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AI - 9 min read

AI Product Design: Five Principles That Hold Up

Practical principles for designing AI products customers trust and use, beyond the prompt-and-pray pattern.

R

R. Okafor

Contributing Editor, AI & Innovation

Updated

AI products fail in predictable ways: opaque output, untrustworthy actions, and friction where there should be flow. These five principles help you avoid the common traps.

Augment, do not replace

Design AI to make a skilled user more effective. Replacing the user removes the judgment that catches errors.

Show your work

Surface sources, intermediate steps, and confidence. Users tolerate imperfect output if they can see the reasoning.

Make undo cheap

AI will be wrong. Easy reversal turns errors into learning instead of damage.

Earn autonomy

Start with suggestions, graduate to drafts, then to actions. Trust is earned across thousands of interactions.

Design for the bad day

Plan for outages, hallucinations, and edge cases. The best AI products degrade gracefully.

Key takeaways

  • -Augment users, do not replace them
  • -Show reasoning to build trust
  • -Earn autonomy gradually

Frequently asked questions

Should every AI product be an agent?
No. Most users want assistance, not autonomy. Agents fit narrow, repeatable workflows.

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