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: 27 roles evaluated in depth, the top ten all scored 4.6 or higher against my CV, and four hit 4.8. 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
- 30
- Sources watched
- 27
- Roles evaluated in one run
- 4
- Top fits, scored 4.8 out of 5
- 191
- Listings tracked so far
How it works
- 1
Scan the boards
Pulls fresh listings from 30 tracked sources, company boards plus the big job sites, 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:
AMP
AI Product Owner
Heidi Health
Product Manager, Intelligence
EY
Decision Modelling, AI & Decision Analytics
Glean
AI Outcomes Manager, ANZ
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 30 tracked sources, company boards plus the big job sites, 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 11 June 2026: 27 roles evaluated, the top ten all scored 4.6 or higher, and four hit 4.8: an AI product owner, a product manager in health AI, a decision-analytics consulting role, and an AI outcomes manager. Each verdict arrives as a written report I review before anything is sent. 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.