Is This AI? No, It's Just An If-Then-Else

When you run a local AI model but it's having an identity crisis. The DeepSeek model introduces itself as GPT-4, then immediately changes its story to being "DeepSeek R1" in the next message. It's like catching your date using someone else's profile pic, then frantically backpedaling when called out. Trust issues with AI: unlocked.

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The evolution of software development methodologies visualized with perfect accuracy: Waterfall: You meticulously build each component one by one, in strict sequence, until you finally have a car. No going back to fix the wheels once you've moved on to the chassis! Agile: Start with a skateboard, then a scooter, then a bike, then a quad bike, and finally a car. Each iteration is a functional product that gets you from A to B with increasing sophistication. AI: Just throw in a weird green alien car from The Jetsons at the beginning, and somehow it magically transforms into the same car as the other methodologies. Nobody knows how it works internally, but hey, it got there faster!

The eternal cycle of tech hype has reached AI, and seasoned devs are getting tired. Non-technical folks are out here acting like AI is going to replace us all tomorrow while pushing no-code solutions that barely work. Meanwhile, actual developers know the truth: these tools are just fancy autocomplete with good marketing. Instead of dropping cash on "AI that writes code," people could learn how their systems actually work and build sustainable solutions. But that requires effort, and why do that when you can just slap "AI-powered" on everything? The real kicker? We're the ones who'll have to clean up the technical debt when the hype dies down. Just like we did with blockchain, serverless, and whatever "vibe coding" is supposed to be.

That moment when a children's chair has better edge detection than your 3000-line image processing algorithm. Spent two weeks optimizing your code only to be outperformed by a piece of furniture from Blues Clues. The black outline is just mocking your gradient descent functions at this point.

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