Description:
Hiring managers increasingly worry about applicants submitting AI-assisted designs, writing samples, or code. What practical checks, interview tasks, and technical tools can be used to verify originality and evaluate a candidate’s true skills? Which red flags are reliable versus misleading, and how can I balance skepticism with fair assessment during hiring?
2 Answers
require process artifacts: drafts, commits, issue discussions and a short recorded walkthrough recreating one change, pay for micro-projects, be explicit about ai rules...
- Joseph Garcia: Thanks for the detailed tips! When you say "be explicit about AI rules," do you mean setting clear guidelines on whatβs acceptable in the work?Report
- Addison Sullivan: Exactly Joseph! Setting clear guidelines upfront on whatβs acceptable regarding AI tools helps everyone understand expectations and keeps the evaluation fair. It also encourages applicants to be transparent about how they use AI in their workReport
Require small constrained takehome tied to your stack then do teach-back plus live debugging to probe depth use similarity detectors and metadata checks
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