Empathy is what separates great engineers from code monkeys. Being non-empathetic is actually costing you opportunities and career growth. Let me elaborate... Remember, your job is to solve a problem, not just write code. You are not a code monkey who just hammers the keyboard.

I’ve used Opus 4.6 and GPT 5.4 on a mix of projects since release, and want to break down where I think they uniquely excel. It’s more nuanced than you’d think! Rigor of code - GPT 5.4. It goes the distance validating its work without asking. Opus needs explicit instruction to

This is the setup that changed everything for me, Claude can now browse the internet on its own. Not with your browser. Its own dedicated browser.. It can now login with your credentials, scrape data, monitors communities and generates leads.. all in the background while you

Claude Code leaked their source map, effectively giving you a look into the codebase. I immediately went for the one thing that mattered: spinner verbs There are 187

Anthropic accidentally leaked their entire source code yesterday. What happened next is one of the most insane stories in tech history. > Anthropic pushed a software update for Claude Code at 4AM. > A debugging file was accidentally bundled inside it. > That file contained

How To Win In Software Engineering!!!!! 1. Read code more than you speak. 2. Ship small, consistent improvements. 3. Learn to debug properly, not just patch things. 4. Understand the business, not just the ticket. 5. Write clear docs for what you build. 6. Ask why before jumping

guys, i honestly do not like clowning on Gary. I don't find being the butt of a joke funny, so I imagine he does not either. But, this is what worries me about where we are going. We are actively encouraging an entire generation that the tech is there when its not, and a

25 backend patterns engineers should know: 1. Repository pattern: abstract data access. 2. Service layer: business logic separation. 3. Factory pattern: controlled object creation. 4. Singleton: single instance management. 5. Dependency injection: loose coupling. 6.

I have seen more systems struggling because of wrong code than slower ones. The fact remains, most engineers optimise too early. About 8 years ago, my principal engineer once told me: Performance is almost always the last thing you should be thinking about. As an SDE-2, this did

Holy shit… someone just made machine learning click. Not static diagrams. Not math-heavy PDFs. Not black-box training. Real algorithms — training step-by-step — visually. It’s called Machine Learning Visualized and it lets you watch models learn in real time. Here’s why this

Honestly, this is the most accurate diagram I've seen. Waterfall: You plan for 18 months and deliver exactly what nobody needs anymore. Agile: You deliver something usable at every step, but the CEO keeps asking, "Where's the car?" AI: You get the car on day one. It has six

12 Mistakes you should NEVER make when it comes to interviews (as a Software Engineer). 0. Thinking "DSA is enough"

x.com/i/article/2040…

AI layoffs are a textbook collective action problem: Each company cuts workers to compete, but if everyone does it, demand collapses. You optimized costs and killed your own customers… and your company.

Some people finish most important DSA topics in 3 - 4 months. And then there are people who are still stuck even after 2-3 years. It's the same DSA for them and same online resources. So what’s really going on here? I’ve been thinking about this a lot, especially after seeing

swe in 2026