Six Months of AI Coding Made Me Forget How to Write a Laravel API

AI programming assistants promise unprecedented efficiency, yet developers report a loss of basic skills; a software engineer at 404 Media recounts being unable to write a simple Laravel API after months of relying on AI.

Major tech firms highlight the shift: Google says 75% of new code is AI‑generated, Microsoft’s CEO notes the figure has reached 30%, and Meta’s Zuckerberg predicts most coding work will soon be taken over by AI, framing the narrative as a productivity breakthrough for investors.

Gartner analyst Daryl Plummer warns that daily reliance on AI‑generated code causes developers to lose coding ability, a view echoed by Manjunath Bhat’s “experience hunger” comment about AI turning junior developers into “quick‑growth” assets at the expense of real learning.

Point Health AI engineer Pia Torain describes sending hundreds of AI prompts daily and feeling her programming ability deteriorate, forcing herself to slow down and manually understand program architecture to avoid costly mistakes.

The phenomenon of “hallucinated code” adds hidden costs: Lightrun’s 2026 AI‑Driven Engineering Report finds 43% of AI‑generated changes require manual debugging despite passing QA, and 88% of companies need two to three redeployments to gain confidence.

Stack Overflow’s 2025 developer survey shows 84% use or plan to use AI tools, but only 3% highly trust AI output; 46% distrust accuracy, 66% say AI solutions are “almost correct but off,” and 45.2% cite debugging AI‑generated code as a major pain point.

Economic motives drive the trend: companies adopt AI to cut junior hiring costs, a short‑term financial gain that Futurum Group analyst Mitch Ashley warns could incur far greater long‑term expenses.

Harvard research indicates that after GPT‑4’s release, employment rates for 22‑25‑year‑olds in AI‑exposed jobs fell by about 13%, and junior developer hiring dropped 67% since 2022.

Azure CTO Mark Russinovich and GitHub VP Scott Hanselman, in an ACM Communications paper, warn that generative AI is fundamentally undermining software engineering talent pipelines, emphasizing the need for “system taste”—the deep judgment that only comes from hands‑on experience.

The article concludes by questioning whether code written without personal understanding truly remains under the developer’s control, urging a reevaluation of AI’s role in skill development.