Sun, Feb 1, 2026

Notes on "How AI assistance impacts the formation of coding skills" Article HN

• AI speeds up coding but reduces deep understanding and mastery
• Juniors (1-3 years experience) showed speed improvements with AI, but 4+ year developers showed no difference
• Modern software work is more about requirements, specs, documentation, and communication than raw coding skill
• Small sample size (n<8) and study design limitations make results questionable
• Takeaways:
  1. Use AI for high-scoring interaction patterns: Ask conceptual questions and request explanations rather than just code generation
  2. Adopt AI for documentation and specs: Multiple developers report dramatic improvements in tickets, PRs, and documentation quality
  3. Be deliberate about learning: If using AI, actively practice explaining concepts and avoid pure copy-paste workflows
  4. Use AI to reduce grunt work: Let it handle boilerplate, test writing, and repetitive tasks while focusing on architecture and requirements
• The research confirms what many suspected: AI coding assistants create a real trade-off between speed and skill development, but the practical significance is hotly contested. The critical question isn't whether AI reduces learning (it does), but whether deep coding skill remains as valuable as expressing requirements clearly—and whether we're comfortable with a generation of developers who can't function without AI assistance.