Is AI really coming for your job, or is the panic just another tech-fuelled mirage?
Every other headline screams that artificial intelligence will replace developers overnight. Yet seasoned coders keep shipping features, stand-ups still run daily, and recruiters still ask for five years of React experience. So what’s the disconnect? Let’s peel back the hype and look at the messy, fascinating truth behind AI in software engineering.
The Promise That Lit Up Twitter
Remember the first time you saw ChatGPT spit out a working Python function? Jaws dropped. OpenAI and Meta execs doubled down, predicting artificial general intelligence within years. Venture capital slid term sheets across the table like hot pizza. Overnight, LinkedIn filled with posts claiming junior devs were obsolete. The promise was intoxicating: push a button, get code, ship faster. But promises age quickly in the harsh light of production. What looked like magic in a demo turned into a debugging nightmare when the same model hallucinated an entire API that never existed. The hype cycle spun so fast that reality became optional.
The Glitches Nobody Retweets
Here’s what the demos don’t show. AI still hallucinates functions that sound right but don’t compile. It lacks any sense of risk—confidently suggesting a database migration that would nuke user data. Reasoning gaps appear when edge cases pop up; the model loops, repeating the same flawed logic. Goal-setting? Nonexistent. Ask it to refactor a legacy monolith and it cheerfully suggests rewriting everything in Rust without considering team skill sets, deadlines, or budget. Problem-solving is hit-or-miss; it can optimise a bubble sort yet miss the obvious memory leak in the next line. These aren’t edge bugs—they’re architectural limits baked into today’s artificial intelligence. And every time a senior dev spends an hour untangling AI-generated spaghetti, the promised productivity gain evaporates.
The Human Advantage That Refuses to Retire
Developers do more than write code. They weigh trade-offs, negotiate scope creep, and calm angry product managers at 2 a.m. They read the room when stakeholders say “simple change” yet mean “rebuild everything.” AI can’t gauge office politics or sense when a deadline is political, not technical. It can’t mentor interns or decide which technical debt can safely rot for another quarter. The human advantage lies in context, empathy, and accountability—traits no language model has mastered. Instead of extinction, the near future looks like a partnership: AI accelerates boilerplate, humans steer architecture. Reskill, adapt, and the hype becomes a toolbox rather than a tombstone.
