- 07-26Anthropic’s first technical PM on token maxing, the jagged edge, and living in the future | Dianne Penn94 分钟
- 00:00Introduction
- 02:31Early Anthropic days
- 08:55Big milestones
- 13:50Inside the exponential
- 20:02Token maxing
- 23:30Anthropic Labs and the incubation model
- 27:30How the research role works
- 31:35How to become a top researcher
- 35:18Frontier model safeguards
- 39:38Hiring in the AI era
- 44:16Building an eval set
- 47:48Evals vs PRDs
- 49:55The importance of hands-on leadership
- 52:46Finding joy in AI
- 58:10How Dianne uses Claude
- 01:01:05Avoiding overreliance on AI
- 01:03:50The constitution that makes Claude better
- 01:07:11AI writing and verification
- 01:11:40Where human brains will continue to be valuable
- 01:14:10Navigating AI with kids
- 01:16:26Alignment, the future of the PM role, and burnout
- 01:21:54Lightning round and final thoughts
- 07-19Why Netflix is betting on systems thinkers—not specialists—in the AI era | Elizabeth Stone (CPTO)72 分钟
- 00:00Introduction
- 02:25AI and role confusion: the storming phase before the forming phase
- 07:36How roles have changed in the past two and a half years
- 11:55Will functions survive? The case for craft specialism
- 13:26What Netflix is hiring more of—and less of
- 17:22Why systems thinking is the rising skill across every function
- 20:20Is the design process dead?
- 22:08Skills trending down
- 28:33AI fluency and Netflix’s career ladder overlay
- 31:00AI use cases beyond coding
- 35:12Netflix’s AI history
- 38:36Excellence as an operating system
- 41:11The pillars of the excellence OS
- 46:41The keeper’s test—and why it’s mostly a positive conversation
- 50:21Attracting top talent in the age of frontier AI labs
- 52:54Junior talent, craft mastery, and the mentorship question
- 56:25Where engineering goes in 5 to 10 years
- 59:45The future of entertainment: beyond film and TV
- 1:02:18AI in Hollywood: Netflix’s creator-enablement position
- 1:06:15Lightning round and final thoughts
- 07-12How tech workers actually feel about AI in 2026 | Annual AI sentiment survey (Noam Segal)96 分钟
- 00:00Introduction to Noam Segal
- 02:34About the survey: methodology and scope
- 06:04The core finding: AI has split the tech workforce in half
- 13:03The AI identity stance
- 14:40The four archetypes: Energized, Conflicted, Disoriented, Resentful
- 19:35Burnout is surging (and why shipping faster is making it worse)
- 22:53A glimmer of hope
- 24:55Layoff worries
- 29:15The career recommendation NPS score
- 36:45The ladder metaphor: rungs disappearing beneath our feet
- 45:14AI is making us faster, not better
- 52:53The #1 fear: being squeezed to do more for the same pay
- 55:55The emotional landscape and “smiling exhaustion”
- 01:01:02Designers and researchers: the most negative group two years running
- 01:06:27Who’s happiest
- 01:12:18Managers: the single biggest lever on well-being
- 01:18:47The industry is “chaotic”
- 01:24:53What employees and leaders can do right now
- 01:31:32AI guilt and closing thoughts
- 07-09Adam Mosseri: AI is a tailwind for authenticity68 分钟
- 00:00Introduction to Adam Mosseri
- 02:09How product teams are changing inside Meta
- 05:48Blurring roles and career anxiety
- 14:01Hiring traits that matter now
- 16:48How AI is resetting who succeeds at work
- 19:38How Meta thinks about token spend and AI costs
- 23:23Where human judgment still matters
- 25:56Why AI is not automatically great at strategy
- 30:36Why great product leaders are curators
- 34:23What Instagram’s algorithm actually knows about you
- 38:08Why chronological feeds often disappoint users
- 40:56Why AI content may be a tailwind for Instagram
- 43:42The future of AI and human content in the feed
- 48:00What Adam admires about other social platforms
- 52:05How he handles public criticism
- 56:31Lessons from the Instagram feed redesign backlash
- 01:00:21Adam’s biggest failure: Instagram on iPad
- 01:03:03His approach to kids, screens, and social media
- 01:06:56What Adam wants listeners to remember