Human approval gates on the AI Agents track. Any action that spends money, deletes data, messages a customer, or changes permissions should pause for approval. The person sees the exact arguments, not a summary that can hide a field.
This lesson assumes you already worked through Graphs when the path is known.
The idea in practice
Pause the loop, store the pending call, and resume only with an approve or reject event. On reject, pass the reason back as an observation so the agent can revise.
A concrete check
goal = {
'track': 'AI Agents',
'lesson': 'Human approval gates',
}
checks = [
'input available at decision time',
'score matches the real decision',
'failure case written down',
]
print(goal['lesson'])
for item in checks:
print('-', item)
Run the sketch locally if you have Python. The printout is a reminder of the checks, not a trained model. Replace the strings with the real inputs from your own example before you treat it as a design.
What usually goes wrong
Approving a paraphrase ('refund the user') instead of the exact payload approves a different action than the one that runs. When this happens, stop adding parameters or tools. Fix the check, the data, or the permission, then run the same example again.
What to write down
- The input you are allowed to use at decision time.
- The output and the score or pass rule.
- One failure you will test on purpose.
- What you will not claim the system can do.
Practice
List four actions in your product. Mark which must pause. Write the exact fields a reviewer must see.
Self-check
- Say Human approval gates in one sentence that mentions an input and an output.
- Name the failure mode in this lesson and the check that would catch it.
Done when: you can explain this lesson without the page open, and you have a written failure case.