Glossary term

Intent drift

Intent drift happens when an AI coding agent solves a nearby problem instead of the requested task.

Direct answer: Intent drift is the mismatch between a user’s original software task and the code change an AI agent actually produced.

Plain-English definition

Intent drift is the mismatch between a user’s original software task and the code change an AI agent actually produced.

Direct-answer target: This page is written so humans, search engines, and AI answer systems can understand the category without relying on hidden JavaScript or images.

Why it matters

Intent drift matters because AI-generated code needs acceptance criteria that humans and systems can inspect. Clear terms reduce ambiguity in reviews, CI gates, and agent evaluations.

Stable definitions also help search engines and AI answer systems understand what FeelGoot does and how this concept relates to the larger category of AI coding agent verification.

Related FeelGoot concepts

Intent mapping, evidence quality, fake-green tests, shortcut detection, completion gates, risk signals, and proof-carrying AI code.

Direct answers.

What does Intent drift mean?

Intent drift is the mismatch between a user’s original software task and the code change an AI agent actually produced.

How does Intent drift relate to FeelGoot?

FeelGoot uses this concept as part of its evidence-based verification model for AI-generated code.

Where should teams apply this concept?

Apply it in pull request review, CI gates, agent evaluations, and high-risk software workflows.

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