Scrum Masters Are Safe

When everyone's out here treating ChatGPT and Copilot like their personal coding assistants, and you're just... not. You've somehow made it through an entire year writing actual code with your actual brain, and now you're wearing that smug superiority like a badge of honor. While your coworkers are prompting their way through PRs, you're out here manually typing semicolons like it's 2019. The look says it all: "I still remember what a for loop looks like without asking an AI." Whether that's admirable or just stubborn is up for debate, but hey, at least your GitHub contributions are authentically yours.

Modern programming is just AI shopping. Why solve a problem yourself when you can make five different AIs race to solve it for you? The real skill isn't writing code anymore—it's knowing which AI's hallucinations are least likely to crash in production. The "hit run on all five" part is where the true chaos begins. Nothing says "I trust my code" like throwing five different AI solutions at the wall and seeing which one sticks. Bonus points if you don't actually understand any of them but confidently present the winner in your next code review. The "like a psychopath" is just chef's kiss perfect. Because what's more psychotic than spending 3 hours asking AIs the same question when you could have just written the damn function yourself in 20 minutes?

First panel: AI reaching for a beautiful painting on the wall, representing our dreams of intelligent systems creating magnificent art. Second panel: Reality hits with a wall of if(){} statements. That's right folks, behind the curtain of every "AI" product your CEO is hyping up is just a glorified chain of conditional logic some poor dev had to write at 1 AM while questioning their career choices. Seven years of computer science education to write if(user_says_hello) return "Hello there!" but with better variable names.

The classic Drake meme perfectly captures the current tech ecosystem's absurdity. Rejecting the noble pursuit of solving actual problems (you know, the things software was originally invented for), while enthusiastically embracing yet another AI chatbot that generates cat poems in Shakespearean English. The pipeline from "I'm going to change the world with code" to "Check out my AI app that predicts what sandwich you are based on your GitHub commits" is alarmingly short. The VC funding paradox in action - actual solutions get ignored while the 47th AI image generator gets a $10M seed round.

The modern coding triangle of dependency! Students and ChatGPT walk hand-in-hand down the path of enlightenment (or cheating, depending on who you ask), while Stack Overflow watches from the shadows like a disappointed parent who knows they'll come crawling back eventually. Remember the good old days when we actually had to understand error messages? Now it's just "Hey ChatGPT, fix this garbage code" followed by "Actually, let me check Stack Overflow because this AI hallucinated a function that doesn't exist." The circle of developer life continues...

We've reached the point where developers have outsourced their entire debugging workflow to ChatGPT and Claude. Just paste the error, stare intensely at the screen like you're summoning ancient spirits, and wait for the AI overlords to fix your mess. Gone are the days of actually reading stack traces or understanding what your code does. Why waste time learning when you can just vibe check your way through production? The LLM becomes your personal debugger, therapist, and rubber duck all in one. Honestly though, we've all been there. Sometimes you just want the answer without the journey. But remember: the LLM is just guessing based on patterns. It doesn't actually run your code or understand your specific context. So when it confidently tells you to add await to a synchronous function, maybe take a second to think it through.