Case study
SPOT
Turning recruiting context into an AI-assisted operating system
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The problem, my contribution, outcomes, and strongest screens.
My role
Product design · Product strategy · AI interaction design
Product focus
A shared recruiting context that survives from intake through sourcing, evaluation, engagement, and reporting.
Overview
SPOT connects JD interpretation, intake, sourcing strategy, candidate evaluation, engagement, and stakeholder reporting around shared, inspectable context.
The problem
Recruiters work across documents, calls, ATS data, email, and presentations. Context decays at every handoff, criteria drift, evidence becomes hard to trace, and stakeholders lose confidence in progress.
What I drove
- Framed the service across recruiter, hiring manager, and AI assistant.
- Established a durable context model for the JD, agenda, questions, market, talent pool, and scorecard.
- Designed live capture that resolves questions and extracts evidence during intake.
What changed
- Connected previously fragmented recruiting activities through one inspectable context model.
- Made unresolved questions, evidence, decisions, and stakeholder-view states explicit across handoffs.
Impact
What the work was designed to move
Business impact
Turned fragmented recruiting activities into a connected operating system built around durable, reusable context.
Customer impact
Recruiters spend less effort rebuilding context between intake, sourcing, evaluation, outreach, and stakeholder reporting.
Revenue impact
Deepens product usage across the recruiting lifecycle, creating more opportunities for retention and account expansion.
Highlights evidence
4 essential screens from the final experience.
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