AI Workflows &
Rapid Product Design.
Architecting the shift from static B2B catalogs to agentic, intent-driven ecosystems — and solving the trust governance gap that prevents most enterprise AI from actually shipping.
Role
Principal Product Designer
Context
B2B Wholesale / Industrial
Tech Stack
Figma + Claude 3.5 Sonnet / O1
Methodology
AI-Augmented Prototyping
The Vision Statement
THE STRATEGIC THESIS.
Universal Syntax
Language is the architect of everything. LLMs have revealed that Music, Math, Science, and even the stars are all structured Design Systems. By treating these disparate syntaxes as a singular grammar, we bridge the "Trust Gap" in enterprise AI.
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The New Rails
For agents to move beyond conversation and into action, they require a trustless medium. Blockchain provides the "Train Tracks." Decentralized ledgers allow AI to transact, negotiate, and settle value securely on behalf of users.
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Trust Governance
Design’s role has shifted. We are no longer just styling interfaces; we are designing the governance of automated economic flows. It is a fundamental shift from designing for "clicks" to designing for "trust."
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Architecture & Strategy
THE INTELLIGENT FRONT DOOR.
My focus over the last year has been architecting the evolution of a B2B platform from a traditional static catalog into a fully agentic ecosystem. The core challenge in enterprise AI isn't simply generating content; it's solving the "Trust Gap" — where flashy demos often fail to meet the rigorous consistency required by industrial buyers.
Live Proof
This Portfolio Site
The portfolio you're reading right now was designed, iterated, and deployed using this exact workflow — built entirely with Agentic AI agents, custom skills, and automated pipelines. From architecture decisions to component-level copy, every layer was AI-augmented. The methodology isn't theoretical. It's live.
Discovery Layer
Coveo AI
UX Simulation.
Comping complex search intents into interactive prototypes to simulate personalized, entitlement-aware results directly at the search level.
Strategy Layer
Agentic
UX Blueprints.
Mapping the transition from static decision trees to intent-driven workflows, ensuring AI responses maintain industrial-grade precision.
Conversational UX
Digital
CSM Agents.
Interactive prototypes demonstrating how chatbots act as the "front door" for wholesale buyers to automate order tracking and inquiries.
UI / Design Layer
Rapid UI
Generation.
Utilising Generative AI (Figma Make, Claude) to drastically compress the design-to-code cycle—including the Doral Tires Agentic CMS—and iteratively prototype new dashboard states.
Personal Initiatives & Experimentation
AGENTIC AI LABS.
Beyond enterprise platforms, I actively develop agentic workflows and Generative AI applications to explore the boundaries of interaction design—bridging holistic store CMS ecosystems with predictive sentiment agents.
Store Associate OS
The 'Sentinel'
Initiative.
Exploration into a headset CMS and 'Store Sentinel' ecosystem providing a holistic overview of associate support—stress/tone patterns, predictive hardware health, and real-time safety triggers (e.g., 'Aisle 6 clean-up' or 'send-support' for lone workers).
Holographic Retail
Computer Vision
& Shelf Tracking.
Real-time inventory auditing through holographic shelf mapping and camera management to identify mismatched items and potential loss-prevention patterns.
Agentic CMS Build
Doral Tires.
Designing and building a mobile-first agentic CMS for Doral Tires, with Figma Wireframes parsed directly by AI agents to accelerate design-to-code build cycles.
Consumer Mobile App
In DevelopmentADHD Focus — App Store Launch.
Designing and building a personal consumer mobile app. This ADHD-focused product aims to improve upon existing management tools through a 6-12 month rapid release model. The entire lifecycle—from Figma Wireframe parsing to AI-driven marketing—serves as a learning-focused, revenue-generating venture.
Deep Dive Feature
The Death of the Keyword.
Intent-Based Discovery replacing manual part-number memorization.
Enterprise search has traditionally forced the user to think like a database. We fundamentally shifted the paradigm from deterministic queries to Intent-Based Discovery.
Conversational AI Discovery
Intent-Based Search UI
Decision Logic
Agentic vs Deterministic Trade-offs.
Visualizing the governance model for automated fulfillment. A matrix overlaying risk tolerance (cost, lead time) against agent autonomy — proving the "Messy Middle" logic behind intent-driven procurement.
Strategic governance required to bridge the trust gap in enterprise fulfillment systems.
Value Realization
Wholesale Workflow Automation.
The agentic ecosystem wasn't just about faster design—it was about Case Deflection & Conversion. By funneling B2B buyers through the Conversational CSM layer, we automated previously manual operations: enabling self-service bulk quote generation, instant order tracking over natural language, and serving "Next-Best-Action" recommendations directly to sales reps during live negotiations.
Core Focus
B2B Friction
Resolving complex wholesale workflows
Sales Enablement
Next-Best-Action
Real-time rep guidance during negotiations
Customer Success
Case Deflection
L1 support automated via CSM agent layer
Velocity
Days → Hours
Figma-to-code cycle via AI-augmented pipeline
Velocity metric based on this portfolio — designed, built, and deployed in a single AI-augmented sprint using the agentic workflow described on this page.
The Future is Generative
2026 Future Outlook.
The next leap for B2B frameworks isn't just about finding products—it's about systems that negotiate and adapt autonomously.
Adaptive Ecosystems
Generative UI for B2B.
The death of the static dashboard. We are moving towards interfaces that rebuild themselves in real time based on a buyer's specific contract terms, seasonal purchasing patterns, and local inventory volatility.
Machine-to-Machine Commerce
Autonomous Procurement.
We are preparing for a future where UI is completely bypassed — a buyer's bespoke AI agent negotiates pricing, terms, and delivery logistics directly and autonomously with the platform's selling agent.
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