1
Start with one bounded task that matches Jobscan's purpose: AI-assisted job application optimizer that compares resumes with job descriptions and provides ATS-oriented feedback. Candidates should use accurate work history and a real target role; recruiting teams should begin with a clearly defined job and structured evaluation criteria; coaching users should select a realistic conversation or interview scenario.
2
Use AI output as a draft or signal, not as unquestioned truth. Review generated resume language, outreach, interview notes, scores, or coaching suggestions against the underlying source. Do not add skills or achievements that the person does not have, and avoid allowing an automated score to become the sole basis for a consequential employment decision.
3
Test difficult cases: career changes, nontraditional experience, accents, accessibility needs, ambiguous answers, and role-specific terminology. For interview and conversation tools, inspect transcripts and listen to recordings where appropriate. For employer tools, audit whether similar candidates are treated consistently and document human review points.
4
Before scaling, confirm consent, retention, deletion controls, accessibility, auditability, regional employment requirements, and expected cost. Pricing is currently classified as freemium, but current plans should be confirmed with the provider.