Job-Hunt Agent
Scores live job ads against my CV, then drafts the application.
What this shows: I can break a tedious manual workflow into steps an agent runs end to end, with hard filters and me making the final call.
A morning of scrolling job boards becomes a handful of roles actually worth applying to, each with a resume and cover letter already drafted for it.
One real run: 253 listings swept, 21 evaluated in depth against my CV. The top five all scored 4.3 or higher and the best hit 4.5. Every verdict came with a written report.
Hard filters beat clever scoring. Skip is a verdict too.
The pipeline, end to end
At a glance
- 44
- Company boards scanned
- 21
- Roles evaluated in one run
- 5
- Strong fits, scored 4.3+ of 5
- 253
- Listings tracked
How it works
- 1
Scan the boards
Pulls fresh listings from 44 company boards across five applicant-tracking systems, and filters to the roles I’m actually after.
- 2
Read the posting
Extracts the full job description from each link, even the awkward single-page application portals.
- 3
Verify it’s real
Checks the role is genuine and still live, not a stale repost or a ghost job, before I spend time on it.
- 4
Score the fit
Rates each role one to five against my real CV, and flags where I’m strong and where I’m short.
- 5
Tailor the CV
Builds an ATS-friendly CV for that exact role, pulling in the keywords the posting actually asks for.
- 6
Prepare to send
Drafts the application answers, then logs and tracks the role so nothing slips through.
Scored against my CV
Every listing gets a score out of five and a verdict. Only the top ones reach me:
Glean
AI Outcomes Manager, ANZ
EY-Parthenon
Senior Consultant, Decision Modelling
Heidi Health
Product Manager, Intelligence
ResMed
Lead Product Manager, Digital & AI
Problem
Job hunting is a volume game that rewards tailoring, and doing both by hand doesn't scale. I wanted the boring filtering and the first drafts handled, with me kept in the loop.
Approach
It sweeps 44 company boards across five applicant-tracking systems and filters to the roles I actually want. Each surviving posting is read in full and checked that it's genuine and still live, then scored one to five against my real CV. Strong matches get an ATS-friendly CV built for that exact role, the application answers are drafted and tracked, and I review and send.
Eval results
From a real run on 25–26 June 2026: 253 fresh listings swept from 44 company boards, narrowed to 21 roles worth a deep read. The top five all scored 4.3 or higher: an AI outcomes manager at 4.5, a decision-modelling consultant and a health-AI product manager at 4.4, and two more at 4.3. Each verdict arrives as a written report I review before anything is sent; I applied to one and have drafts ready for the rest. Next up: a proper eval of the scoring itself, the agent's ranking against my judgement.
What broke
The first scorer over-weighted keywords and loved any ad that said the word AI. Adding seniority and context checks pulled it back toward sane rankings.