Operating Principles
How I run the work.
The convictions behind every search I take. They're the reason companies bring me in to do the hiring themselves — not to advise on it.
Quality of hire is the only scoreboard.
Speed and volume are worth watching, but they only ever matter in service of a single outcome, which is the right person in the right seat doing the work you actually hired them to do. That's the metric every search I take on is ultimately measured against.
Delivery over advice.
I get into the trenches and do the hiring itself — sourcing, screening, and closing — rather than handing over a deck or a framework from the sidelines and hoping it sticks. As far as I'm concerned the work only counts once the seat is actually filled.
Hire to the business plan.
Roles should map to the outcomes a company is chasing rather than to a headcount target, so before a single search opens I want the org design to connect who you're hiring to what the business is genuinely trying to achieve.
Intention over volume.
Top-of-funnel recruiting was never really about how many people you can reach; it's about reaching the right ones and giving them a real reason to care. In my experience precision consistently beats a bigger, noisier pipeline.
Augment, don't replace.
AI is best at taking the friction out of recruiting — sourcing, organizing, and spotting patterns — so that more of my time goes to the human work that actually moves a decision: building trust, reading motivation, and closing people who are understandably skeptical.
Build the engine, not just the hire.
The systems, automation, and sourcing workflows tend to outlast any single search, so I try to leave behind real recruiting infrastructure that keeps working long after the first hire has landed rather than a one-off result.
Trust is the close.
Candor with candidates and stakeholders is what ultimately moves a decision, and no tool builds trust, navigates a hard conversation, or truly understands a career choice on your behalf. That part stays stubbornly human.