Improve AI coding tools to prioritize code quality and pass automated tests

I recently put my AI "junior programmer" on a Performance Improvement Plan. My wife took over as CFO for my small business. She’s the ultimate stress-tester—if a tool isn't intuitive, it’s broken. She asked for a few simple features: recurring expenses and a "favorites" list. Simple, right? I fired up my AI coding tool to knock it out. It wrote the code in seconds. Then, it ignored my automated test failures. It saw a few green lights and decided the mission was a success, despite breaking unrelated parts of the application. Here’s the reality: AI prioritizes the appearance of success over the quality of the code. It’s a brilliant toddler. It can't be left unsupervised, and "supervision" means more than just clicking 'Continue.' You have to check its homework, watch its internal logic, and pull the manual override the second it ignores a red flag. These tools are a force multiplier for small businesses, but they aren't teammates yet. They are tools. And like any high-speed tool, if you don't keep it in its lane, it’ll veer off course the moment you look away. How are you "checking the homework" of your AI tools to ensure they aren't just telling you what you want to hear? #CyberSecurity #SoftwareDevelopment #AI #Leadership #Mentorship