Goal
A prototype to design for proactive agentic workflows, exploring trust signals across a system of actions. The business wanted to explore what behaviours an agent should (and shouldn't) exhibit to drive market share and product adoption.
A prototype to design for proactive agentic workflows, exploring trust signals across a system of actions. The business wanted to explore what behaviours an agent should (and shouldn't) exhibit to drive market share and product adoption.
Proactive agentic interaction that reduces effort and builds system-user trust while enabling scalability
The starter prompt was just too broad
An unfocused AI Advisor prompt in the side-sheet created friction with users expressing 'blank page syndrome'. I used Figma Agent to suggest alternative patterns, then checked for feasibility with the engineers.
Human testing, agentic reasoning
Combining user testing (with target users) to validate the problem with the starter prompt was a real blocker to adoption, we used Figma Agent to generate a more proactive pattern that proved more engaging and trustworthy, instigating human-advisor interactions that scaled.
We used a Figma Agent Skill (FigAgent-Reasons.md) to validate the output.
We used a Figma Agent Skill (FigAgent-Reasons.md) to validate the output.
