AI for Junior Software Engineers (surya-digital.com)

Surya Digital announced a firm policy: software engineers with under one year of experience are prohibited from using any AI tools. The company argues this isn't anti‑AI but a pro‑fundamentals stance—new engineers must first build core skills (manual coding, debugging, architecture, specification writing and code review) before leaning on AI. The firm likens AI to a faulty calculator (claiming a 15–30% error rate) that can teach bad intuition if used prematurely, and warns AI’s autocomplete can create a false sense of competence that hides subtle bugs, security flaws and architectural anti‑patterns. For the AI/ML community this raises practical and ethical questions about deployment, onboarding and tooling: AI is a powerful productivity multiplier for experienced engineers who can instantly spot flawed outputs, but it can increase technical debt and senior review burden when misused. Key technical takeaways are clear — effective AI use requires the ability to validate model outputs, write precise prompts/specs, and perform root‑cause debugging — so organizations should consider staged AI access, training curricula, and assessment gates rather than blanket adoption. Surya’s stance underscores a broader tradeoff between short‑term velocity and long‑term engineering judgment.