Generative AI Tools —
Director of Product Design

Overview

Standing up design for a new 500-person AI organization

Concentrix spun up a new technology organization — roughly 500 people — with a mandate to build AI-enabled tooling, but no design function, no shared system, and no common process to build on. As Director of Product Design, I led design and the teams across three concurrent workstreams that gave the new org its foundation:

A design system — I directed a team to build a Material UI–based system and rolled it out across the 500-person org so disparate teams shared one language. PDLC — an AI-enabled tool that streamlines the entire product-development lifecycle, which I drove from executive vision through shipped tool. GILEs — a developer co-pilot, where I led the design of a sharper, more usable experience for engineers.

Because PDLC and GILEs were generative-AI products, the design work wasn't only screens and flows — it was defining where AI added value and making that legible to the people who would rely on it. Rather than bolting AI on at the end, I wove it into the process itself: specifying, step by step, how AI would show up for the people doing the work.

The Challenge

A brand-new org with no design function — and a mandate to build AI fast

A ~500-person organization had been stood up with no standardized process, no shared design system, and no design function to anchor any of it. The executive team wanted to use AI to streamline the product-development lifecycle — but had no clear picture of what that lifecycle actually looked like across the org.

My mandate was to establish the design foundation and ship AI tooling in parallel: build a system the whole org could share, extract and map a process no one had documented, and turn it all into products people would actually use — starting from near-zero on every front.

Workstream 02 · PDLC

PDLC — an AI tool to streamline the entire product lifecycle

PDLC began as an executive vision: an AI-enabled tool to streamline how the whole org takes a product from idea to launch. My job was to turn that ambition into something real — extracting the vision, understanding the actual process, and designing AI into every step.

1 · Extract the vision — executive event mapping

I facilitated event-mapping workshops with the executive team to pull their vision for the AI-enabled process out of their heads and onto the wall — mapping it in its entirety and establishing a shared language before any design began.

2 · Understand reality — SME interviews

I interviewed subject-matter experts for every step of the lifecycle — 24 in all — to learn how the work actually happened, where it broke down, and where AI could meaningfully streamline each step. The gap between the intended process and the real one reshaped the product's scope.

3 · Synthesize — process research

I gathered the process documentation scattered across the organization and synthesized it into one coherent picture of the product-development lifecycle — the source of truth the tool would be built around.

4 · Map it together — and design AI into every step

I mapped how all the steps connected into one end-to-end flow, capturing the outcomes, RACI (who's responsible, accountable, consulted, and informed), inputs, and — critically — how AI would show up at each stage. Rather than treating AI as a feature bolted on at the end, I wove it into every step of the process, so the team and leadership were aligned on exactly where and how it added value.

5 · Design it — wireframes

I translated the research into wireframes — testable flows for how a user would move through each stage of the lifecycle inside the tool.

6 · Ship it — the live PDLC tool

The essential steps launched as a live internal product. The PDLC tool tracks every product across its lifecycle stages — from intake and discovery through definition, build, and launch — with AI filling the gaps at each step.