The "Human-in-the-Loop" Architecture: Where Automation Ends
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The "Human-in-the-Loop" Architecture: Where Automation Ends

K
Kaprin Team
Jan 24, 20269 min read

The biggest mistake leaders make is asking: "Can AI do this job?" The answer is usually "Sort of." The finding "Sort of" is what leads to failure.

The goal is not 100% automation. It is 90% Automation + 100% Reliability. That last 10% comes from humans.

The Confidence Score Router

Every decision an AI Agent makes has a statistical probability (Logprobs). Efficient systems surface this as a "Confidence Score."

  • Scenario A (High Confidence > 98%): User asks "Reset my password." AI handles it instantly. Zero human touch.
  • Scenario B (Low Confidence < 80%): User asks "Why did my rate change?" The AI sees conflicting data. It does NOT guess. It routes the ticket to a human queue, but pre-fills the draft answer: "I think it is because of rate hike X, but please verify."

The "Cyborg" Workflow

This creates a "Cyborg" workflow. The human agent doesn't start from a blank page. They start as an editor. They review the AI's low-confidence guess, fix it, and hit send.

Crucially, the fix is fed back into the training set. Every time the human corrects the AI, the AI gets smarter. This is the "Data Flywheel." Over time, the 80% confidence threshold moves to 85%, then 90%.

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