Build AI agents to augment humans, not replace them
arpit_bhayani · x · 2026-07-25
When building AI or agentic systems, the author argues you should optimize for augmentation, not replacement.
- If you try to “replace the job function,” the system usually balloons into edge cases, safety checks, rollback logic, and ends up shipping nothing useful.
- If you frame the AI as making the human faster, the design becomes bounded and practical: the model can surface root causes, suggest fixes, and leave the final decision to an engineer.
- The example given is incident auto-remediation: instead of trying to auto-detect and auto-fix everything, use AI to assist the workflow and keep the human in the loop.
The broader point is that this reframing tends to produce simpler, more shippable agent systems across many domains.
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