Building trust in agentic tools: What we learned from our users

As AI agents increasingly contribute to software development, building trust between humans and these autonomous systems becomes vital, according to GitLab's UX Research team. Their study reveals that trust isn't formed through singular breakthroughs but through numerous "micro-inflection points"—subtle design choices and interaction patterns that gradually build confidence in AI agents over time. The research identifies four pillars essential for trust: safeguarding actions, providing transparency, remembering context, and anticipating needs. Safeguards like confirmation dialogs and rollback capabilities ensure security, while transparency transforms AI agents into comprehensible partners. Remembering user preferences and adapting to feedback further enhances trust, and anticipatory capabilities allow agents to proactively support workflows. Organizations are advised to implement AI agents in low-risk environments initially, gradually increasing reliance as trust grows. The study emphasizes that trust compounds through consistent positive micro-interactions, transforming AI agents into indispensable partners, while a single failure can significantly undermine accumulated confidence.

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