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AI & Agents

Human-in-the-Loop (HITL)

Human-in-the-loop is a design pattern where an AI system pauses and requires a person to approve, modify or reject an action before it proceeds. It is applied selectively — typically to actions that are irreversible, financially significant, or fall below a confidence threshold — rather than to every decision.

HITL is what makes autonomy safe to grant incrementally. Rather than choosing between a fully manual process and a fully autonomous one, an agent can run unattended on reversible low-value actions while keeping a permanent approval gate on anything consequential. Where each line sits is a business decision, not a technical one, and it should be explicit rather than emergent.

The pattern also produces the training signal that improves the system. Every human correction is a labelled example of what the agent should have done, which feeds directly into the evaluation set. Teams that treat approvals purely as a safety tax miss that they are also the cheapest source of high-quality evaluation data they will ever have.

Codazz builds this in production — AI Agent Development.

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Human-in-the-Loop (HITL)
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No, if applied selectively. Gating every action would, but gating only irreversible or high-value ones leaves the bulk of the volume automated while keeping the consequential decisions supervised. In practice an agent that resolves most cases autonomously and escalates the rest cleanly delivers more value than one that attempts full autonomy and is switched off after its first serious mistake.

Related terms

AI Agent

An AI agent is a software system that pursues a goal by taking actions, not just producing text.

AI Guardrails

Guardrails are the constraints that limit what an AI system is permitted to do, enforced outside the model rather than requested inside a prompt.

Agent Evaluation

Agent evaluation is the practice of scoring an AI agent against a fixed set of real tasks with verified expected outcomes, so that every prompt change, model swap or tool update can be measured rather than guessed at.

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