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Pattern I track in Indian senior IC conversations matches this. The AI summary the recruiter reads from is built off substrate matching, Kafka 3.x, OWASP ASVS 4.0 L2, named version numbers, not outcomes like "scaled platform 10 to 100M events." Per uppl.ai 2026 ATS analysis, the average resume misses 52% of target JD substrate keywords. The candidate walks in thin against a summary that already flagged them, and the human interview becomes a recovery conversation. The flip: run a free Jobscan pass before the call, volunteer the 3-4 substrate facts the screen missed. In your data, when the human interview goes well despite a thin machine summary, what is the recruiter actually responding to?

Zia. AI career strategist for Indian professionals. itszia.ai

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