Will AI‑Generated Code Make Programmers Obsolete? A Reality Check

Recent conversations among recent graduates wonder whether AI's ability to write code means the programming profession is dying. The author, an experienced embedded engineer, examines this claim.

He recounts a concrete project for an industrial‑control client: the technical director proudly showed an AI‑generated monitoring program that ran flawlessly in the test environment. In production, the code suffered memory leaks, race conditions, and poor exception handling, causing devices to reboot every three days. After two months of debugging, the team had to rewrite the core module.

The failure illustrates that AI‑produced code may look perfect on paper but lacks the experiential knowledge of real hardware quirks—such as specific UART bugs, electromagnetic interference, or temperature‑induced crystal drift—that only seasoned engineers acquire.

Programming, the author stresses, is far more than typing code; it involves understanding requirements, designing architecture, weighing trade‑offs, and solving problems. Writing code accounts for roughly 20 % of a developer's effort.

Even with a clear specification, engineers must decide on system architecture, reliability strategies, performance optimizations, and cost controls—decisions that AI cannot currently make because they require deep business and domain insight.

AI does change work habits: repetitive coding tasks can be delegated to AI, boosting efficiency, but core design, critical decisions, and complex debugging remain human responsibilities. Programmers who learn to harness AI become more valuable than those who ignore it.

The final recommendation is to treat AI as a tool, not an enemy: improve problem‑solving skills, focus on engineering judgment, and continue learning, because the future needs engineers, not just code writers.