A playbook for human-in-the-loop checkpoints
A human checkpoint is meant to catch what the agent shouldn't decide alone. Placed well, it's nearly invisible — a fast approval on the rare case that needs one. Placed badly, it becomes a bottleneck that erases whatever time the agent saved. This guide covers where to put a checkpoint, who should own it, and how to keep it from becoming the former.
Start from risk, not from doubt
The instinct is to add a review step wherever you're unsure the agent will get it right. That leads to reviewing everything, which defeats the point. Instead, place checkpoints where a wrong action would be costly or hard to reverse — releasing a payment, changing a customer-facing record, sending an external message — regardless of how confident the agent's classifier is.
Match the reviewer to the decision
A checkpoint needs an owner with the authority and context to actually decide, not just a name attached to a queue. A finance exception belongs with someone who can approve payment. An escalated support ticket belongs with someone who can see the full account history. Routing a decision to the wrong reviewer just moves the bottleneck instead of removing it.
Give the reviewer enough to decide fast
The most common failure mode isn't the checkpoint itself — it's a checkpoint with no context attached. A reviewer who has to go open three other systems to understand what they're approving will either take too long or approve on autopilot. The checkpoint should carry the agent's reasoning, the data it used, and exactly what it's asking permission to do.
Track the checkpoint, not just the outcome
Log every checkpoint decision: what was proposed, who reviewed it, what they decided, and how long it took. That log does two things — it's the accountability record when a decision is questioned later, and it's the data you need to tell whether a checkpoint is actually catching problems or just adding latency.
Revisit checkpoints as trust builds
A checkpoint placed during a pilot, when nobody has evidence the agent is reliable, is not the same checkpoint you need six months into stable production. Revisit thresholds against the evaluation data — if a category of action has a long track record of correct, low-risk decisions, that's the evidence needed to loosen the threshold, not a guess.