Project Case Study
MyApplio
An AI-assisted job search workspace that connects resumes, applications, and interviews in one pipeline. Next.js 16 and Supabase, with Gemini-powered resume import, job discovery, and cover letter drafting, plus a Chrome extension that captures postings in one click.
View Live Project →Overview
MyApplio is an AI-assisted job search workspace. The positioning is stated on the landing page as "Resume to offer · AI assisted", and the promise underneath it is "Resumes, applications, interviews. Nothing falls through."
Most job seekers run their search across a spreadsheet, a resume file, an email inbox, and a browser full of tabs. Each tool holds one stage and knows nothing about the others. MyApplio's premise is that the stages are the product: a captured posting becomes an application, an application pulls from a resume, a resume gets tailored per role, and an interview inherits the context of both.
The Problem
Postings disappear before they are recorded, or get pasted into a spreadsheet without their details
Resumes fork into a dozen near-identical files with no source of truth
Cover letters restart from a blank page for every application
Deadlines and follow-ups depend on memory
Nothing connects a stalled application back to the material that produced it
Information Architecture
The dashboard is organized around the entities of a real search rather than a single flat list:
Capture: ai-job-search for discovery, plus the Chrome extension for one-click clipping
Pipeline: applications, companies, roles, people, events, notes, links
Material: resume, cv, cover-letter, with match scoring a resume against a posting
Preparation: interview-prep, review, ready, goals
Public surface: resume-directory, resume-search, and shareable public resume pages
What This Means for the Business
Private, protected accounts: Each user's data is locked to that user at the database level, and even the public demo account is read-only.
AI costs that stay under control: Routine extraction runs on a lighter AI model and writing tasks on a stronger one, every call is metered against credits, and usage limits stop abuse.
Resume import you can trust: An uploaded PDF resume is read in two passes, a first draft and then a check against the original, so users fix less by hand.
Reminders at the right time: Notifications are scheduled around each user's own time zone.
Secure billing and a hardened site: Payment notifications are verified before they are acted on, and the site is protected against common web attacks.
The Chrome Extension
MyApplio Job Clipper is a Manifest V3 extension with a service worker and a side panel. It scrapes LinkedIn, Indeed, Glassdoor, Workday and others into MyApplio as draft applications. The extraction logic alone is roughly 82 KB of site-specific code, because every board structures its postings differently. Drafts, not finished records: capture should be one click and cost the user no decisions.
What This Case Study Demonstrates
Designing a multi-entity product where the connections between stages are the value
Running production AI economically by matching model tier to task, metering every call, and capping inputs
Building on Supabase with serious RLS, 193 migrations, and database-native scheduling
Shipping a browser extension and a web app as one coherent product
Making security and cost boundaries explicit in code rather than in a runbook
Live: https://myapplio.com/
Role: Solo delivery (product → schema/RLS → AI pipeline → billing → extension → SEO)
