EraCode glossary
Neutral definitions you can cite or link to. Each entry explains one AI-era engineering concept and how it shows up in real development work.
Skill atrophy is the gradual weakening of coding judgment, debugging fluency, and code reading habits when developers over-delegate to AI.
AI coding skill decay is hands-on coding fluency loss from relying too heavily on generated code without deliberate practice.
Cognitive debt is the mental cost of accepting generated code without building enough understanding to debug or maintain it later.
AI-assisted engineering uses AI to accelerate software work while developers retain ownership of correctness, architecture, and review.
Codebase literacy is the ability to navigate, reason about, and safely change a specific codebase instead of relying on generic coding skill alone.
Developer skill retention is the deliberate practice of keeping a team's coding, debugging, and review abilities sharp as AI tools change daily workflows.
Daily coding practice is a short, repeatable habit where a developer writes, reads, or debugs code without an AI assistant drafting the first version.
Coding skill maintenance is the ongoing practice of preserving implementation, debugging, and review fluency while AI tools change daily workflows.
AI overdependence is when a developer ships work mostly by accepting AI output with too few reps in reading, debugging, or reasoning about the code.
Agentic coding is a workflow where an AI agent drives most of the implementation while the developer steps back from the code to an orchestrator role.
Vibe coding is a colloquial term for development driven by intuition and AI prompting rather than deliberate reading and reasoning about code.