
Sign up to save your podcasts
Or


Stephen Gubenia, Head of Detection Engineering for Threat Response for Cisco Meraki, shares his evolution from managing overwhelming alert volumes as a one-person security team to architecting sophisticated automated systems that handle everything from enrichment to containment.
Stephen discusses the organizational changes needed for successful AI adoption, including top-down buy-in and proper training programs that help team members understand AI as a productivity multiplier rather than a job threat.
The conversation also explores Stephen’s practical "crawl, walk, run" methodology for responsibly implementing AI agents, the critical importance of maintaining human oversight through auditable workflows, and how security teams can transition from reactive alert management to strategic agent supervision.
Topics discussed:
Listen to more episodes:
Apple
Spotify
YouTube
Website
By Panther Labs5
1111 ratings
Stephen Gubenia, Head of Detection Engineering for Threat Response for Cisco Meraki, shares his evolution from managing overwhelming alert volumes as a one-person security team to architecting sophisticated automated systems that handle everything from enrichment to containment.
Stephen discusses the organizational changes needed for successful AI adoption, including top-down buy-in and proper training programs that help team members understand AI as a productivity multiplier rather than a job threat.
The conversation also explores Stephen’s practical "crawl, walk, run" methodology for responsibly implementing AI agents, the critical importance of maintaining human oversight through auditable workflows, and how security teams can transition from reactive alert management to strategic agent supervision.
Topics discussed:
Listen to more episodes:
Apple
Spotify
YouTube
Website

374 Listeners

1,535 Listeners

653 Listeners

33 Listeners

12,225 Listeners

318 Listeners

8,039 Listeners

9,927 Listeners

511 Listeners

138 Listeners

40 Listeners

44 Listeners

1,654 Listeners

1,427 Listeners

798 Listeners