Into AI Safety Scaling AI Safety Through Mentorship w/ Dr. Ryan Kidd
12 snips
Feb 2, 2026 
Dr. Ryan Kidd, co-executive director of MATS and former physics PhD, shares how he scaled a premier AI safety talent pipeline. He defines the high-impact "amplifier" archetype and why it is under-served. He explains rigorous mentor selection, balancing funder priorities with research independence, and the value of geographic hubs plus remote access. Practical field-building strategies and program design are front and center.
AI Snips
Chapters
Transcript
Episode notes
Archetypes Clarify Hiring Needs
- MATS defines three talent archetypes: connectors, iterators, and amplifiers to structure recruitment and field-building.
- Each archetype requires different training and evaluation mechanisms.
Hire For Plural, Liminal, Relational Skills
- Look for amplifiers who are plural, liminal, and relational: jack-of-all-trades, technically fluent, and outcome-focused on others.
- Recruit people who can read papers and manage teams rather than pure ops or pure research profiles.
Amplifiers ≈ Technical Program Managers
- Amplifier roles resemble technical program managers more than generic ops; they need bounded technical experience to work with researchers.
- Effective amplifiers often come from research backgrounds or technical startup roles.