Becoming a tech lead was the goal from pretty early in my career. I had a clear picture of what the role was. More responsibility, more influence over the work, more of the interesting problems landing on my desk because someone had to figure them out and that someone, finally, would be me. It read like the natural next step. The thing you graduate to once you're good enough. What that picture did
_ Timeline - 2 Months _ PLAN DSA - C++ - Striver sheet , developer map for Leetcode. Development - Backend - JS ,MONGO - Developers roadmap for backend , Projects - Developers Roadmap. Low-Level - Rust - Developers Roadmap , Rust Book , Projects - CodeCrafter. Development - TS , SQL ,DOCKER , AWS, MY GITHUB MY LEETCODE
I have been meaning to upgrade my personal site to Astro 6 for a while. The release notes sat in my open tabs for weeks, and every time I sat down to do it, I found an excuse to work on something else. This week, I finally ran out of excuses. I carved out an afternoon, ran npx @astrojs/upgrade, crossed my fingers, and expected a smooth ride. The dev server crashed immediately with a cryptic error
The DataFrame class (from Pandas) is a work of art. Even if you never "do data", priceless lessons can be gleaned by studying this class. It starts simple enough. Usually you will create a DataFrame by ingesting from a CSV file or database table or something. But you can whip up a small one like this: import pandas as pd df = pd.DataFrame({ 'A': [-137, 22, -3, 4, 5], 'B': [10, 11,
For years, I called myself a web designer. Then a developer. Then a digital consultant. None of those titles ever felt quite right. Because clients weren't just asking me to build things. They were asking me to solve problems. Slow sites, broken checkouts, confusing navigation, teams that couldn't figure out how to update their own content. That's when I realized what a technology solutions profes
I've been working remotely for a while, and most of what I picked up in the first six months turned out to be wrong, or wildly overrated. Not bad advice exactly. Most of it sounds reasonable when you read it. It just isn't doing the work it claimed to. The "wake up at 5am, dedicate a workspace, use the Pomodoro technique, journal every morning" stack is a kind of theater. Some of it helps a little
When we talk about Data Visualization and Dashboards, enterprise tools like Tableau or PowerBI often dominate the conversation. However, for Data Scientists and Developers, these GUI-based tools can feel restrictive. What if you need complex machine learning integration, custom UI logic, or automated CI/CD deployments? Enter the holy trinity of Python visualization tools: Streamlit, Dash, and Boke
[05] When to Pull the Trigger on FIRE — Monte Carlo Says You're Already Free This is Part 5 of a 6-part series: Building Investment Systems with Python "You need 25x your annual expenses." That's the standard FIRE rule. For ¥9.6M annual expenses, that's ¥240M. Most people see that number and think: "I'll never get there." But the 25x rule assumes a fixed 4% withdrawal rate, zero income, zero ada