I'm a talent intelligence nerd who builds things.

Not "builds things" like I dabble - I mean I understand problems by turning them into artifacts.

Command centers. Pipeline trackers. Boolean libraries. Search workflows. Heat maps. Playbooks.

If the information only lives in my head, it does not exist yet.

By day: Senior Talent Intelligence & Sourcing Strategist at Marvell Technology, focused on semiconductor and AI/ML engineering talent.
By reputation: 3x SourceCon Hackathon Champion.
By compulsion: I will absolutely turn your sourcing problem into a command center.

475 browser bookmarklets - searchable, filterable, one file, no extensions.

Built because I got tired of losing tools I loved.

A curated library of sourcing tools, Chrome extensions, research sites, and recruiter resources.

Built for modern talent teams.

A packed Chrome extension preserving LinkedIn scraping functionality from Instant Data Scraper v0.1.7.

For people who understand that useful data rarely arrives in a tidy export.

GitHub search operators, advanced search syntax, and recruiter-friendly techniques for finding technical talent.

Because GitHub is a talent database and most people do not know it yet.

Candidate-friendly technical interview prep resources, coding practice links, guides, and shareable references.

Built for the “do you have anything I can send them?” moment.

• I founded Sourcers Who Code because sourcers who build their own tools are a different kind of dangerous
• I believe sourcing is an intelligence problem, not a volume problem
• I care about OSINT, search strategy, talent mapping, and the weird little workflows that make research faster
• I use AI the way most people use Google, except I am also building with it
• Night owl. Music always on. Harvey nearby, supervising with emotional authority

• AI-assisted sourcing and research workflows
• Agentic research pipelines for talent intelligence
• Recruiter command centers and reusable knowledge systems
• Lightweight tools that make sourcing faster without requiring a giant tech stack
• Better ways to turn scattered market signals into actual hiring decisions