Dell Deterministic Finder Tool

Built for scale and speed, this tool uses recursive scanning and AI-driven detection to locate keywords across entire design ecosystems. Search results are compiled into a structured list of artifacts, sorted by most recent usage and grouped by file and page. With a single click, users are deep-linked into the exact canvas location-auto-zoomed to the relevant element for immediate inspection or copy. The result is a deterministic, reliable search experience that bridges fragmented files and accelerates workflows.


From search to source in one click.

With a single click, designers are taken directly to the exact location of the artifact, automatically zoomed in and ready to use, dramatically improving speed, accuracy, and workflow efficiency.

  • Design artifacts were buried across multiple files and versions

  • Searching required manual scanning and deep file navigation

  • No direct way to jump to the exact location of an element

  • Designers wasted time recreating assets that already existed

  • Workflows slowed down due to fragmented systems and lack of visibility

My Role

I led the end-to-end design of this AI-powered Figma plugin, owning both the product vision and user experience. My role spanned from early concept development and system architecture planning to UX flows, interaction design, and final interface execution. I worked at the intersection of design and AI, translating complex technical capabilities into intuitive, usable workflows for designers.

  • Defined product vision and core use cases

  • Designed system architecture and user flows

  • Created wireframes, interaction patterns, and UI designs

  • Collaborated with engineers on AI integration and feasibility

  • Iterated based on usability and workflow efficiency goals

The Initial Idea

This initial architecture and UX planning phase focused on bridging AI capabilities with real design workflows inside Figma. The system was structured to translate unstructured inputs, like PDFs, keywords, or natural language queries, into actionable design outputs.

By mapping how data flows between the plugin, LLM, and Figma’s environment, the foundation ensured that search, retrieval, and placement of design elements could happen seamlessly within a single experience.

UX of Initial Idea

On the UX side, the goal was to eliminate friction and reduce cognitive load. Instead of forcing users to navigate complex systems, the interface was designed around simple, intuitive actions: search, select, and place. Early flows prioritized clarity, giving users visible control through structured results, clickable options, and predictable outcomes. This ensured that even with advanced AI working in the background, the experience remained transparent, fast, and easy to trust.

  • Defined system architecture connecting Figma plugin, LLM, and design file ecosystem

  • Translated unstructured inputs (PDFs, keywords, chat) into structured design actions

  • Designed a simplified UX flow: search → review options → place element

  • Prioritized real-time feedback and clear system responses for user trust

  • Reduced complexity by embedding all actions directly within the design environment

  • Established scalable logic for multi-file search, retrieval, and placement

The Design Process

The design process was driven by one goal: make something powerful feel effortless. I started by breaking down how designers currently navigate files, reuse components, and search for past work, highlighting inefficiencies and repeated behaviors.

The design initially had users upload the entire brief for their design file and allow the AI to generate an entire rough drafted design with copy indicating where past artifacts were located.

However, this consumed too many tokens for the AI and caused many technical crashes or time delays in the designers’ work.

Phase 1

From there, I designed around a simple mental model: users shouldn’t have to think about where something lives, only what they’re looking for. This led to a streamlined flow where AI handles the complexity in the background, while the interface presents clear, actionable choices.

After holding multiple meetings with the design team, the main friction point for them was not generating designs from the brief, but rather trying to find old artifacts from previous design files to copy/paste and iterate. This is what caused them to lose the most time.

Phase 2

Through iteration, I refined how results are surfaced, how users move between options, and how placement feels immediate and predictable. Every decision prioritized reducing friction and keeping designers in their flow.

  • Mapped existing behaviors and inefficiencies

  • Designed around a “don’t make users think” principle

  • Simplified AI complexity into clear UI patterns

  • Iterated on result hierarchy and interaction clarity

  • Focused on maintaining flow within the design environment

Phase 3

The experience was designed around a simple, repeatable flow: search, review, and place. Instead of navigating across files, designers can query what they need and instantly see relevant results pulled from across the entire design system.

Results are structured and ranked by recency, giving users clear, actionable options. Each result acts as a direct entry point allowing designers to jump straight to the exact location of an element or place it directly into their current file.

  • Multi-file keyword search across entire design ecosystem

  • Results organized by file, page, and recency

  • Clickable options for quick navigation or direct use

  • Seamless flow from discovery to action

Core Experience

Interaction and System Design

The interaction model prioritizes clarity, speed, and trust. Every action has a predictable outcome, search returns structured results, selection reveals context, and placement happens instantly within the canvas.

Behind the scenes, recursive scanning and AI-powered keyword detection enable deep visibility across files, while the interface keeps that complexity hidden. Users are given control through clear options, without being overwhelmed by the underlying system.

  • Clear, predictable interaction patterns

  • AI-powered scanning without added user complexity

  • Direct placement into selected frames or pages

  • Real-time feedback to reinforce user confidence

By eliminating manual searching and fragmented workflows, the tool significantly reduces time spent locating and recreating design assets. Designers can move faster, reuse existing work more effectively, and maintain greater consistency across files and teams.

This project reinforced the importance of designing AI-powered tools that feel intuitive and transparent. Rather than exposing complexity, the most effective solutions embed intelligence into familiar workflows, enhancing, not disrupting, how people already work.

  • Reduced time spent searching across files

  • Minimized duplicate design work

  • Improved consistency across teams and outputs

  • Streamlined workflows within a single environment

Reflection:
Balancing powerful AI capabilities with a simple UX was the biggest challenge. This experience strengthened my ability to translate complex systems into clear, usable products while maintaining speed, trust, and usability.

Impact and Reflection