As a software engineer experimenting with AI for the past 2 years, I’ve tested nearly every AI coding assistant on the market and developed a workflow that consistently delivers results.

Here’s my tried-and-tested method for solo developers looking to leverage AI to make SaaS products.

Last week, X exploded when a “vibe coder” announced his SaaS was under attack.

His business, built entirely with AI assistance and “zero hand-written code,” was experiencing bypassed subscriptions, maxed-out API keys, and database corruption.

His follow-up admission made this notable: “as you know, I’m not technical so this is taking me longer than usual to figure out.”

As someone deeply immersed in the AI code generation space, I’ve been watching this unfold with a mix of sympathy and frustration. Let me be clear — I’m not against AI-assisted development. My own tool aims to improve code generation quality. But there’s a growing and dangerous fantasy that technical knowledge is optional in the new AI-powered world.

After observing many similar (though less public) security disasters, I’ve come to a controversial conclusion: vibe coding isn’t just inefficient — it’s potentially catastrophic.

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, and I’ve got some thoughts.

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 what actually works for me as a solo developer.

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.