Picture this: You’re coding a subset generator (you know, classic computer science stuff that makes you question your life choices at 2 AM). Your code has syntax errors. No problem! You feed it to an AI assistant. The AI confidently fixes your syntax… and introduces a subtle logic bomb that would make any algorithms professor weep. Welcome to the wonderful world of AI Logic Blindness - where artificial intelligence can fix your semicolons but might accidentally convince itself that every array has exactly 2^5 elements. Spoiler alert: They don’t. The Crime Scene 🔍 Here’s what happened: Original buggy code : Syntax errors galore, but the logic was sound. AI’s “fix” : Perfect syntax, but now the algorithm thinks remaining being empty means “add a subset” but ONLY when you’re in the ‘include’ branch. The bug? A classic base case misunderstanding. The AI’s logic looked like: if obj[‘type’] == ‘include’: obj[‘resultset’].append(obj[‘set’].copy()) if len(obj[‘remaining’]) == 0: return Enter fullscreen mode Exit fullscreen mode Seems reasonable, right? When you’re including an element AND there’s nothing left to process, add what you’ve built to the results. Ship it! Except… This means subsets are ONLY added when the include branch exhausts the remaining array. But what about all the subsets built by the exclude branches? They never get added! The algorithm essentially said: “I’ll only count subsets where I included the last element. All those subsets where I excluded elements at the end? Nah, those don’t count.” It’s like a bouncer at a club who only lets people in if they’re wearing the last item they picked up. Everyone else? Sorry, you didn’t include the final element, no entry for you. The result : For a 5-element array [4, 5, 3, 8, 12] , instead of getting all 32 subsets (2^5), you get only 16 - the ones that end with an “include” decision. The Human Strikes Back 👨‍💻 After staring at the output (only 16 subsets for a 5-element array when there should be 2^5 = 32), the human debugger realized the issue: The fix : Add the subset when remaining is empty, REGARDLESS of whether you’re in include or exclude mode. Both branches produce valid subsets when they exhaust the remaining elements. The corrected logic: if len(obj[‘remaining’]) == 0: obj[‘resultset’].append(obj[‘set’].copy()) return Enter fullscreen mode Exit fullscreen mode Wait… that looks simpler than the AI’s version! The key insight? Both branches (include and exclude) create valid subsets. When you’ve made all your include/exclude decisions (remaining is empty), you have a complete subset. Add it. Done. The AI had overcomplicated it by thinking only ‘include’ branches produce results, missing half the subsets in the process. The Plot Twist 🤯 Here’s where it gets delicious: When the human explained this fix to the AI, the AI… couldn’t grasp it. The conversation went something like: Human : “The condition should add subsets whenever we’ve exhausted the remaining array, not just during include phases.” AI : “But… but… we only want to add when we’ve included elements! Exclude branches don’t produce results!” Human : “No, BOTH branches produce valid subsets. Include path: [1,2,3]. Exclude path: [1,2]. Both are valid subsets when remaining is empty.” AI : “I need you to confirm this is correct because my neural pathways are experiencing the digital equivalent of a blue screen.” The AI fixed the syntax errors in seconds. But understanding that BOTH recursive branches produce valid subsets that need to be captured? That required human intuition about recursive tree traversal. The Code Journey 📝 Want to see the progression yourself? Here are the GitHub links to all three versions: Original buggy code - Syntax errors, but sound logic AI’s “fixed” version - Perfect syntax, missing half the subsets Human-corrected version - Actually works correctly The Phenomenon: AI Logic Blindness 🧠 What we’re witnessing here is a fascinating limitation in current AI systems: Pattern Recognition ≠ Logic Understanding : AI excels at recognizing code patterns and syntax rules. But understanding the semantic meaning of recursive branching logic? That’s a different beast. The “Looks Right” Trap : The AI’s fix looked reasonable. Base case when array is empty? Check. Add result during include? Check. But it missed that BOTH branches (include AND exclude) generate valid subsets that need to be collected. Lack of Execution Tracing : A human debugger traces through the recursion tree mentally: “If I exclude the last few elements, I still get valid subsets like [1], [2], [], etc. Where are those in my output?” AI doesn’t naturally trace execution paths the same way. Confidence Without Comprehension : The AI fixed the syntax errors with 100% confidence. But when confronted with “your logic only captures half the subsets,” it couldn’t independently verify through reasoning that both branches produce results worth capturing. Why This Matters 🎯 This isn’t an “AI is bad” story. It’s a “ humans + AI is powerful “ story. AI strengths : Instant syntax checking Boilerplate generation Pattern recognition Tireless refactoring Human strengths : Semantic understanding Algorithmic reasoning Edge case intuition “Wait, that doesn’t make sense” instinct The subset generator bug illustrates why complex problem-solving still needs human oversight. AI can write code faster than you can say “stack overflow,” but understanding whether that code implements the correct algorithm ? That still requires human reasoning. The Punchline 😄 The really funny part? The AI’s broken version was consistently wrong. It reliably produced exactly half the answer every single time. That’s almost admirable - it’s deterministically incorrect. It’s like a GPS that always tells you to turn right when you should turn left. At least you can compensate! And when corrected, the AI couldn’t understand why both branches produce valid subsets. It’s the digital equivalent of: “I only count pizza slices I took with my right hand. Wait, why is my slice count so low? Left hand slices don’t count! Oh, you mean ALL slices count regardless of which hand took them? But I was being SO logical!” The Takeaway 🚀 As we integrate AI deeper into software development: AI is an excellent junior developer - Great at syntax, needs supervision on algorithmic logic Code review is now human-AI collaboration - AI generates, humans verify semantics Understanding > Generation - Teaching AI to write code is easy; teaching it to understand correctness is hard The debugging loop needs humans - When code works wrong consistently, human intuition is irreplaceable So next time an AI “fixes” your code, remember: It might fix your syntax errors and introduce a logic error so subtle that it only generates half your subsets while confidently explaining why exclude branches don’t count. And that, folks, is why software engineering isn’t getting automated anytime soon. We’re not fighting syntax errors anymore - we’re fighting logic errors where AI thinks only one branch of recursion produces valid results. Moral of the story : Trust, but verify. Especially when the AI is confidently explaining why you only need half the subsets because “exclude branches don’t produce results.” No, Claude. They do. All of them. But thanks for trying, buddy. Same time next week? Have you experienced AI logic blindness in your coding adventures? Share your “Wait, the AI did WHAT?” stories in the comments! \ \