AI is starting to write more software code than ever before, but just because the code runs doesn't mean it's ready for prime time. And we're going to talk about that and more in today's version of Two Minutes on Tech by Art and Logic.

AI-assisted development has definitely changed the game. Developers can generate boilerplate code, build interfaces, and even write functional prototypes in minutes. But here's the catch: most of that code is missing context, business logic, scalability, security, compliance, and real-world edge cases. Code that runs isn't the same as code that performs under a load, handles exceptions gracefully, or integrates securely with real systems.

AI doesn't know your domain, it doesn't understand your users, and it can't anticipate edge cases or compliance needs—well, yet. It's come a long way, but it's not really ready for prime time yet. And some common gaps in AI-generated code include—hold on, let me get my nerd voice ready—sloppy development practices, weak architecture, missing test coverage, performance bottlenecks, security vulnerabilities, and lack of documentation or version control. I don't even look at it if it doesn't have version control. Don't get me out of bed if it doesn't have version control. That's my nerd voice.

Daisy, cue the... anyway, all of these are essential ingredients in turning code into something reliable and scalable. So what's the bottom line? AI can help you move fast, yes, but getting to production still takes experience, planning, good engineering, and some super nerds. Don't forget the nerds. AI writes code, but humans still build software. This has been Two Minutes on Tech by Art and Logic.