How LLMs changed job searching (for better, mostly)

For a long time, job hunting was a numbers game with a heavy time cost per application. You searched, you copy-pasted, you re-wrote the same bullets a hundred different ways. The volume that mattered was always blocked by the time per application.

LLMs collapsed that.

What changed - **Tailoring is now seconds, not hours.** Given a resume and a JD, an LLM can produce a tightly aligned resume version in 10 seconds. - **Match scoring is cheap.** Asking "how well does this resume fit this JD, 0-100?" costs less than a cent per pairing. - **Application logistics is automatable.** Browser agents can fill forms and submit.

What didn't change - **You still have to be the candidate.** No model can give you experience you don't have. - **Recruiters can detect bulk LLM output.** Generic AI-written cover letters are now an antipattern. - **ATS systems still exist.** They still tokenize. They still score.

Where the asymmetric advantage is The leverage isn't in writing prettier bullets. It's in **breadth + truthfulness**: - Apply to 50 roles that genuinely fit, each with a sharply tailored resume that doesn't invent things — instead of 10 roles with rewritten-by-hand resumes that take all weekend. - Spend the time you save on actually preparing for interviews.

That's the bet Projobly is making.