Summary
Jeff Su synthesizes hiring research covering more than 4,000 hiring managers and nearly 2 million job applications — drawing on studies from MIT, Oxford, and multiple academic institutions — to identify five updated resume rules for an era where AI screens candidates before humans ever see a resume.
The five core findings: 87% of hiring managers say AI software reads simple text-based resumes more accurately than visual or graphic-heavy ones; tailored resumes produce 84% higher interview rates, but the most keyword-stuffed resumes actually receive 21% fewer interviews than moderately tailored ones; 59% of hiring managers view AI-assisted applications positively while 28% reject AI-heavy resumes showing no personal effort; resumes quantifying impact see 75% higher interview rates than those listing responsibilities only; and 60% of hiring managers want demonstrated AI skills, not just tool names listed under a skills section.
For each finding, Su translates the data into concrete action steps: format resumes as single-column selectable-text PDFs under 2.5MB; use keyword mapping against real experience rather than keyword stuffing; brain-dump raw facts before prompting AI to polish the wording; and prove AI proficiency through specific accomplishments. The video includes a two-step prompting workflow — capture facts first, then ask AI to strengthen language without altering the underlying claims — as a practical guard against the generic filler that modern hiring systems are increasingly calibrated to deprioritize.
📺 Source: Jeff Su · Published September 15, 2026
🏷️ Format: Deep Dive
