What AI coding costs you
5 hours ago
- #AI-coding
- #cognitive-debt
- #developer-productivity
- AI coding tools like Cursor and Copilot have significantly improved developer productivity by reducing the need for manual searches and providing context-aware suggestions.
- The shift towards AI-assisted coding introduces cognitive debt, where developers lose deep understanding of the code they review, leading to skill atrophy over time.
- Studies show that developers relying heavily on AI score lower in conceptual understanding and debugging, essential skills for reviewing AI-generated code.
- The seniority pipeline in software engineering is at risk as juniors using AI produce senior-level code without understanding the underlying architecture, while seniors lose their coding skills by only reviewing AI output.
- Forced AI adoption in companies leads to gaming of metrics and reduced actual productivity, as developers perform unnecessary tasks to meet AI usage targets.
- The joy of coding and the creative flow state are diminished when developers shift from writing code to reviewing AI-generated output, leading to faster burnout.
- Finding the right balance in AI usage is crucial; cognitive engagement through asking questions and understanding AI-generated changes preserves learning and skill development.
- The long-term risks of over-reliance on AI include bugs that pass initial checks, codebases that no one fully understands, and a decline in the ability to debug without AI assistance.
- Executives pushing for full AI automation overlook the human cost, including mental fatigue and the erosion of critical thinking skills necessary for sustainable software development.