LESSEN LLC
•
2026
Developed scalable AI design system for multi-product ecosystem
Responsibilities
Design System · UX Strategy · System Architecture · AI Interaction Design · Research Synthesis
Project Scope
B2B · B2C · B2B2C · AI Platform · Desktop & Mobile · AI Interaction Layer on Existing Design System
Team
Solo Designer · PM
Timeline
2 months
The Brief
AI was introduced piecemeal across chat and workflows without a shared interaction model, leading to fragmented patterns and unclear boundaries of use. This project defined a unified AI interaction system and architecture layer to standardize how AI is embedded and behaves across the product.
Intent
The goal was to design an AI interaction architecture grounded in real usage patterns rather than default chat‑first assumptions. The system needed to standardize how AI appears across workflows and chat, and give teams a shared framework to scope, compare, and evaluate new AI features.
IMPACT
Established a unified AI interaction system across chat and embedded workflows, creating a consistent model for how AI is surfaced and integrated across the product ecosystem. This reduced ambiguity for teams designing new AI features and introduced a shared structure for evaluating, prioritizing, and building AI experiences.
System Design
New HCAI Framework
System Components
30+ Components
System Scope
6 B2B Products
APPROACH
SOLUTION
A unified AI interaction system that defines how AI is embedded into workflows and how it behaves across chat. The system separates reusable UI patterns from interaction types, allowing teams to design consistent AI experiences without redefining behavior for each new feature.
03
HCAI Framework
Introduced a classification framework separating Workflow AI (bounded, task‑based interactions) from Agent AI (open‑ended conversational interactions), providing a shared decision model for how AI should be designed and embedded.
RETROSPECTIVE
HOW MY PROCESS HAS CHANGED
This project reinforced a systems‑first approach grounded in observed behavior and usage constraints. I now begin system design by understanding what users are trying to accomplish and how they naturally engage with AI, then shape the interaction architecture and patterns around that, rather than starting from predefined UI components.
WHAT COULD BE IMPROVED
Future iterations would extend the system into more complex AI workflows and define clearer guidance around agent behavior, tone, and interaction consistency as AI capabilities evolve. I would also formalize governance for introducing new AI patterns, so the system can evolve without fragmenting.