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AI for Job Search

Skill Gap Analysis

Job descriptions are wish lists, and that is what makes them so bad for self-assessment. Fourteen bullets, half of them written by someone who copied last year’s posting, and no signal about which two actually decide the hire. You scan the list, notice three things you have never touched, and quietly decide not to apply. Or you go the other way and spend four months on a certification that no interviewer will ever ask about.

Skynet reads across many postings instead of one, which is where the pattern becomes visible. What appears in every listing is the real requirement. What appears once is noise. Against that, it maps what you already have — including the experience you would not have thought to count — and tells you what is genuinely missing.

How it works

step 01

Name the role you want

Not your next job — the one after that, if you like. The agent works from a target, not from your current title.

step 02

Let it read the market

It gathers real postings for that role and finds what actually recurs: the tools, the scope, the years, the things mentioned every single time.

step 03

Compare against your history

Your background is already in memory. The agent maps it against the pattern and splits the result into three: what you have, what you have but describe badly, and what is genuinely absent.

step 04

Get a plan for the real gaps

For each true gap, a specific way to close it and an honest estimate of how long. Some gaps are a weekend. Some are a job change. The agent says which.

Build it from a prompt

Point it at the destination and ask what stands between you and it.

The useful part is often the second list — the things you have already done but never named properly. That gap closes in an afternoon of rewriting. For the rest, you get a plan aimed at what hiring managers actually check.

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