Human-in-the-loop design
Also known as: HITL, human oversight, human review step, approval gate
As AI systems handle longer, more consequential task sequences, one of the key design decisions is where to keep humans in the loop. Human-in-the-loop design is the practice of mapping out which actions are low-stakes enough to be fully automated versus which should pause for human review before executing.
The gradient matters. 'Full automation' and 'manual approval for everything' are both wrong answers for most real systems. A well-designed loop might auto-approve routine actions, flag medium-confidence decisions for quick human review, and require explicit sign-off before irreversible actions like deleting data, sending emails, or making purchases.
This isn't just about safety, it's also about learning. Human review points generate signal. They catch edge cases before they become incidents, build operator confidence in what the system is doing, and create data you can use to decide when it's safe to reduce oversight. Many builders find that human-in-the-loop gates are how you build trust in an agentic system over time, not a sign that the automation isn't working.