I led the design and scoping of lightweight AI features to reduce manual lift, eliminate duplication, and improve UX efficiency across Microsoft FastTrack’s onboarding and feedback systems. I designed these initiatives to accelerate productivity without requiring heavy back-end AI investment.
Core Problem
Identified Manual Research Overhead
I identified that manual research during onboarding planning was creating significant time waste, consuming 20-30 minutes per case and slowing down operations.
Diagnosed Feedback Signal Noise
I diagnosed that a lack of deduplication for user feedback was introducing signal noise into internal systems, making it difficult to prioritize engineering work.
Mapped Fragmented User Workflows
I mapped the user journey and found that users had to switch between multiple tools for research, feedback, and documentation, creating a disjointed and inefficient experience.
Strategic Objectives
- My goal was to deliver meaningful automation without overbuilding or creating heavy infrastructure dependencies.
- I aimed to reduce redundant manual labor and clean up feedback signal noise to reinforce trust in internal tooling.
- I scoped AI pilots that demonstrated a clear time-saved ROI, enabling me to earn prioritization without executive escalation.
Key Initiatives
- I scoped lightweight AI workflows directly within Dynamics 365 to automate onboarding research.
- I designed simple prompt templates that accelerated case preparation by 20-30 minutes.
- My focus was on a low-complexity solution to avoid backend infrastructure changes.
- I proposed a low-lift system with a '+1' interaction pattern to cluster duplicate feedback items.
- I designed it to clean up backlog signal quality and save hours in weekly triage time.
- This solution provides clearer prioritization signals for product and engineering teams.
Executive Summary
I created a flexible, low-code blueprint for advisory automation. By partnering directly with developers and framing ambiguous friction points as user stories with measurable ROI, I enabled non-technical testers to engage with AI models in a structured, safe, and consistent format without manual copy/paste or formatting between tools.
- ➤Enabled a single-form UX for high-trust document output.
- ➤Secured engineering commitment by tying pilots to operational efficiency outcomes.
- ➤Designed for enterprise extensibility with a unified delivery layer and modular prompt adaptation.