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Screen job listings daily against resume and salary data
A laid-off job seeker runs an agent each morning that reviews LinkedIn, cross-references levels.fyi leveling and salary, and assesses fit to their resume.
Time saved
Not reported
Setup time
Not reported
Running cost
Not reported
Cost range
Not reported
Use case overview
A laid-off job seeker runs an agent each morning that reviews LinkedIn, cross-references levels.fyi leveling and salary, and assesses fit to their resume.
Reported experience
What they did
The commenter, laid off and job hunting, runs an agent every morning that reviews LinkedIn listings. It cross-references levels.fyi for each role's leveling and salary, then assesses fit against their resume. They apply their own judgement to the shortlist before deciding what to pursue.
How it went
The agent surfaces 5-10 possible positions a day, which human review cuts to 0-2, about 0.5 on average. Roughly 10% of applications get a reply, and the interview pipeline is full.
Worth knowing
The agent only narrows the field; the author's own judgement still removes most candidates, and the targeted approach, not volume, is credited for the response rate.
Example prompts
Each morning, open my [LinkedIn job search or saved search link] and review new listings posted in the last 24 hours for [target role and location]. For each one, check the level and typical pay for that company on levels.fyi, compare the role to my resume at [resume link or pasted text], and rate fit from 1 to 5 with a one-line reason. Finish with a ranked shortlist of the top 5, flag any under [minimum salary], and do not apply to or message anyone.
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