By Shivacha Engineering
Trust is a product requirement
Users abandon AI features that are occasionally wrong in ways they cannot detect. The goal is not perfection — it is calibrated trust: users rely on the AI where it is reliable and can verify or correct it where it is not.
Show your work
Citations, highlighted source passages, the query behind a generated chart and a preview of the action an agent intends to take all let users verify quickly. Verification must be cheaper than doing the task manually.
Design for correction
Make it easy to edit, reject or refine AI output. Every correction is also feedback: captured properly, it improves prompts, retrieval and evaluation sets.
- Inline editing of generated content
- One-click rejection with reason
- Undo for AI actions
Keep humans in control
For consequential actions — sending money, contacting customers, changing records — suggest and confirm rather than act silently. Autonomy can grow as measured reliability justifies it.
Price the uncertainty
AI features have variable costs. Product design and pricing should account for model routing, caching and quotas so the experience stays good and margins stay healthy.
