Innovation happens when people are free to think, experiment, and speculate.

Matt Ridley

Rapid Prototyping

The emergence of Agentic-AI is transforming how digital products are imagined, designed, and built. Instead of relying solely on traditional design cycles, designers and product teams can now rapidly explore ideas by creating AI-powered agents that simulate workflows, decision-making, and user interactions.

Using a vibe-coding approach, I leverage AI tools to quickly translate concepts into working prototypes—often in hours rather than weeks. This allows ideas to move from hypothesis to interactive validation much faster, enabling teams to test experiences, evaluate agent behaviors, and explore new product opportunities early in the design process.

By combining product thinking, design strategy, and AI-assisted development, these prototypes serve as living experiments that help validate concepts, refine user experiences, and uncover entirely new product directions.

This approach represents a new era of product design—where designers are not only shaping interfaces, but orchestrating intelligent systems and AI agents that actively participate in the user experience.

Apex Strategic Partners - Project Pipeline Dashboard

Rapid Prototype Development using Figma Make

Project Overview

A sophisticated enterprise project pipeline management system for consulting firms, designed to provide real-time visibility into sales opportunities, resource allocation, hiring needs, and delivery capacity. Built entirely as a functional prototype using Figma Make to validate concepts and user workflows before committing to full-scale development.

The "Vibe Coding" Approach

This prototype exemplifies the power of rapid iteration and conceptual validation through what I call "vibe coding" - the process of quickly building functional, interactive prototypes that capture the essence and user experience of a final product without the overhead of production infrastructure.

Using Figma Make, I transformed an enterprise consulting workflow concept into a fully interactive dashboard in hours rather than weeks, including:

  • 6 prospective project opportunities with complete lifecycle tracking

  • 12 delivered projects showcasing historical performance

  • Multi-criteria filtering system (stage, confidence level, account owner, search)

  • Deliverables timelines with status tracking and dependencies

  • Resource capacity planning across 10+ role types

  • Hiring pipeline with 19+ open positions and salary ranges

  • Sales team collaboration features with phase tracking

  • Revenue analytics comparing $13.2M pipeline against $27.2M delivered

Why Prototype Before Building?

1. Validate Assumptions Early

Before writing production code, I tested critical assumptions about:

  • Information hierarchy (What do sales leaders need to see first?)

  • Filter combinations (How do teams actually want to slice opportunity data?)

  • Navigation patterns (Top-level cards vs. drill-down details)

  • Data relationships (Pipeline stages, deliverables, resource allocation)

2. Rapid Iteration Without Technical Debt

Made major structural changes in minutes that would take days in production:

  • Reorganized project card layouts based on visual hierarchy

  • Added account owner visibility after realizing it was buried

  • Restructured filtering logic when initial approach felt clunky

  • Experimented with different comparison visualizations for pipeline vs. delivered revenue

3. Stakeholder Alignment

A working prototype enables:

  • Immediate feedback from end users (sales teams, executives)

  • Concrete discussions about features vs. abstract requirements docs

  • Visual alignment on design aesthetic and information density

  • Priority setting based on actually using the interface

4. Technical Discovery

Prototyping revealed implementation considerations:

  • Complex state management needs (filtering across multiple dimensions)

  • Data modeling requirements (project phases, deliverables, hiring needs)

  • Real-time calculation performance (weighted pipeline values, resource utilization)

  • Edge cases (empty states, missing account owners, filter combinations)

5. Accelerated Development

Once the prototype is validated:

  • Frontend developers have a pixel-perfect reference with working interactions

  • Backend teams understand exact API requirements from prototype data flows

  • QA engineers can write test cases from prototype user journeys

  • Product managers have concrete scope to estimate and plan sprints

Design Highlights

  • Editorial Aesthetic: High-contrast serif headings (Cormorant Garamond) paired with clean sans-serif UI (DM Sans), creating a sophisticated consulting brand feel

  • Asymmetrical Grid Layouts: Dynamic card sizing that breaks monotony and guides attention

  • Progressive Disclosure: Key info visible at card level, full details available on drill-down

  • Real-time Filtering: Multi-dimensional filtering with visual feedback and active filter badges

  • Status-Driven UI: Color-coded stages, progress indicators, and at-risk flags throughout

Technologies Demonstrated

  • React + TypeScript patterns for complex state management

  • Framer Motion for sophisticated scroll animations and staggered reveals

  • Recharts for data visualization and comparisons

  • React Router for multi-page navigation architecture

  • Advanced filtering algorithms with memoization for performance

Outcome

This prototype serves as both a design validation tool and a development blueprint. It proves the concept works, identifies gaps in requirements, and provides a complete specification for engineering teams - all achieved in a fraction of the time traditional development would require.

By prototyping first with Figma Make, I de-risk the project, align stakeholders, and ensure that when development begins, the team is building the right solution, not just a solution.

Time to Prototype: ~4 hours
Equivalent Development Time: 2-3 weeks
Value: Validated concept, identified 8+ UX improvements, aligned 3 stakeholder groups before writing production code

💡 Try it. Interact with the app below to see how it works.

IdeaProof - AI-based Business Idea Validator

A mobile-first web application that helps entrepreneurs validate their startup ideas through comprehensive AI-powered analysis. Users input their business concept, target audience, and market details to receive instant feedback from four specialized AI agents: Market Research, Competitor Analysis, Monetization Strategy, and MVP Recommendations.

Key features include:

  • Multi-agent AI validation system with detailed scoring and risk assessment

  • Dark/light theme toggle with smooth animations

  • Local storage persistence for saving and managing validated ideas

  • Edit and re-validate functionality for iterative refinement

  • Responsive design optimized for mobile devices

  • Clean, modern UI with custom animated logo

Tech Stack: React, TypeScript, Tailwind CSS, React Router, Motion (Framer Motion), Lucide React Icons, localStorage API

Built with a focus on user experience, the app features a sticky bottom navigation, intuitive form flow, and color-coded scoring system to help founders make data-driven decisions about their business ideas before investing time and resources.

💡 Try it. Interact with the app below to see how it works.