TechDebtGPT

Company: techdebtgpt.com

Role: Lead Product Designer

Industry: AI / Developer Tools / SaaS

AI-Powered Technical Debt Management

Overview

TechDebtGPT is an AI-powered SaaS platform that helps engineering teams understand technical debt, team performance, and project health.The platform translates complex code-level signals into clear insights for developers, team leads, and CTOs, helping teams make better decisions about code quality and delivery.

My Contributions

• As the sole Product Designer, I led the end-to-end UX, from ideation and wireframing to visual design and user research, working closely with the founding team and engineers to shape the product from concept to beta launch.
• Collaborated with founders, product manager, front-end & back-end engineers

+46%

User Satisfaction Increase (post-beta)

1.5x

Faster Team Insights (vs. manual tracking)

New Revenue Streams (from standalone team metrics product)

The Challenge

Engineering teams often struggle to measure and communicate the impact of technical debt on delivery, quality, and team health. Existing tools are either too technical for leadership or too surface-level for developers, leaving teams without a clear way to translate engineering data into actionable insights.
The goal was to design a product that could combine repository data, pull request analysis, and team performance metrics into a single, intuitive dashboard.

Process

Discovery & Research:

Conducted stakeholder interviews with developers and engineering managers to understand how teams track technical debt and project health.
Analyzed competing tools such as GitHub Copilot, Code Climate, and SonarQube.

Ideation & Wireframing:

Defined key product modules including PR analysis, risk tracking, team performance, and contribution insights.
Mapped core user flows around answering three key questions: team health, project risk, and contributor impact.

Visual Design & Prototyping:

Designed a dark-mode-first dashboard optimized for engineering workflows.
Created data visualizations including leaderboards, risk indicators, and team performance charts.

Testing & Iteration:

Conducted usability tests with engineering teams to refine chart readability, data density, and AI insights.

Post-beta testing showed a 46% improvement in perceived product usefulness.

Key Features Delivered

• AI-powered project insights: Transforms repository data into clear team performance insights.
• PR and code analysis: Analyzes pull requests to detect risk patterns and development bottlenecks.
• Team performance dashboard: Provides a leaderboard and contribution breakdown across team members.
• Risk monitoring system: Highlights high-risk code areas and unresolved issues.
• Project health overview: Combines sprint activity, PR trends, and technical debt indicators.

Outcome & Impact

• Successfully launched MVP for early-stage engineering teams
• Reduced manual tracking of technical metrics across multiple tools
• Improved user satisfaction by 46% post-beta
• Positioned TechDebtGPT as an AI-powered insights platform for engineering teams