Emil Michael on Recruiting Technical Talent for Government

A defense official describes short-term service and personal outreach.

EMEmil MichaelInvité · Uber
Chaîne
No Priors: AI, Machine Learning, Tech, & Startups
Publié
16 janv. 2026
Vidéo
1:27
Lecture
1 min
Original
anglais
Ouvrir sur YouTube
En faisant défiler, la vidéo se réduit en bas à droite et continue. Les sous-titres suivent votre langue de lecture.
Langue de lectureDisponible en 2 langues
Cet article n’est pas encore disponible en français ; il s’affiche dans l’original en anglais.
RÉSUMÉ

En 30 secondes

Michael discusses technical recruits, a proposed graduate service pathway and his recruiting approach.

  1. 1RecruitingMichael seeks technical staff.
  2. 2ServiceHe describes a proposed two-year pathway.
  3. 3Personal outreachHe contacts potential candidates directly.

À retenir

  1. He values technical builders.
  2. He describes a proposed two-year service pathway.
  3. He recruits through personal outreach.
TEXTE INTÉGRAL

Lire le texte remanié, chapitre par chapitre

Transcription seule
01

Technical recruits

US defense official Emil Michael describes efforts to recruit technically skilled people for government service.

US defense official Emil Michael describes efforts to recruit technically skilled people for government service.

Michael discusses staff brought into government through DOGE and says some were later deployed to other technical projects. This is his account of the program.

He says he values a builder mentality and argues that technically skilled recruits can attract more colleagues.

02

A service pathway

Michael describes a proposed two-year service pathway for recent graduates, presenting technical work as another form of public service.

Michael describes a proposed two-year service pathway for recent graduates, presenting technical work as another form of public service.

He also describes personally contacting people between jobs and asking colleagues for potential candidates.

Sur la même chaîne

38:06EN
No Priors: AI, Machine Learning, Tech, & Startups· 29 oct. 2026Podcast · 3 voixServal’s Jake Stauch on coding agents for enterprise ITInvité : Jake Stauch · Anime : Sarah Guo, Elad GilStauch explains why Serval is challenging ServiceNow, how it approaches permissions and approvals, and why background agents remain difficult to deploy safely.IA en entrepriseAgents de codeWorkflow automation+2
1:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 27 oct. 2026PodcastGeorge Kurtz on How AI May Change CyberattacksInvité : George KurtzThe CrowdStrike CEO describes his assessment of evolving threats.
39:23EN
No Priors: AI, Machine Learning, Tech, & Startups· 15 oct. 2026Podcast · 2 voixThe Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of CybersecurityAnime : Sarah Guo, Elad GilOpenAI's president explains why solving open math problems is a proof point for science, how proactive agents change product form, and why security spending must exceed software spending.SécuritéAI securitySécurité et gouvernance+3
1:04EN
No Priors: AI, Machine Learning, Tech, & Startups· 14 oct. 2026PodcastWalter Goodwin on the Slow Steps in Chip DesignInvité : Walter GoodwinA chip founder explains why automation does not remove every computational bottleneck.SemiconductorsAI cost & performance
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 9 oct. 2026Podcast · 2 voix10,000 GB300s for Four Weeks: Reflection’s Open-Model LedgerAnime : Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.Open source et communautéOpen-weight modelsReinforcement Learning+3
0:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 8 oct. 2026PodcastMichael Lee on Rethinking Organizations with AIInvité : Michael LeeA business leader argues that the opportunity goes beyond faster tasks.