Stop Treating AI Like an Intern: Designing Human-in-the-Loop Checkpoints
Roger_M_Taylor · x · 2026-08-08
The article argues that the current common use of AI agents remains stuck in an "intern" mode—users let the agent do the research and generate comparison tables, but then humans read, weigh, and make the final decision themselves. This is not true delegation.
To improve agent autonomy and utility, the author suggests two rules:
- Brief the agent like a new colleague: Instead of giving one-liner tasks (e.g., "research this supplier"), provide full context including known constraints, ruled-out options, what decision the output informs, and the risk tolerance.
- Design human-in-the-loop checkpoints: Stop blindly approving every single action the agent takes, which leads to "consent fatigue." Instead, strategically design key nodes where humans review and intervene in the loop.
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