Pastplied

Pastplied – A Smart Job Application Tracking System

Pastplied is a modern web application I built while actively searching for a job. During that process, I ran into a surprisingly common problem: job postings started to look familiar, but I couldn’t remember if I had already applied. There were no emails, no confirmations, and no reliable way to verify whether an application had already been sent.

That moment of confusion became the motivation behind Pastplied — a tool designed to track job applications clearly, reliably, and without friction, so every application is documented and easy to revisit.

Why I Built Pastplied

When applying to many roles across different platforms, it’s easy to lose track. Job boards don’t share data, confirmation emails get buried, and job titles often repeat across companies. I found myself hesitating before applying, wondering:

• Did I already apply to this position?
• When did I apply, if at all?
• Which companies have I already contacted?

Pastplied solves this by giving me a single source of truth for my job search — a dashboard where every application is stored, searchable, and timestamped.

What the Project Does

Pastplied is a job application tracking system that lets users save and manage job applications with minimal manual input. Instead of filling out long forms, users simply paste a job listing URL, and the app takes care of the rest.

Using AI-powered extraction, Pastplied automatically detects:

• Job title
• Company name
• Job location

Each application is then stored with an application date and can be edited, updated, or removed at any time.

The goal was to make tracking applications faster than applying itself.

Smart Job Import With AI

The most distinctive feature of Pastplied is its smart job import. I wanted the process to feel effortless, so I integrated AI-based extraction that reads job listings directly from their URLs.

Behind the scenes:

• The job listing page is fetched and parsed
• Relevant content is extracted using server-side HTML parsing
• Google’s Generative AI processes the data and identifies key job details

This approach reduces human error, speeds up the workflow, and removes the friction of manual data entry during an already stressful job search.

Clean Dashboard for Job Search Clarity

Once applications are added, they appear in a clean, minimal dashboard designed for clarity. From there, users can:

• See all applications at a glance
• Track when each application was submitted
• Edit details as needed
• Remove outdated or irrelevant applications

The interface is fully responsive and supports dark mode, making it comfortable to use during long job search sessions.

How It’s Built

Pastplied is built as a modern full-stack application using the same production-grade tools I’d use in a real-world product.

Frontend

The frontend is built with Next.js (App Router) and React, using TypeScript for type safety. Styling is handled with Tailwind CSS and shadcn/ui, allowing for a clean, accessible design system with reusable components.

Form handling is implemented with React Hook Form and Zod, ensuring fast performance and strong validation.

Backend & Authentication

The backend is powered by Convex, providing real-time database updates and serverless functions without unnecessary complexity. Clerk handles authentication, keeping user data private and securely scoped to each account.

AI & Data Processing

For job data extraction, I combined Cheerio for HTML parsing with Google Generative AI to intelligently interpret job listings across different websites, regardless of layout or structure.

What I Learned From This Project

Building Pastplied helped me explore:

• AI-assisted data extraction
• Real-time full-stack architecture
• Secure authentication flows
• Designing UX for high-friction workflows
• Building tools that prioritize speed and clarity

Most importantly, it reinforced how valuable small, focused tools can be when they solve a real problem at exactly the right moment.

Final Thoughts

Pastplied is a project born directly from experience. It’s a practical solution to a problem many job seekers face but rarely track properly. By combining automation, AI, and a simple interface, the app turns job application tracking into something effortless and reliable.

This project showcases my ability to identify real user pain points and turn them into polished, production-ready applications.