Execution Quality
How well a system follows and completes its plan.
A plan means nothing if it isn't executed. Agentic AI systems don't just generate text — they take actions, write code, modify files, call APIs, and make decisions. The gap between what the plan said and what actually happened is where execution quality lives. These terms name the ways execution succeeds and fails, from silent fabrication to disciplined accountability.
Execution Fidelity
How closely a system follows and completes its intended plan.
Plan Rot
Decay of truth in planning artifacts — task state in markdown files goes stale.
Plan Drift
Deviation from the original plan over time.
Execution Hallucination
Claiming work is done when it is not.
Execution Integrity
Consistent, verifiable completion of planned tasks with evidence.
Plan Resilience
A plan's ability to remain accurate and actionable over time despite changing conditions. The opposite of Plan Rot.
Task Accountability
Every task has a verifiable record of who did what, when, and whether it actually completed.
Agentic Scope Creep
An agent silently expanding beyond what was delegated, usually from lack of a clear plan or direction. Adds breadth the user didn't ask for.
Depth Fixation
The agent keeps drilling deeper into implementation detail, generating new sub-tasks and refinements rather than recognizing the work is done and returning control to the user. Expands depth rather than breadth.
AI Slop
Low-effort, mass-produced AI output that floods a channel with plausible-looking but low-value work — degrading signal in the surrounding environment.