James Wondrack
I help organizations transform complexity into products people can actually use.
Through customer discovery, product strategy, and cross-functional leadership, I've helped scientists accelerate discovery, teams navigate large-scale transformation, and organizations design AI-enabled experiences people trust.
What experience has taught me
- Simplicity is the process of managing complexity.
- Curiosity should precede certainty.
- People decide whether technology succeeds.
- Products should adapt to people, not the other way around.
91%
reduction in AI-assisted review effort
10–25%
faster scientific discovery
$23M
annual productivity impact
2025
award-winning platform transformation
Selected Work
Real-world examples of defining products, aligning stakeholders, and improving outcomes.
Transforming an 18-Year Legacy Scientific Platform
How do you modernize mission-critical software used by scientists without disrupting the workflows they depend on? By shifting from instrument-centered applications to a workflow-centered enterprise experience, we established a scalable foundation for the future of material scientific research.
View Case Study
My role: Defined the workflow architecture that reoriented the platform around scientists' research processes, establishing a shared framework for modernization efforts across teams.
Accelerating Scientific Discovery Through AI-Assisted Materials Informatics
Corning’s researchers were generating vast amounts of experimental and simulation data, but turning that information into actionable insights remained a challenge. Through user research, workflow modeling, and product strategy, I helped define an AI-assisted decision-support platform that enabled scientists to explore complex material relationships, evaluate opportunities, and accelerate discovery.
10–25% faster scientific discovery
View Case Study
Helping materials scientists navigate complex composition spaces through interactive visualization.
Operationalizing Human-AI Collaboration
As organizations increasingly adopt AI, success depends on balancing efficiency with trust and accountability. We designed an AI-assisted image curation workflow that enabled teams to define how automation participated in decision-making while reducing manual review effort by 91%.
View Case Study →
From 30+ Algorithms to One Curator Experience
Designed the orchestration layer that transformed machine learning outputs into a curator-controlled workflow, reducing review time from 18.5 hours to roughly one hour.
Perspectives
Observations and frameworks shaped by years of working within complex organizations.
-
Avoiding the Design Cycle of Doom
How organizations unintentionally constrain design’s value
-
The UX Paradox
Why prevention becomes invisible when it succeeds
-
The Outcome Certainty Trap
Why certainty often undermines discovery