RecruitLingo

This candidate's resume is full of AI terms. Help me work out what they've actually done before the screening call. {{Paste the resume}} THE ROLE: {{Job Title}}, {{level}} WHAT THE ROLE NEEDS: {{e.g. shipped LLM features used by real customers, model training at scale, evaluation and monitoring}} For each AI claim on the resume: 1. Sort it into one of: shipped to real users; internal tool or prototype; course, hackathon or side project; or can't tell. Quote the line that put it there. 2. For anything that reads as production, what should also be there if it's real: users or traffic, cost, latency, how quality was measured, what went wrong. Point out which of these are missing. 3. Two questions per claim that someone who built it answers with specifics straight away, and someone who followed a tutorial can't. Focus on decisions and failures, not definitions. 4. What a strong answer sounds like and what a weak one sounds like, in plain language I can judge on the call without knowing the technology. Then: 5. Tell me whether the underlying engineering (APIs, data handling, testing, deployment) looks solid, since that usually matters more than which AI framework they named. 6. What I should not count against them: side projects and courses are legitimate evidence of interest and learning, just not of production experience. Don't invent concerns. If a claim is specific and checkable, say it looks credible.