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AI Generates Code, Not Knowledge: A Developer's 5-Month Honest Assessment

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A developer and educator shares a key insight after five months of teaching and coding alongside AI assistants: AI tools can only produce useful output when the user already understands the underlying concepts. The author argues that AI functions as a statistical predictor, generating plausible-looking code that may contain errors, bad practices, or flawed assumptions invisible to inexperienced developers. To stay in control of AI-generated output, the author deliberately uses a simple technology stack — Nginx, Tomcat, MongoDB, vanilla JavaScript, and Java Beans — avoiding complex frameworks that add hard-to-debug abstraction layers. The piece also pushes back against manufactured urgency in the tech industry, calling out courses and influencers who pressure developers into rapid AI adoption under threat of becoming obsolete. The core message is that debugging and foundational knowledge matter more than ever in the AI era, and there are no shortcuts to genuine competence.

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