Right now, there's a rumor floating around: "Just spend enough time with Claude, get its vibe, and BAM! Become a software engineer."
Not gonna happen. Claude will not make you a software engineer. At best, you'll be a script kiddie with the most advanced compiler known to humanity.
Why? Why is the idea of making vibe coding into software engineering is just a myth?
1) Writing code ≠ software engineering.
Claude is an execution engine. Perfect for fast scripts or even React components. Writing code is the easiest part of software engineering, which includes parsing data with Python, being different from memory management in C++, configuring secure VPCs, designing compiler passes, and many more. What does it boil down to? System design.
2) Dreaming about context engineering.
You may have heard people talk about tough prompts teaching you "context engineering." Nope. You can't prompt for the unknown unknowns. If you ask the AI to write you a backend, it will happily create tens of megabytes of code inside one database document. With the experience, you know how bad of an idea it is, because you've encountered document size limitations and network fees. LLMs go for the path of least resistance; lacking the engineering context to guide it, you get a poorly designed system.
3) The multi-million dollar security trap.
Think you can just vibe-code an authentication flow? AI is notorious for generating code that compiles flawlessly but is riddled with invisible vulnerabilities—missing rate limits, hardcoded secrets, and string-concatenated SQL ripe for injection. When you rely on AI to build your architecture, you aren't just risking a buggy app; you are opening the door to catastrophic user data leakage. And when that data spills, regulators won't care that Claude wrote your backend. You will be staring down GDPR fines and legal nightmares easily worth millions of dollars or euros. Security architecture isn't something you can prompt-engineer after the breach happens.
4) "Learning as you go"
Learning as you go is negligence, and the most dangerous take is that hitting the ceiling with your AI prompts will allow you to learn all the necessary things, like CI/CD pipelines, infrastructure, hardware sensitivity, and optimization. Hitting the ceiling doesn't mean spending a quiet weekend learning about DevOps and such. No, it will be hit when you lose data due to a production outage and receive a four-hundred-dollar invoice from Vercel after using the AI to build a computationally-intensive backend on Vercel.
Engineers know this ceiling is coming. And that's what allows them to avoid it, design the system in such a way that it will never happen.
Do not confuse smart autocompletion with good engineering practices.
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