Emil Michael on Recruiting Technical Talent for Government

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

EMEmil MichaelGast · Uber
Kanal
No Priors: AI, Machine Learning, Tech, & Startups
Veröffentlicht
16. Jan. 2026
Video
1:27
Lesezeit
1 Min.
Original
Englisch
Auf YouTube öffnen
Beim Scrollen schrumpft das Video in die rechte untere Ecke und läuft weiter. Untertitel folgen Ihrer Lesesprache.
LesespracheIn 2 Sprachen verfügbar
Diesen Artikel gibt es noch nicht auf Deutsch, daher wird das Original (Englisch) angezeigt.
ZUSAMMENFASSUNG

In 30 Sekunden

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.

Das Wichtigste

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

Den bearbeiteten Text nach Kapiteln lesen

Nur das Transkript
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.

Mehr aus diesem Kanal

38:06EN
No Priors: AI, Machine Learning, Tech, & Startups· 29. Okt. 2026Podcast · 3 StimmenServal’s Jake Stauch on coding agents for enterprise ITGast: Jake Stauch · Moderation: 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.Enterprise-KICoding-AgentenWorkflow automation+2
1:07EN
No Priors: AI, Machine Learning, Tech, & Startups· 27. Okt. 2026PodcastGeorge Kurtz on How AI May Change CyberattacksGast: George KurtzThe CrowdStrike CEO describes his assessment of evolving threats.
39:23EN
No Priors: AI, Machine Learning, Tech, & Startups· 15. Okt. 2026Podcast · 2 StimmenThe Defenders' Window: Greg Brockman on AI-Generated Knowledge, Drug Discovery, and the New Physics of CybersecurityModeration: 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.SicherheitAI securitySicherheit & Governance+3
1:04EN
No Priors: AI, Machine Learning, Tech, & Startups· 14. Okt. 2026PodcastWalter Goodwin on the Slow Steps in Chip DesignGast: 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. Okt. 2026Podcast · 2 Stimmen10,000 GB300s for Four Weeks: Reflection’s Open-Model LedgerModeration: 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 & CommunityOpen-weight modelsReinforcement Learning+3
0:39EN
No Priors: AI, Machine Learning, Tech, & Startups· 8. Okt. 2026PodcastMichael Lee on Rethinking Organizations with AIGast: Michael LeeA business leader argues that the opportunity goes beyond faster tasks.