FitResume: Tailored Resumes with LLMs

Tailoring resumes and cover letters for each job application is one of the most time-consuming aspects of job searching, yet it's also one of the most important. Generic, one-size-fits-all applications are easily spotted by recruiters and rarely lead to interviews. Effective job applications require careful analysis of job postings, identification of key requirements, and customization of application materials to highlight relevant experience and skills. For active job seekers applying to multiple positions, this customization process can consume hours per application, significantly limiting the number of positions they can apply to.

The challenge is compounded by the need to maintain authenticity and accuracy. While it's important to highlight relevant experience, job seekers must ensure that all claims are truthful and verifiable. Exaggerations or inaccuracies can be discovered during background checks or interviews, damaging credibility and career prospects. Additionally, applications must sound natural and reflect the candidate's voice, not read like they were generated by a template or AI system.

Large Language Models (LLMs) offer tremendous potential to assist with resume and cover letter customization, but they come with significant risks. Generic LLM prompts often produce generic, templated content that doesn't reflect the candidate's actual experience or the specific job requirements. LLMs can also "hallucinate"—generating plausible-sounding but inaccurate information that could mislead recruiters or create problems during verification. Without proper grounding, LLM-generated content may not accurately reflect the candidate's qualifications or may fail to address specific job requirements.

FitResume's Tailored Resumes with LLMs addresses these challenges by using a grounded prompting approach that ensures accuracy, relevance, and authenticity. The system doesn't just ask an LLM to "write a resume"—it provides the LLM with specific, verifiable information about the job posting and the candidate's experience, then uses carefully crafted prompts that require the LLM to cite sources and base all content on provided information.

The system begins by analyzing the job posting to extract key requirements, responsibilities, and qualifications. It identifies important keywords, required skills, and preferred experience levels. This analysis ensures that the tailored content addresses what the employer is actually looking for, not just generic job description language.

Next, the system reviews the candidate's work history, achievements, and qualifications. It identifies experiences and skills that match the job requirements, quantifiable achievements that demonstrate impact, and relevant projects or accomplishments. This matching process ensures that the tailored content highlights the most relevant aspects of the candidate's background.

The LLM then generates tailored resume sections and cover letter content using grounded prompts that explicitly require the model to cite the job posting and the candidate's history. These prompts prevent hallucinations by forcing the LLM to base all content on provided information rather than generating generic or fabricated details. The system also includes source citations in the generated content, allowing candidates to verify accuracy and understand the reasoning behind specific recommendations.

Quality control is built into the process. The system flags content that lacks source citations, highlights potentially generic language, and suggests areas where the candidate's actual experience could be better emphasized. This ensures that generated content is not just tailored, but also authentic and accurate.

By combining LLM capabilities with grounded prompting and source citation, FitResume enables job seekers to create high-quality, tailored applications quickly while maintaining accuracy, authenticity, and verifiability. This approach transforms resume customization from a time-consuming manual process into an efficient, AI-assisted workflow that produces better results.