Human-Code Divergence
The gap created between a user and their codebase when an agent mediates all development.
Human-Code Divergence is a new class of problem unique to agentic coding. The developer stops writing code directly and instead describes what they want to an agent that writes it. Over time, a gap opens: the developer knows less and less about how their own codebase works. They know what it does but not how. They can describe features but can't trace bugs. They own the product but not the implementation. This isn't inherently bad — abstraction is how all engineering progresses — but it becomes dangerous when the developer can't review, understand, or override the agent's work.
More in Human-Agent Relationship
Cognitive Load
The mental burden placed on the human when working with AI systems.
Agency Erosion
Gradual loss of human decision-making authority as agents take over more workflow without checkpoints.
Skill Atrophy
Decay of human technical skills from prolonged delegation to agents.
Automation Dependency
Reliance on agents to the point where the human can't perform the task without them.
Trust Without Verification
Accepting agent output without review — a precondition for Execution Hallucination going undetected.
Confidence Decay
The gradual erosion of user trust as a system repeatedly loses context, hallucinates, or fails to follow through.
Capability Illusion
The user believes the AI can do more than it actually can, leading to over-delegation and undetected failures.
Learned Helplessness
The user stops attempting tasks they could do because the agent is "supposed to handle it."