PODCAST · Lenny's Podcast

2026 年 4 月节目

6 期 · 6 期带分节

  • 04-26Snapchat CEO: Why distribution has become the most important moat | Evan Spiegel
    1. 00:00Introduction to Evan Spiegel
    2. 02:28Why consumer social products are so hard to build
    3. 04:31How Snapchat cracked distribution with close friends, not network size
    4. 05:50Why distribution is the new moat in the AI era
    5. 08:39Snapchat’s innovation track record (and why software isn’t a moat)
    6. 11:39Why Snap is betting on two of the hardest businesses: consumer social and hardwa
    7. 16:00Specs use cases
    8. 17:56The innovation process
    9. 21:34The velocity of design work at Snapchat
    10. 25:07Why Evan says you must talk to customers
    11. 26:06The origin story of Stories
    12. 28:25How screenshot detection saved early Snapchat
    13. 31:03Why they waited to hire PMs—and what role they play now
    14. 34:41How AI is shifting the designer-PM-engineer triad
    15. 36:10Design as an intentional bottleneck for product cohesion
    16. 37:24Why staying close to customers matters for any leader
    17. 39:39What Evan looks for when hiring designers
    18. 41:57How to develop young design talent
    19. 44:16Designers shipping code with AI—and the guardrails needed at scale
    20. 47:20Using jobs-to-be-done to organize AI transformation
    21. 48:50How the CEO job has changed over 15 years
    22. 51:30Learning to communicate
    23. 54:08Why this year is Snapchat’s “crucible moment”
    24. 56:22Being the “middle child” in tech
    25. 57:51Screen-time philosophy with four kids (ages 2 to 15)
    26. 1:01:08AI Corner
    27. 1:04:02Contrarian Corner
    28. 1:06:04Lightning round and final thoughts
  • 04-23How Anthropic’s product team moves faster than anyone else | Cat Wu (Head of Product, Claude Code)
    1. 00:00Introduction to Cat Wu
    2. 01:29Working with Boris Cherny
    3. 04:29What Anthropic looks for when hiring PMs
    4. 06:18How to help your teams move fast
    5. 08:58How PRDs and roadmaps have evolved at Anthropic
    6. 10:28The Mythos model and Anthropic’s shipping velocity
    7. 11:54What happened with the Claude Code source code leak
    8. 12:53Integrating with OpenClaw
    9. 14:19How the PM team is structured at Anthropic
    10. 15:42How engineer and PM roles are merging
    11. 17:54Why product taste is the most valuable skill
    12. 20:10Where human brains will continue to be useful
    13. 22:23How to stay sane in constant chaos
    14. 24:16What gets sacrificed when you ship so fast
    15. 27:47The /powerup command
    16. 28:32Why Anthropic has been so successful
    17. 32:28When to use Claude Code vs. Desktop vs. Cowork
    18. 35:58Tips for getting started with Cowork
    19. 38:44Demo: Using Cowork to build slide decks overnight
    20. 41:48Cat’s PM tech stack and internal tools
    21. 46:47Which teams use the most tokens
    22. 51:15The emerging skills PMs need for AI companies
    23. 55:00Why building evals is underappreciated
    24. 58:44Why Claude’s character and personality matter so much
    25. 1:00:44How new models force product changes
    26. 1:05:11The vision for Claude Code and Cowork
    27. 1:07:22Advice for thriving in an AI-driven world
    28. 1:09:18Why 95% automation isn’t good enough
    29. 1:11:58Build apps you use every day, not prototypes
    30. 1:13:41The divide between AI skeptics and believers
    31. 1:15:19Lightning round
  • 04-19Why half of product managers are in trouble | Nikhyl Singhal (Meta, Google)
    1. 00:00Introduction to Nikhyl Singhal
    2. 02:25The big picture: what’s changing for product managers
    3. 10:00Are product leaders doing better than 2-3 years ago?
    4. 11:44What will change in the next couple of years
    5. 14:23How companies are changing the way they build products
    6. 15:51What “judgment” really means for PMs
    7. 17:46Why there won’t be any more bad software
    8. 20:25The skills you need to be effective today
    9. 23:31Why there are more PM roles than ever
    10. 24:27The builder versus information-mover divide
    11. 30:14The non-builder problem
    12. 30:53Should PMs code?
    13. 34:15Why experienced leaders still matter
    14. 35:44The diversity setback nobody’s talking about
    15. 37:21Why your brand doesn’t matter as much anymore
    16. 39:54How valued skills are flipping upside down
    17. 40:49Why change is so hard for humans
    18. 43:53The “equal disappointment” algorithm
    19. 46:39You must cross the threshold
    20. 48:37This chaos will settle
    21. 53:19Finding your moment of joy
    22. 58:50Nikhyl’s AI stack and what he’s building
    23. 1:00:53The obsolescence mindset
    24. 1:05:24Specific advice for PMs right now
    25. 1:08:58The four jobs that will exist in the future
    26. 1:11:59Why alignment is changing (but not disappearing)
    27. 1:15:40How engineering is changing even more than PM
    28. 1:17:04The surprising design plateau
    29. 1:18:49Finding optimism in the chaos
    30. 1:21:12Lightning round
  • 04-12Hard truths about building in the AI era | Keith Rabois (Khosla Ventures)
    1. 00:00Introduction to Keith Rabois
    2. 01:59Why Keith hasn’t used a computer since 2010
    3. 04:52The team you build is the company you build
    4. 07:40How Keith learned to identify talent at PayPal
    5. 10:05Tactics for getting better at hiring
    6. 15:31The barrels vs. ammunition framework
    7. 18:52What makes someone a barrel
    8. 22:36How to attract the best talent
    9. 26:18Building companies on undiscovered talent
    10. 27:53Why better performance requires more pressure
    11. 32:36Career advice in the age of AI
    12. 35:14The future of the product triad
    13. 41:03Why design and code are merging
    14. 49:35What practicing law taught Keith about entrepreneurship
    15. 51:22Contrarian takes on customer feedback
    16. 1:02:33Identifying great AI opportunities
    17. 1:05:13Advice for evaluating statrups
    18. 1:12:36Criticizing in public vs. private
    19. 1:15:05Failure corner
    20. 1:17:29Lightning round
  • 04-05Head of Growth (Anthropic): “Claude is growing itself at this point” | Amol Avasare
    1. 00:00Introduction to Amol and Anthropic’s growth
    2. 03:15The story of cold emailing Mike Krieger to get the job
    3. 08:28What it’s like leading growth at the fastest-growing company ever
    4. 10:46What the growth team actually does at Anthropic
    5. 12:16The concept of “success disasters”
    6. 13:55Why activation is the biggest challenge in AI products
    7. 18:05Improving Mercury’s onboarding experience
    8. 20:57The importance of adding the right kind of friction
    9. 25:10Anthropic’s org structure
    10. 27:06Why Anthropic focuses on big bets over micro-optimizations
    11. 33:34Automating growth experiments with Claude (CASH)
    12. 38:20How AI is starting to identify what experiments to run
    13. 41:07The future of PM, engineering, and design roles
    14. 47:19Why you might need more PMs as engineers get more productive
    15. 51:13How Amol uses AI to prototype ideas and skip PRDs
    16. 58:10Amol’s morning routine: AI analyzes 20 to 25 charts automatically
    17. 1:03:31Getting coaching from an AI version of your manager
    18. 1:06:27How Anthropic’s focus on coding and B2B drove their success
    19. 1:12:10Balancing growth with AI safety as a core mission
    20. 1:18:09Advice for thriving in an AI-first future
    21. 1:22:53Anthropic’s culture and the “notebook channels” on Slack
    22. 1:35:12Failure corner: Shutting down his startup after raising money
    23. 1:38:25The traumatic brain injury that changed everything
    24. 1:46:49Lightning round
  • 04-02An AI state of the union: We’ve passed the inflection point, dark factories are coming, and automation timelines | Simon Willison
    1. 00:00Introduction to Simon Willison
    2. 02:40The November 2025 inflection point
    3. 08:01What’s possible now with AI coding
    4. 10:42Vibe coding vs. agentic engineering
    5. 13:57The dark-factory pattern
    6. 20:41Where bottlenecks have shifted
    7. 23:36Where human brains will continue to be valuable
    8. 25:32Defending of software engineers
    9. 29:12Why experienced engineers get better results
    10. 30:48Advice for avoiding the permanent underclass
    11. 33:52Leaning into AI to amplify your skills
    12. 35:12Why Simon says he’s working harder than ever
    13. 37:23The market for pre-2022 human-written code
    14. 40:01Prediction: 50% of engineers writing 95% AI code by the end of 2026
    15. 44:34The impact of cheap code
    16. 48:27Simon’s AI stack
    17. 54:08Using AI for research
    18. 55:12The pelican-riding-a-bicycle benchmark
    19. 59:01The inherent ridiculousness of AI
    20. 1:00:52Hoarding things you know how to do
    21. 1:08:21Red/green TDD pattern for better AI code
    22. 1:14:43Starting projects with good templates
    23. 1:16:31The lethal trifecta and prompt injection
    24. 1:21:53Why 97% effectiveness is a failing grade
    25. 1:25:19The normalization of deviance
    26. 1:28:32OpenClaw: the security nightmare everyone is looking past
    27. 1:34:22What’s next for Simon
    28. 1:36:47Zero-deliverable consulting
    29. 1:38:05Good news about Kakapo parrots