
I run recruiting at a 90-person startup without a recruiting team. AI lets me handle what used to require 2-3 full-time recruiters while keeping the human touch where it matters most.

AI sourcing pipeline filling engineering roles 56% faster than average
Vantage needed to hire 12 engineers in Q1 with no recruiting agency budget. As the sole recruiter, I was spending 80% of my time sourcing and only 20% on high-value activities like closing.
Fill 11 of 12 roles in 23 days vs 52-day industry average with 38% response
Created a Claude workflow that analyzes job requirements, identifies ideal candidate profiles on LinkedIn/GitHub, and drafts personalized outreach. Notion tracks every candidate through the pipeline. Zapier automates follow-ups and scheduling.
Filled 11 of 12 roles in Q1 with an average time-to-fill of 23 days (vs. 52-day industry average). Outreach response rate was 38% vs. previous 14%.

Personalized onboarding system boosting 90-day retention to 94%
New hires were falling through the cracks in the first two weeks. IT setup was late, buddy assignments were inconsistent, and managers had no structured onboarding checklist. Three of the last ten hires left within 90 days.
Improve 90-day retention from 78% to 94% with personalized onboarding system
Built a Notion-based onboarding system with automated task creation via Zapier. Claude generates personalized onboarding plans based on role, team, and manager preferences. Automated check-in surveys at day 7, 30, and 60 flag at-risk hires early.
90-day retention improved from 78% to 94%, and new hire time-to-productivity (measured by first PR or first client call) dropped by 40%.

AI-designed interview scorecards cutting mis-hire rate by 60%
Interview process was inconsistent—each interviewer asked different questions, scoring was subjective, and there was no calibration. Mis-hire rate was approximately 1 in 5.
Reduce mis-hire rate from 20% to 8% with structured interview system
Used Claude to design role-specific interview scorecards with behavioral and technical questions mapped to competencies. Built a Notion database where interviewers log structured feedback. Claude generates debrief summaries highlighting consensus and red flags before hiring committee meetings.
Mis-hire rate dropped from approximately 20% to approximately 8% over 6 months. Interview-to-offer ratio improved from 8:1 to 4:1, meaning fewer interviews needed per hire.

AI comp benchmarking tool replacing $40K in consultant fees
Vantage was relying on expensive one-off salary surveys and recruiter gut feel for compensation. Offers were either too low (losing candidates) or too high (budget pressure), and we had no real-time market data.
Improve offer acceptance from 62% to 81% with AI compensation benchmarking tool
Aggregated data from Levels.fyi, Glassdoor, Pave, and AngelList into a Notion database. Claude analyzes the data by role, location, seniority, and company stage to generate recommended ranges. Updates quarterly with new market data via Zapier scrapes.
Offer acceptance rate improved from 62% to 81%, and the tool replaced the $40K/year we were spending on external compensation consultants.