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FurFinder is a robust backend-focused application designed to streamline the process of finding lost pets. Built entirely with Pure TypeScript, this project prioritizes logic, scalability, and clean code without the need for a frontend.
Key Technical Highlights:
Architectural Logic: Developed using a service-oriented architecture, organizing data paths for pets, reports, and matches.
Strict Typing: Leveraged TypeScript's power to ensure data integrity across models and services.
Scalable Structure: Implemented a modular folder system (services, models, decorators) for easy maintenance and team collaboration.
Data Management: Managed complex relationships between users and pet recovery reports through specialized logic handlers.
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5 months ago, a client came to me with a problem.
Not just "we need a B2B ordering portal."
More like – "we had a team build it. It didn't work. Can you start over?"
That's a different kind of brief.
I said yes, opened Figma, and started from scratch.
50+ unique screens for OXGroup, a full B2B dealer ordering platform. Every flow, every state, every edge case was designed properly before a single line of code was written.
Then the previous dev team was out. My team was in.
Backend devs. Frontend devs. Me, somehow, as the PM now.
That last part still feels new. I've spent years living in Figma. Coordinating a full dev team, keeping scope tight, making calls under pressure, different muscle entirely.
Turns out I don't hate it.
1 week of AI development later, we have a live, working demo. Built from my Figma file using Claude Code as the foundation.
4 weeks, we will have a live, fully functional platform we can give access to our customers.
We're not done. Automation testing is next, to catch everything before the client does. Then PostHog goes in, so we have real analytics from launch, not assumptions.
The lesson I keep coming back to:
Good design doesn't save a bad process. But a good process makes design unbreakable.
Got a product that didn't survive its first dev team?
💌 DM me. That's kind of our thing now.
Before: too many tabs, too many generic applications, no real tracking.
After: one clear AI-assisted job search system.
I build job search setups that help candidates apply smarter and stay organized.
What that can include:
AI prompt templates for tailoring resumes and cover letters
A structured tracker for jobs, follow-ups, and interview stages
Tool recommendations based on your target roles and workflow
A practical system for deciding which jobs are worth the effort
For people who are tired of guessing their way through the process.
Starting from $15
Typical delivery starts at 3 days
Also on Fiverr -> https://www.fiverr.com/s/GzRXKDa
I also turned part of this into an Apify actor -> https://apify.com/immense_greenery/linkedin-application-copilot
Use it if you want to score LinkedIn jobs yourself and generate application packs for review.
DM me if you want the full system built around your search.
I want to share a real piece of a client project that we are working on right now.
We used Claude to turn static Figma screens into a functional prototype with real inputs, validation states, keyboard interaction, component behavior, and flow logic.
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