# Lynt: Turning a Hackathon Prototype into a Real AI Résumé Product (GitHub Finish-Up-A-Thon) > Source: > Published: 2026-06-04 20:12:01+00:00 *This is a submission for the GitHub Finish-Up-A-Thon Challenge* **Lynt** is an AI-powered résumé and cover-letter builder with a visual editor, live print-accurate preview, one-click PDF export, and a public shareable page. The core idea is not just generating text with AI — but letting AI **apply structured edits directly into the document** while preserving layout, formatting, and history. Users can rewrite bullets, reorder sections, and tailor résumés to job descriptions with full undo support. The goal is to make editing a résumé feel faster and more reliable than copy-pasting between ChatGPT and a document editor. It started as a hackathon project called *ResumeForge*, originally just a markdown → PDF tool. Over time, it evolved into a full SaaS with authentication, cloud storage, document ingestion (PDF/DOCX/images), an AI editing system, and a reliable PDF generation pipeline. This project is currently in private beta while final stability and polish are being completed. Lynt began as a hackathon prototype built around a simple idea: markdown → PDF export. It worked, but it was not reliable enough for real-world use. The original version had clear limitations: It felt like a demo that “almost worked,” but not a product you could trust. The focus shifted from adding features to improving **reliability and correctness**. Instead of free-form AI output, the system was rebuilt around: A key shift was making the AI behave like an **editor**, not a generator. Every change is: When moved into real-world conditions, several issues surfaced: `DOMMatrix` issues)These were not feature bugs — they were production reliability issues. The final system is not defined by features, but by **predictability**: The biggest change was moving from “it works” to “it behaves reliably.” Copilot helped mainly with accelerating repetitive development: A Copilot coding agent was also used for a scoped feature (PR #21), which was reviewed and merged. However, the core system design — especially the AI editing contract, validation system, and document safety model — required manual architecture decisions. Lynt started as a hackathon experiment and evolved into a production-grade system focused on one goal: making AI-powered document editing reliable, deterministic, and safe. The Finish-Up-A-Thon provided the push to complete the hardest part of any product — the reliability layer that turns a demo into something real.