Building TailorSwan: My AI Resume Tailoring Platform

An AI Resume Builder

I was desperately looking for jobs and I got fed up with Google Sheets. Even with all the intelligence we have around us, I felt dumb. No progress with job applications. No interest in maintaining a Google Sheet.

You might ask: if you could not even maintain a Google Sheet, how did you build a web app for resume building?

I built it hoping I would apply faster. Instead of doing 4 to 5 applications a day by hand, I wanted something that could take the slow parts off my plate. Finding a job post. Reading the JD. Checking if they support visas. Seeing if it matches my resume. Then tuning it based on my experience and rewriting it so ATS would actually pick it up.

To get past that 4 to 5 a day ceiling, I built a web app that helps a candidate fast-track resume tuning. It comes purely from their existing experience. Every resume a candidate tunes is based on the source, their existing resume. That is the true authentic source.

What this tool does is take every problem I ran into and handle it.

Problem	How I solve it
Doing only 4 to 5 applications a day by hand. Highest I ever hit was 10.	A web app that fast-tracks resume tuning so you are not stuck rewriting everything yourself.
Finding a job post. If you look across every job board and try to avoid fake ones, 20 was about the max. My capacity was 5 a day, so 15 of those sat until tomorrow.	20 a day keeps you in the front row. With the speed this app gives you, you can actually work those 20 instead of watching 15 go to next day.
Reading the JD. About 5 minutes by hand.	The LLM scrapes and extracts the JD.
Understanding the JD. Another 5 minutes by hand.	Contrast the JD with the existing resume.
Seeing if it matches my resume. About 3 minutes by hand.	The LLM scores it using a contrast score rubric.
Tuning and rewriting the resume to line up with the JD, based on my actual experience. 20 to 35 minutes.	The LLM handles it in 30 seconds to 1 minute. Review takes about 5 minutes.