Why AI-generated code is not enough
My new
feature on InfoWorld explores the gaps in AI-generated code and what needs to change.
Did we normalize AI-generated code too soon?
AI coding assistants promised productivity gains, but reality paints a more complicated picture. AI-generated code is now the norm — but it's also riddled with quality issues, security risks, hallucinations, and a lack of big-picture awareness.
Some worry AI will replace developers entirely, but experts tell a different story. As Steve Wilson puts it, "LLMs are like interns with goldfish memory." They're useful, but they lack the problem-solving ability that senior engineers bring to the table.
For my latest InfoWorld feature, I dug into where AI-generated code falls short — and what’s being done to fix it. Solutions are already in the works: better training data, more context, automated validation, human-in-the-loop processes, AI agents, and more. Time will tell how it shakes out.
I gathered opinions from many leaders in tech and reports on this fascinating subject — thank you to everyone who contributed!
Featured image credit: GuerrillaBuzz on Unsplash.
