Two case studies, intentionally. The first shows where I am now - designing agentic AI systems where errors aren't UX inconveniences, they're compliance failures. The second shows the research rigour and end-to-end execution discipline that got me here. Together they tell a complete story.
A framework for mapping where AI agency is appropriate - and where it isn't - within enterprise financial reporting workflows. Designing the boundary between what AI handles and what stays with the human.
Read →Empowering non-analytical users to calculate simple numbers on their own - without filing a ticket to an analyst. End-to-end: discovery, research, concept, validation, delivery.
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