“Doctor, it hurts when agents create unreviewable PRs.” “Don’t do that.”
AI agents are producing large amounts of code that can be difficult for humans to review.
When agents generate thousands of lines of code at once, it becomes hard to spot errors or understand the logic. One way to manage this is to break projects into small, testable chunks. This approach keeps humans involved in the process while using AI to handle the bulk of the work.
For the public sector, this highlights the importance of transparency. Instead of treating AI as a black box, organizations can invite agents into existing human workflows. This ensures that every AI-assisted step remains visible and auditable by the people in charge.
How can we balance AI speed with the need for human oversight?
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