In 12 years of my dev career, I’ve spent countless hours battling browser bugs.

Recently, I discovered an MCP that’s cut my debugging time in half.

MCP as a term is being overused too much, but just understand them as APIs that AI agents can use.

I found an MCP to let AI see and interact with your browser, called BrowserTools. Once you integrate it with Cursor, you can ask it see what’s going on in your browser and the console.

Using AI for coding isn’t perfect, but it definitely makes me faster.

I’ve been coding with Cursor AI since it was launched now while building my SaaS. The internet seems split between “AI coding is a miracle” and “AI coding is garbage.” Honestly, it’s somewhere in between.

Some days Cursor helps me complete tasks in record times. Other days I waste hours fighting its suggestions.

After learning from my mistakes, I wanted to share some cursor workflows and best practices that actually work in production.

I’m not sure if I’m ready for what’s coming next with AI. Things are moving too fast.

The recent releases of Claude 3.7 and GPT-4.5 were… surprising. I read articles where AI researchers admitted these systems solved problems faster than they could.

We’re racing toward a world where humans might not be the smartest ones anymore. And we’re doing it willingly, even eagerly.

A year ago, I laughed off AGI fears. Then, I watched these new models solve in seconds what took me hours. I suddenly felt… outdated.

Something’s been bugging me about how new devs learn and I need to talk about it.

We’re at this weird inflection point in software development. Every junior dev I talk to has Copilot or Claude or GPT running 24/7. They’re shipping code faster than ever. But when I dig deeper into their understanding of what they’re shipping? That’s where things get concerning.

Sure, the code works, but ask why it works that way instead of another way? Crickets. Ask about edge cases? Blank stares.

The foundational knowledge that used to come from struggling through problems is just… missing.

We’re trading deep understanding for quick fixes, and while it feels great in the moment, we’re going to pay for this later.

A couple of days ago, Cursor went down during the ChatGPT outage.

I stared at my terminal facing those red error messages that I hate to see. An AWS error glared back at me. I didn’t want to figure it out without AI’s help.

After 12 years of coding, I’d somehow become worse at my own craft. And this isn’t hyperbole—this is the new reality for software developers.

As a content creator in the tech space, I found myself caught in an all-too-familiar trap: endless hours of doomscrolling through social media and news aggregators, trying to stay on top of the latest trends.

The signal-to-noise ratio was abysmal—for every meaningful tech development, I had to wade through countless memes, heated arguments, and clickbait. I knew there had to be a better way.

Mark Zuckerberg recently claimed AI will replace mid-level engineers by 2025.

As someone building AI developer tools and studying their real-world implementation, I believe this fundamentally misunderstands both the current state of AI and the role of mid-level engineers.

Here’s what Meta is missing.