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Mariano Rodrigo

Mariano Rodrigo

AI Solutions Engineer building production systems with artificial intelligence, automation, and full-stack architecture. This is my public engineering lab: architecture decisions, implementation reports, experiments, and lessons from real systems.

Human-in-the-loop review at scale

· automation, human-in-the-loop, operations

The goal of automation is not to remove humans. It is controlled leverage: let the system do the repetitive work and route human judgment to the few decisions that actually move the outcome.

Designing the loop

  • Confidence routing. High-confidence, low-stakes outputs auto-proceed; everything else lands in a review queue. The model decides what not to escalate.
  • Make review fast. Show the reviewer the output, the source, and the specific claim in question — not a raw blob. Seconds per item is the target, not minutes.
  • Capture the correction. Every human edit is training and evaluation data. Reviews that vanish are wasted signal.

Why it scales

As volume grows, the escalation rate should fall — because the corrections feed back into thresholds and prompts. If every new item still needs a human, the loop is not learning; it is just a slower manual process with extra steps.

A good human-in-the-loop system makes people sharper and rarer in the flow, never more chaotic. That is the line between leverage and theater.