The defining trait is autonomy over a sequence of actions. An agentic system is given a goal, breaks it into steps, calls tools or APIs, observes the result, and continues until the goal is met. That is what separates it from a single prompt-and-response model.
The autonomy is also the risk. An agent that can act can act wrongly, which is why oversight controls, an approval gate on consequential actions, least-privilege permissions, and an audit trail, matter more than the model itself.
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From definition to a working system
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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