AI Resume Generators — What Works and What Doesn't

AI resume tools are everywhere. ChatGPT, dedicated resume builders, browser extensions—they all promise to help. But do they deliver?

What doesn't work

Generic prompts — "Write me a resume for a software engineer" produces generic output. No hiring manager wants to read that.

Single-shot generation — One prompt in, one document out. There's no job-specific context, no requirement extraction, no mapping of your experience to what they want.

Template shuffling — Some tools just rearrange your existing content into a prettier layout. That's not tailoring.

Keyword stuffing — Stuffing keywords without real experience behind them gets flagged. ATS and humans both notice.

What works

Job-specific context — The tool needs the actual job description. Requirements, keywords, company context. Without it, you get generic output.

Profile-to-job mapping — Your real experience, skills, and achievements mapped to what the employer wants. Not invented, matched.

Structured pipeline — Extract requirements → match your profile → generate tailored content. Each step improves output quality.

Human review — The best tools produce a strong draft you can refine. Not a black box that replaces your judgment.

What to look for in an AI resume tool

• Does it use the job posting as input?
• Does it reference your actual experience (not invent it)?
• Can you refine the output with natural language?
• Is the output consistent across resume, cover letter, and pitch?

The Profica approach

We built Profica around a simple principle: one profile, infinite applications. You maintain one career profile. Each job gets a tailored output generated from that profile—not from thin air. Paste any job posting; get a matched resume, cover letter, and pitch in under 2 minutes.

See the difference yourself.