Risk signal · Intent drift detection

Detect intent drift in AI-generated code.

Detect when AI coding agents solve a nearby task instead of the actual request. Map intent to code changes, tests, and acceptance evidence.

Direct answer: Intent drift happens when an AI coding agent produces work that is adjacent to the requested task but not actually aligned with the original intent. FeelGoot compares the task, constraints, changed files, and evidence to expose that mismatch before acceptance.

Why intent drift matters

The most expensive agent failures are not always syntax errors. They are plausible completions that miss the point while sounding finished.

An agent may add a fallback instead of fixing the root cause, change a different path than the requested one, or implement a narrower behavior than the acceptance criteria require.

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.

How FeelGoot maps intent

FeelGoot starts from the user request, acceptance criteria, constraints, and non-goals. It then checks whether changed files and tests are connected to those requirements.

The output is not merely a score. It is a reviewable map of what is supported, what is partial, and what does not connect to the task.

Common drift patterns

Adjacent feature: the change improves a related workflow but not the requested one.

Narrow patch: the code handles a single example but not the general behavior.

Summary inflation: the final answer claims complete work even when evidence supports only partial completion.

Context loss: the agent ignores constraints, non-goals, or prior decisions.

Direct answers.

What is intent drift?

Intent drift is a mismatch between the original task and the work an AI agent actually performed.

Can tests catch intent drift?

Sometimes, but only if the tests encode the real acceptance criteria. FeelGoot checks the relationship between intent, tests, and code changes.

Who needs intent drift detection?

Teams using autonomous coding agents for production code, infrastructure, migrations, or high-cost review queues need intent drift detection.

Give AI coding agents an evidence gate.

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