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Conducting pre-research with AI agent personas: Pressure-testing concepts for expert workflows

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Conducting pre-research with AI agent personas: Pressure-testing concepts for expert workflows

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Wednesday, June 10, 2026 • Designing with AI 2026

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Conducting pre-research with AI agent personas: Pressure-testing concepts for expert workflows
Speakers: Snehal Pendharkar
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Summary

Designers in complex domains like finance, healthcare, or government are often asked to design for expert workflows they barely understand, while their subject-matter experts are too busy to join every iteration. This case study shows how niche AI “agent personas” became an always-available, domain-aware first pass on ideas—helping a UX professional in fintech to pressure-test concepts, understand upstream/downstream impacts, and arrive at better prototypes faster. In this work, AI serves explicitly as a pre-research layer, not a substitute for real users, formal research, or usability testing, ensuring that human insight remains at the center of the design process.

Key Insights

  • AI personas can help UX teams pre-emptively pressure test complex workflows before SME access.

  • Structuring AI personas with detailed role, goals, pain points, and boundaries ensures specific and relevant feedback.

  • Including a confidence summary in AI responses helps users distinguish between grounded facts and inferences, mitigating hallucinations.

  • AI critiques of wireframes expose operational friction and workflow gaps, not just surface usability issues.

  • Integrating AI with codebases improves understanding of data lineage, user entitlements, and ecosystem dependencies.

  • AI cannot guarantee policy compliance or capture all organization-specific exceptions.

  • Early AI involvement fosters confident preparation and sharper questions in SME reviews.

  • AI-driven expanded scope can cause scope creep, needing prioritization and feasibility discussions with technology teams.

  • AI responses are generally repeatable and consistent when grounded in stable persona definitions.

  • AI pre-research helps challenge operational workflows, uncovering inefficiencies that improve overall UX beyond UI enhancements.

Notable Quotes

"Can AI help us do better in pre-research for expert-heavy workflows before we actually get access to the subject matter experts?"

"The real problem is that the team is already making decisions in incomplete conditions."

"Generic advice is usually too broad for a complex workflow such as escalation or compliance."

"AI personas can be valuable as bounded pre-research tool helping us think earlier and reduce avoidable gaps."

"The confidence summary was added to remind us that the AI response is provisional and needs verification."

"When AI got it wrong, it did so in ways that matter operationally, skipping required compliance or assuming outdated workflows."

"The biggest improvement was confidence — walking into a room with senior stakeholders prepared to ask sharper questions."

"AI cannot replace user research, usability testing, or domain expert validation."

"AI helped me challenge operational workflows and ask why approvals happen multiple times across systems."

"Running the same prompt with a defined persona produces consistent and reliable AI responses."

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