TL;DR — We’re Using AI to Write Code Because We’re Lazy, and Not Putting AI in Software Because That’s Hard

Everyone’s out here treating AI like a cheat code for writing CRUD faster, like, “Yo GPT, make me a dashboard.” Boom—10 seconds later you’ve got 300 lines of JavaScript spaghetti that looks smart until you run it. Magic! Ship it, right?

Meanwhile, actually putting AI inside the product—like, say, recommending stuff, making decisions, personalizing things—that’s where the party ends and the real engineering begins. Suddenly it’s not fun anymore. Now you need:

• Clean data (which nobody has)
• Real monitoring (that doesn’t just say “it’s fine” until your AI starts recommending adult toys to toddlers)
• Model versioning, fallback logic, ethical audits, human-in-the-loop systems, logs that mean something, and KPIs that aren’t made up on a whiteboard by a guy who’s never deployed anything in his life.

But yeah, sure, let’s keep shouting about how “AI is changing everything!” while most software still can’t change a button color without a full regression cycle and a Jira ticket approved by seven managers.

AI writing code? That’s easy. You screw it up, roll it back. No one dies.
AI inside your product? That’s runtime. That’s risk. That’s “Why did the AI approve a $400K refund to someone named NULL?”

And here’s the real kicker: half the companies out here think they’re doing AI-in-software just because they threw a LLM behind a chat widget that answers, “I don’t know, ask support.” Bravo.

So why is no one doing it right? Because writing code with AI is sexy and gets likes on LinkedIn.
But building AI-powered features that actually work? That’s infrastructure. That’s DevOps. That’s culture. That’s discipline.

And let’s be honest—most teams still struggle with git merge conflicts, so I’m not putting my trust in them to build a self-learning user experience that doesn’t melt down during daylight savings.

We’re addicted to the dopamine hit of AI writing our code. But until we get serious about the boring stuff—testing, monitoring, fallback plans, ethical behavior—we’re not building smart software.

We’re just generating dumb code faster.