Upfront bias: I've built a tool that tailors r sum s to postings and it launches here Tuesday. Which puts me on one side of a question I keep going back and forth on.
Against: if every application is AI-optimised, keyword matching becomes noise, recruiters get more volume, and the signal from "this person clearly wrote this for us" disappears.
ATS was already a keyword filter before AI arrived. People who knew that gamed it; people who didn't got screened out over formatting. Tooling just levels that.
Where I landed while building: it should only use what's genuinely in your experience, and it should tell you which lines it couldn't evidence. Mine flags them and makes you confirm before sending. I'm not certain that's enough.
I've spent 13 years in payments provider onboarding, certifications, the unglamorous ops side. Somewhere in my own job hunt I noticed I was spending more time maintaining the tracking spreadsheet than preparing for interviews. Role, link, date applied, did I tailor the CV, did I follow up. It rotted after about two weeks, every time.
So I built the thing I wanted instead. It launches here on the 9th.
Before it does I'd rather hear how other people actually run this: What are you using right now: spreadsheet, Notion, Trello, nothing? Which part do you stop doing first? For me it was follow-ups. And the honest one: did tracking ever actually get you an offer, or is it just anxiety management?
Twin-Seeker is an autonomous AI job search agent that manages your entire career pipeline—from 17-board discovery to ATS-tailored applications, STAR interview prep, and offer negotiation. Powered by Selfnode’s Identity Matrix and strict claim-frame verification, Twin-Seeker grounds every tailored resume and cover letter in your actual work history so the AI never fabricates skills, tools, or tenure.
