Design AI agents, customers can trust
A guide to making AI feel trustworthy. Free, practical, and built from real product lessons.
Your AI works perfectly.
The technology is solid.
But users don't trust it.
They doubt results.
They hesitate to delegate.
They abandon your product before seeing its value.
When trust breaks, everything breaks
Users see AI as a toy
Without trust, even accurate outputs get dismissed. Your AI becomes a novelty feature users test once and abandon.
Things turn legal
Opacity around AI decision-making doesn't just frustrate users—it exposes you to regulatory risk and compliance issues.
Your brand is damaged
Trust is hard to build and easy to lose. One major trust breach can permanently damage your reputation and market position.
Users leave, costs rise
Low trust means low adoption. That means higher support costs, negative reviews, and an uphill battle for every new user.
A brand is trust
Steve Jobs said a brand is just one thing — trust. In AI, that trust is built one honest interaction at a time. The Trust Builder framework helps you make each one count.
Meet Joy: Your Guide to Trust-Building Design
Throughout the guide, you'll follow Joy, an AI concert planning agent helping you book an Oasis concert trip. Joy finds the best seats, books a nearby hotel, and arranges flights, all within your style and budget.
What you'll get
A framework for designing trust
The Trust Builder works across all AI experiences — assistants, agents, autonomous systems, or recommendation engines. Learn the principles once, apply them everywhere.
Real UI examples
Explore how trust-building design comes to life in practice. This guide presents a narrative where an AI agent, Joy, assists in planning a trip for an Oasis concert in London. Joy's interactions exemplify every trust-building pillar through dedicated UI patterns.
Ready-to-use checklists
5 practical checklists to evaluate and improve your AI immediately:
- Competence: Core reliability, asking questions, showing work
- Transparency: Clear explanations, visible process
- Predictability: Setting expectations, consistent flow
- Alignment: User goals first, clear intentions, fair trade-offs
- Resilience: Error handling, recovery options
Designer tips you can apply today
Practical insights and quick wins. No fluff, just actionable guidance.
Competence
Joy asks the right questions and delivers reliable results
Transparency
There is a reason behind every recommendation
Predictability
The process follows a clear, consistent flow
Alignment
Joy consistently prioritizes your needs over hers
Resilience
When things fail, there is a safe recovery to your work