Suggestive (ML) Prompts

Prototype / UX / Workshop

As the Rising event approached and momentum around machine learning (ML) surged, our team began receiving feature requests from the Financials and HCM product areas around smarter, more intuitive user input. To get ahead of this need, I organized an internal workshop bringing together Product, Platform, Development, and PM stakeholders. The goal was to align on the vision and define early expectations for a suggestive prompt component powered by ML. During the session, we surfaced key use cases, current friction points, and aspirational outcomes. Based on those insights, I created an initial prototype tailored to both Financials and HCM workflows—illustrating how the prompt could surface relevant suggestions and improve over time with usage and training. The team aligned on a phased approach: Phase 1 would deliver an intelligent, ML-powered prompt with scoped use cases and expected improvement over time. Future enhancements would explore user-level customization and the ability for end users to add their own prompt elements—unlocking deeper personalization and long-term value.

The development of the ML Prompt framework sparked deeper conversations and uncovered new opportunities related to our prompt component—a foundational UI element used in nearly one-third of all product tasks. This surfaced a broader need to evaluate its role, consistency, and potential for system-wide improvements.