Case Study
An AI-powered product designed to bring the modern job search into a single workflow.
Visit ApplyGridThe modern job search isn't a single task—it's an ongoing workflow spread across dozens of disconnected tools. Existing platforms help people find jobs or track applications, but none manage the entire workflow from discovery to networking to interview preparation. ApplyGrid is my attempt to bring that workflow into a single, AI-powered product.
The modern job search has become increasingly fragmented. Finding opportunities, tailoring resumes, tracking applications, preparing for interviews, networking, and managing recruiter conversations all happen across different platforms, spreadsheets, and AI tools.
While researching existing job search products, I realized that each platform solved a single part of the process well, but none managed the entire workflow. As a result, job seekers spend as much time managing their search as they do actually searching for jobs.
ApplyGrid was designed to bring that workflow into a single, AI-powered platform.
Rather than starting with a fixed set of requirements, ApplyGrid evolved through continuous iteration. As I evaluated existing products and tested new ideas, I found that many features users considered essential already existed—but they were scattered across separate applications and disconnected workflows.
Throughout the design process, I continually simplified the experience by questioning each step of the user's journey. Features that added unnecessary complexity were removed, workflows were consolidated, and AI became increasingly responsible for automating repetitive tasks rather than requiring additional user input.
Each iteration reinforced the same product principle: the goal wasn't to build more features—it was to reduce the amount of work required to manage a successful job search.
ApplyGrid was designed using an iterative, AI-assisted product development process that allowed ideas to move quickly from concept to working software.
I designed the user experience in Figma, rapidly prototyped new workflows using AI development tools, and continuously refined the product based on testing and feedback. Rather than treating design and development as separate phases, I used AI to quickly validate ideas, explore alternative user experiences, and evolve the product through rapid iteration.
This approach significantly shortened the feedback loop between identifying a problem, designing a solution, and testing it, allowing the product to evolve much faster than a traditional development process.
Start with what the user already has.
Rather than asking users to manually configure every aspect of their job search, ApplyGrid begins by understanding who they are. Users upload their resume, connect their email, and define the type of opportunities they're looking for. AI uses this information to personalize the entire experience from day one.
Relevant opportunities—not endless searching.
Instead of requiring users to constantly search multiple job boards, ApplyGrid continuously surfaces opportunities that align with their background and career goals. The focus is on helping users spend less time searching and more time evaluating the right opportunities.
Manage the entire workflow in one place.
The pipeline brings together applications, recruiter conversations, interviews, follow-ups, and next steps into a single workspace. Rather than relying on spreadsheets or disconnected tools, users can understand the status of every opportunity from one screen.
AI where it's actually useful.
Rather than existing as a standalone chatbot, AI is integrated directly into the workflow. It helps tailor resumes, prepare for interviews, summarize job postings, draft networking messages, and reduce repetitive work without requiring users to constantly switch contexts.
Reduce manual work.
ApplyGrid continuously synchronizes job search activity, monitors connected accounts, updates application status, and surfaces relevant information automatically. The goal is to reduce the administrative burden of job searching so users can focus on finding the right opportunity.
Building ApplyGrid fundamentally changed how I think about product management.
Before AI-assisted development, product managers often had to rely on lengthy design and engineering cycles before validating an idea. Today, it's possible to move from identifying a problem to testing a working solution in a matter of days. That has completely changed the way I approach product development.
More importantly, ApplyGrid reinforced something I've believed throughout my career: product managers create the most value when they stay closely connected to the entire product lifecycle. Understanding users, designing intuitive experiences, rapidly validating ideas, and continuously improving the product shouldn't be separate activities—they're all part of building great products.