I'm a technical writer. I've spent twenty years designing systems that help people find what they need, act on it, and move on. So when my job search hit 200 applications and I still couldn't tell you what was actually active in my pipeline, it was a professional embarrassment as much as a practical problem.
So I built something.
The tool
It's a local Flask app that runs on my MacBook. Nothing in the cloud, no SaaS vendor with access to my data. It reads from the Excel tracker I already had and surfaces what I actually need to see.
The home screen shows my active pipeline as cards, unread mail from my job search inbox, and a next-steps checklist that writes back to the source file when I check things off. One click opens Apple Mail with a follow-up draft pre-addressed to the right person. Another pulls fresh pipeline status directly from the tracker. There's a full search across 415 application rows, pipeline notes, and company research in one box.
I also built a snapshot feature that pushes a mobile-friendly HTML file to iCloud. When a recruiter calls and I'm away from my desk, I have my full pipeline on my phone in about three seconds.
Why not just use Teal or Huntr
I tried them. They're fine for logging applications, but they don't connect to my email, my notes, or my contacts workflow. I also wanted to understand what I was looking at. Designing the data model for my own job search forced me to define what "active" actually means. (Stage at screening or above, or Result explicitly marked pending. Everything else is noise.)
Building the system is part of how I think through a problem. That's probably not true for everyone, but it's true for me.
What 415 applications taught me
There's a lot of signal in that data. I advance consistently in enterprise environments, regulated industries, and government contracting. Tech startups filter me out early, usually because I don't have Docs-as-Code experience. That's a gap I can close, but I wouldn't have seen it clearly without a system.
The skills transfer
Twenty years of technical documentation and knowledge management is, among other things, training in information architecture and workflow design. Knowing what to track, what to ignore, and where things live. Those skills don't stop mattering between jobs. That's when they matter most.
The code is on GitHub: github.com/davidgolden99/job-search