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How I Built 4 Projects in 2 Days Using Bolt AI — My 6-Step Prompting Formula

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  AI is here to make dev work easier — if you ask me. Recently, I completed four full hackathon projects in just two days . These were projects that would normally take me a week or more to finish. If you’re a developer or not, you need to try Bolt . In this post, I’ll share exactly how I used Bolt — and how I structured my prompts to complete each project in under 6 hours and make them production-ready for deployment.  — - Why Prompts Matter While AI tools are becoming more accessible, they’re only as good as the instructions you give them . That’s where prompt engineering comes in. I used a practical 6-step formula that helped me focus, guide the AI properly, and get results fast.  — - ⚙️ My 6-Step Prompting Formula 1. Task Start with an action word, like you’re directing a scene. Use verbs like ” Build ”, ”Generate” , or ”Create.” > 🧠 Example: > Build a full-stack web app called ‘Inboxfolio’ that turns professional emails into a beautiful portfolio . This sets a...
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  🚀 Building Inboxfolio with Bolt: A No-Code Journey to a Portfolio From Your Inbox In the ever-evolving world of web development, new tools emerge regularly promising to make app building faster, smarter, and easier. But every now and then, one of those tools delivers so much value in so little time that it truly feels like magic. Bolt is one of those tools — and in this post, I’ll walk you through how I used it to build Inboxfolio , a portfolio site that turns emails into beautiful, professional resumes. ✨ What is Inboxfolio? Inboxfolio is a simple but powerful idea: professionals often receive opportunities, praise, or job inquiries via email. Why not turn those emails into a live portfolio? Imagine receiving a testimonial, collaboration invite, or speaking request in your inbox — and seeing it elegantly displayed on your website moments later. Instead of asking people to learn design or code, Inboxfolio lets them just send an email to a special address. The backend...
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Mastering Python Web Scraping: Libraries I Trust and Lessons Learned

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 Web scraping has been one of my go-to solutions whenever I need structured data, but there’s no API in sight. Over time, I’ve learned which Python libraries get the job done without unnecessary stress, and what practices save me from getting blocked or overwhelmed. In this post, I’ll walk you through some of the Python libraries I rely on the most, plus some practical tips from experience. 🚀 My Go-To Python Web Scraping Libraries 1. requests : Start Here, Always If I just need to send a simple GET request and grab a page's HTML, requests is my default. It’s straightforward, reliable, and lets me set headers or session cookies with minimal hassle. python Copy Edit import requests url = "https://example.com" response = requests.get(url) print (response.text) 2. BeautifulSoup : Clean and Readable Parsing Once I get the HTML, BeautifulSoup helps me extract exactly what I need. It’s intuitive, even if the website’s structure is messy. python Copy Edit from bs4...
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