Clear Match Talent
AI-Powered Recruitment Nurturing Tool
The Problem
The team had a plan: spend 3+ months building custom AI infrastructure before a single recruiter could use the product. I thought we were solving the wrong problem first.
I ran a one-week test using existing AI tools. It worked. We scrapped the custom build, redirected the roadmap, and recovered 3 months of development time.
My Role
I sat between founders and the CTO, translating vision into feature specs and technical constraints back into roadmap decisions.
What I Built
With the CTO, I mapped the backend database to support future AI capabilities and designed the candidate priority matrix: a scoring algorithm built on 6 profile archetypes that surfaced the right candidates based on relationship strength, job match, engagement, and timing.
AI Recommended Outreach
Surfaces a pre-drafted, personalized message the moment a job signal is detected. The recruiter reviews, edits if needed, and sends. Eliminates the time gap between signal and outreach.
Candidate Profile Card
Shows relationship scores, status, and contact history in one view. Recruiters can assess fit and urgency without digging through notes or spreadsheets.
Interaction History
A chronological feed of every touchpoint with the candidate, each tagged by priority level. Gives the recruiter instant context before reaching out.
The Conflict
The team hit a wall. The CTO had a plan: spend 3+ months building custom AI infrastructure before a single recruiter could touch the product. The founders wanted to move fast but didn't have the technical background to push back. So the plan stood, mostly by default.
I wasn't convinced we needed to build from scratch. My read was that existing AI tools could automate the nurturing workflow just as effectively, without months of backend work. But I had no proof, and a technical argument alone wasn't going to move anyone.
So instead of debating it, I ran a test to validate my hypothesis.
My Experiment
One week. Off-the-shelf AI tools. I used Claude to simulate the full candidate nurturing workflow through prompt engineering, testing whether we could automate outreach drafts without any custom backend work.
The Results
90%+ draft acceptance rate.
The AI-generated messages were good enough that recruiters barely edited them. The experiment proved we didn't need custom infrastructure.
We scrapped the original plan, redirected the roadmap, and recovered 3 months of development time.
The Product
Two clicks. That's all it takes for a recruiter to know who to reach out to, what to say, and why today is the right moment.
The dashboard surfaces candidates by urgency. One click opens their profile with full relationship scores, interaction history, and an AI-drafted message already written. The recruiter reviews, hits send, and a follow-up reminder is set automatically.
No manual triage. No writing from scratch. No lost leads.
My one-week test proved the entire workflow could run on existing AI tools. The product is what that experiment made possible.
Key Takeaway
The best design decision I made on this project wasn't a UI choice. It was knowing when to challenge a technical assumption before the team spent months building the wrong thing.