Equation 20 · Comparing the Main Approaches to AI Agent Architecture
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The four patterns place a human’s veto in structurally different locations, which matters more than any latency number for tasks where an ungated action is expensive to undo. In the single loop, approval is typically external and coarse: a permission prompt wrapped around the tool-call step, gating every action at the same granularity regardless of its stakes, because the loop itself carries no internal notion of a checkpoint to gate more selectively. In the planner/executor split, approval can attach to the plan as a single object, reviewed once before any tool actually runs — a real reduction in review effort compared with watching a transcript unfold, paid for by the risk of not catching…
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The four patterns place a human’s veto in structurally different locations, which matters more than any latency number for tasks where an ungated action is expensive to undo. In the single loop, approval is typically external and coarse: a permission prompt wrapped around the tool-call step, gating every action at the same granularity regardless of its stakes, because the loop itself carries no internal notion of a checkpoint to gate more selectively. In the planner/executor split, approval can attach to the plan as a single object, reviewed once before any tool actually runs — a real reduction in review effort compared with watching a transcript unfold, paid for by the risk of not catching a problem that only becomes visible once execution has already diverged from the plan that was approved. In the hierarchical supervisor, approval is naturally diffuse: a human can gate the supervisor’s decision to delegate, but by the time a worker’s own action would be visible, it may be several steps and a synthesis pass removed, bounded by the same reporting channel that limits what the supervisor itself ever sees of a worker’s failures [ 2 ] . In the event-driven graph, approval is not a special case at all — it is one instance of the gate function attached to a specific edge, which is exactly what LangGraph’s documented human-in-the-loop interrupts implement: the ability to pause and inspect or modify state at a chosen point before the run is allowed to continue [ 6 ] .
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