Hack Your Job Hunt: My New Resume Optimizer

Ali Mobini | Dec 2, 2025 min read

I want to share how I’ve been using this access to build something actually useful for the job hunt.

I’ve built a specific “Gem” designed to take the pain out of tailoring resume and motivation letter to each job application. This is Specifically for those of us who live and die by LaTeX.

What is a “Gem”?

If you’re new to the ecosystem, “Gem” is essentially a fancy marketing term for a wrapped system prompt. Instead of starting every chat session by explaining who you are and what you need the AI to do, you build a Gem. You give it a persistent set of instructions, context, and behavioral constraints.

It’s the difference between typing “Act as a senior editor and fix this text” every single time, and just having a button labeled “Editor” that already knows your style guide.

The Resume & Motivation Letter Optimizer

The job market is brutal right now. We all know the advice: “Tailor your resume to every single job description.” We also know the reality: rewriting your resume and cover letter five times a day is exhausting.

I built a Gem specifically to automate this grunt work without sacrificing quality.

How It Works

This tool is built for the LaTeX crowd. If you don’t know LaTeX yet, take this as your sign to learn it. It is the gold standard for clean, professional documentation, and it makes version control meaningful.

Here is the workflow:

  1. Input: You feed the Gem your resume.tex, your motivation_letter.tex, your raw project/work history data, and the specific Job Description.
  2. Processing: The Gem analyzes the requirements of the job against your actual experience.
  3. Output: It generates optimized versions of your .tex files.

The Guardrails

I spent a significant amount of time tuning the system prompt to avoid the biggest issue with AI career tools: lying.

  • No Hallucinations: It is strictly instructed to optimize based only on the experience you provide. It will not invent a skill you don’t have just to match a keyword.
  • Structure Preservation: It doesn’t try to reinvent your design. It replaces the content within your existing LaTeX code, so your formatting remains intact.

A Note on the Output

While the goal is automation, never trust an LLM blindly. The output is usually 90-95% of the way there, but it may require a few manual tweaks to get the spacing or phrasing exactly right. Think of it as a first draft that gets you to the finish line much faster, rather than a magic “submit” button.

The Takeaway

Finding an internship or a full-time role is incredibly draining right now. The mental load of customizing every single application is enough to make anyone burn out.

Hopefully, this workflow helps you reclaim some of that time. Grab the student deal before December 9th, build your Gem, and good luck with the applications.

Link to the Gem: CV & cover letter optimizer .

Written by Ali Mobini, a developer exploring system architecture, embedded systems, and intelligent automation.