on building UI components and logic for web applications. It allows you to quickly turn your ideas into a live web app that people can interact with. For context, Vercel is the name of the company that created v0. It’s a cloud platform that provides hosting services as well as other useful tools for developers, including v0. The basic version of v0 is free (with some limitations), but it should be more than enough to get to know the tool. If you're interested in pricing, you can find it – here .

Welcome to our opening article about Cursor (AI IDE)! In this article, we would cover all the basic and core knowledge that you need to know about it. And which you would be using most of the time. We’ll do it in depth, without cutting any corners! And in future articles, we'll get into even more complex topics, like advanced tips or Cursor’s “Composer” feature. But first, we’ll start from building a really solid background. So, let's jump right in to it! Nowadays, tech grows and moves so fast that sometimes it's hard to keep up. To stay on top, we as the developers, always have to be ready embrace new tools, which can increase our productivity 10X while saving us a lot of time. One of such tools is Cursor, an IDE powered by AI that’s transforming how developers write, debug, and optimize their code. Cursor combines artificial intelligence with the standard features of an IDE to help you easily debug your code, provide smart code autocompletion, and offer many other features that can boost your productivity. Cursor is forked/built from VSCode, one of the most popular IDEs among developers. And it retains not only the familiar user-friendly interface, but large ecosystem of VS Code extensions as well. This foundation means that those already familiar with VSCode will find it relatively easy to transition to Cursor.