← Back to Google
AI Prototyping PDLC Transformation Product Building

Product Source of Truth

A live AI prototype reimagining how Ads launches are tracked, communicated, and aligned on — replacing process-heavy workflows with a single, data-backed source of truth.

This work is under NDA. Visuals and specific metrics are redacted. The narrative focuses on design thinking, strategic approach, and impact at a structural level.

What it is

A live AI prototype designed to serve as the definitive source of truth for all Ads launches. The project reimagined the discovery phase by using a functional, data-backed tool — rather than static mocks — to drive alignment across Product, GTM, Leadership, and Support.

The problem

For Product teams

Launching meant creating multiple entries across disconnected systems and notifying different stakeholders — GTM, Support, Leadership — at different moments. The result was information overload and a high collaboration tax.

For GTM

No visibility into which launches were upcoming. Teams had to scramble last-minute to plan comms strategy and shape narratives without a reliable line of sight.

For Leadership

Walking to stage meant preparing well in advance, but there was no clear view of what was proposed, launched, or deprioritized. Teams resorted to ad-hoc presentations and trackers to share updates.

For Support

Lack of project visibility made it difficult to plan support services and draft help resources — leading to reactive, last-minute scrambles at launch.

What I did

PDLC transformation

Pioneered a prototyping-as-discovery mode of execution — using a live, instrumented codebase as the primary discovery artifact. This significantly reduced design handoff time and accelerated the build cycle for engineering.

Solo Product Builder

Acted as the sole designer and frontend developer, delivering the prototype to over 150 users from day one. Combined UX and frontend development, leveraging AI tools to move at the speed the project demanded.

Why it was hard

Speed vs. discovery

Traditional discovery would have been too slow for the scale of the 2026 roadmap. A critical milestone event meant there was a necessity to solve for immediate user needs while simultaneously using the prototype as a vehicle to learn and uncover the highest-value use cases.

Building on shifting ground

Requirements were being defined by PM partners in parallel with the build. Managing this risk — building with conviction while staying responsive to evolving scope — required constant judgment calls on where to invest depth vs. breadth.

Impact

Months saved
Reduced discovery-to-MVP timeline through real-time iteration on a live codebase
160+
Active users during pilot phase, with ~2m 34s avg. engagement time and weekly return cadence
Blueprint
Created a repeatable AI-led prototyping framework now adopted by adjacent design teams as part of Product Factory initiatives
← Customer Voice Conversational Coaching →

Perpetually in a state of beginner's mind.