The latest articles on DEV Community by TheDataKnight99 (@tdk99). https://dev.to/tdk99 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4114497%2Fa6a9483e-60e0-4018-a99a-ace92090f197.jpg https://dev.to/tdk99 en TheDataKnight99 Mon, 07 Sep 2026 19:06:54 +0000 https://dev.to/tdk99/i-got-tired-of-losing-good-jobs-to-timing-so-i-built-a-pipeline-that-scores-linkedin-listings-5p8 https://dev.to/tdk99/i-got-tired-of-losing-good-jobs-to-timing-so-i-built-a-pipeline-that-scores-linkedin-listings-5p8 <p>A job posting gets 200+ applicants in 48 hours. By the time LinkedIn's daily digest hits your inbox, the window is already closing.</p> <p>I kept finding great matches days after they were posted. So I built SnapplAI: it scrapes fresh LinkedIn listings, sends each one to Gemini to score it against your CV, and emails you only the top matches, before the crowd even sees them.</p> <p><strong>How it works</strong></p> <p>Four steps, one pandas DataFrame, no frameworks:</p> <p>Scrape — fresh listings from LinkedIn based on your filters<br> Summarize — Gemini extracts structured fields as JSON<br> Analyze — each listing scored against your CV (chain-of-thought enforced: reasoning before judgment)<br> Deliver — top matches emailed to your inbox</p> <p>Runs locally, via Docker, or as a scheduled GitHub Actions cron. Full setup takes 5 minutes.</p> <p><strong>Why no framework</strong></p> <p>I wanted a clean data pipeline with LLM calls where they matter, not an agent framework. Python orchestrates, AI evaluates. Each Gemini call retries with exponential backoff and falls back through a model chain, so a throttled API doesn't crash the run.</p> <p><strong>Try it</strong></p> <p>👉 <a href="https://dev.tourl">github.com/TDK-99/SnapplAI</a></p> <p>MIT-licensed. Issues, PRs, and forks are welcome.</p> python ai opensource automation