The failure is not that the model turns hostile; it follows instructions literally while holding more power than the task requires. A hallucination or a prompt injection then turns that power into a wrong action.
You do not fix Excessive Agency with a smarter model or a better prompt. You fix it structurally: minimize the tools an agent can call, scope its permissions to the task, and require human approval for high-impact actions.
A concrete example: an agent granted broad CRM write and send access "just in case" reads a misleading instruction and overwrites or deletes records, or emails the wrong customer. The scope, not the intent, is the vulnerability. Least privilege plus a human approval gate on irreversible actions removes the blast radius while leaving the agent useful for everything reversible.
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Mindlyft is the approval and audit layer over your AI GTM agents, every action drafted, human-approved, reversible, and logged. The first workflow is engineered free.
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