The workflow, in plain English
Before: You browse LinkedIn jobs. You read each listing and mentally map it against your skills. “Do I have 3+ years Python? Yes. Kubernetes? Sort of.” This takes hours.
After: Every job listing on the page has a colored badge: green (90%+ match), yellow (70-89%), red (below 70%). You click a yellow one. Below the description: “You match 8/10 requirements. Gap: Terraform certification. Emphasize your AWS experience.” The listing became a career advisor.
Why traditional tools can’t: No job board offers resume matching on the listing page itself. AI resume tools require you to leave the site and upload to a separate platform.
Step-by-step
- Open a job listing (e.g., LinkedIn, company ATS, aggregator).
- Provide your resume (or point to an open tab/document) and ask for a match score.
- Review gaps and decide whether to apply, save, or skip.
- If applying, generate tailored bullets and talking points.
Example prompts to try
- “Compare this job to my resume and give me a score + gap list.”
- “Rewrite my summary bullet to match the top 3 requirements.”
- “Tell me what to highlight in an interview for this role.”
Tips for better results
- Be specific about what you want injected into the page (buttons, filters, a panel, a summary, etc.).
- If the page has multiple sections, tell dassi exactly what to focus on (e.g., “the transactions table” or “the diff for file X”).
- Prefer safe workflows first: draft, summarize, label, and prepare — then take actions (submit, purchase) only after review.