The Skip Podcast

What do the hottest companies look for when they hire a CPO or head of product? I put the question to three people who sit in these searches every week: Lindsay Keith of Daversa, Andrew Abramson of Fusion Talent, and Caroline Horn of a16z. We had a similar conversation in January 2026, and the market has moved a lot since. A year ago, founders wanted a narrow profile: a former founder, hands-on, willing to work 9-9-6 hours. That profile hasn't gone away fully, but as companies mature past their first head of product, founders increasingly know what they want. The winning profile is the executive builder: someone senior enough to run the function and still close enough to the work to build.
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Key topics:
• Why founders want senior leaders who never stopped building
• Why "go be an IC" stopped applying to executive searches about six months ago
• Staying "close to the metal": how companies test whether an executive is really hands-on
• Why working sessions with the team have replaced the take-home presentation
• The attributes that matter more than the title
• Why technical depth is now a must-have for product leaders
• In-office expectations, and why 9-9-6 went quiet but didn't disappear
• Comp as a pressure cooker
• Why AI fluency will be table stakes by next summer, and what will differentiate candidates instead
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Timestamps
00:00 Introduction
02:28 Meet our guests from Daversa, Fusion Talent, and a16z
04:58 How much has demand for product leaders grown this year?
06:14 The two types of companies hiring a CPO right now
09:34 Why founders under-hired and are now up-leveling the role
12:15 How companies assess whether an executive is really hands-on
14:25 Working sessions have shifted from presenting to building together
18:00 The profile of candidates closing searches in the last 90 days
20:50 Why later-stage companies want builders who can attract AI-pilled PMs
23:30 Should executives found a company to boost their careers?
25:00 The attributes that matter
27:10 Do AI companies need leaders with AI experience?
31:04 Building AI reps outside your day job
33:08 In-office expectations and whether 9-9-6 has cooled
35:15 Can executives with families keep up with the pace?
39:12 How to assess a company's culture before you join
44:25 How to evaluate a paper-rich offer at a high valuation
49:05 Competing with Meta, Google, and the labs on comp
51:58 Predictions for next summer: researchers, physical AI, and technical depth
56:18 Why AI fluency will stop differentiating candidates
57:24 Domain depth as the next differentiator
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Referenced:
• a16z
• Abridge
• Airbnb
• Airtable
• Anthropic
• Atoms
• Autodesk
• Bending Spoons
• ChatGPT
• Claude
• Cursor
• Datadog
• Daversa
• Decagon
• DoorDash
• Figma
• Fusion Talent
• Google
• Gusto
• Harvey
• Meta
• Miro
• Nash
• OpenAI
• Sharp Performance
• Sierra
• Square
• Substack
• Travis Kalanick
• Uber
• Vercel
• xAI
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Brought to you by:
• Chargebee—Billing and monetization infrastructure for the AI era
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Where to find Nikhyl
• Twitter/X
• LinkedIn
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Where to find Lindsay
• LinkedIn
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Where to find Andrew
• LinkedIn
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Where to find Caroline
• LinkedIn
–
Join The Skip
• Skip Coach
• Skip Community
–
Find The Skip
• Website
• Substack
• YouTube
• Spotify
• Apple Podcasts
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Don't forget to subscribe to The Skip to hear me coach you through timely career lessons. Access exclusive sessions from 100+ top product leaders at skip.coach. If you're interested in joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at nikhyl@skip.community


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit theskip.substack.com

In this episode, Tulsee Doshi, who leads product for Google's Gemini models, joins me for the fourth conversation in the "Inside PM" series. Tulsee has spent eleven years at Google, moving through Search and YouTube before taking on product for the Gemini family and Google's video, image, and audio models. We get into how her team avoids building a boring product, why their blend of platform work and lab work feels like a new kind of product management, and what she looks for in the PMs she thinks will thrive in that environment.
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Key topics:
• Why customer requests get weighed against research the customers can't see
• Why stack-ranking every request would leave you with a boring product
• The 20 prompts trick for turning a vague ask into a great eval
• How to know a model is ready to ship without waiting a year
• Reading a model's "vibes," and why Simon Tokumine's gut check carries real weight
• Prototyping features that don't work yet on purpose
• Why "technical" on her team means thorough, not a computer science degree
• The Nano Banana moment that "fuels all of the other chaos"
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Timestamps:
00:00 Introduction
03:28 Welcoming Tulsee Doshi to break down how Google builds Gemini
04:10 Eleven years at Google, from Search and YouTube to leading Gemini
06:20 Why the model team works like an engine maker for a garage of cars
08:40 Why stack-ranking every request would produce "a boring product"
11:25 "Nothing can replace a great eval": evals as the new PRD
14:36 The "20 prompts" trick for turning a vague ask into a great eval
18:44 How to know a model is ready to ship without waiting a year
22:40 "Vibes": why Simon Tokumine's gut check on a model carries real weight
27:20 Why speed beats trying to build the perfect product today
29:35 Prototyping features that "don't quite work yet," on purpose
31:05 The 60/20/20 rule for building against a model that keeps improving
33:58 The five traits she looks for in a research PM
40:35 Why "technical" on her team means thorough, not a CS degree
44:25 How AI tools are changing what Google's PMs do all day
48:30 Why Google's I/O still matters as a forcing function
52:50 The vibe inside Gemini right now: hype and chaos at once
55:20 What she'd change running product outside a model lab
57:15 The Nano Banana moment that "fuels all of the other chaos"
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Brought to you by:
• Chargebee—Billing and monetization infrastructure for the AI era
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Referenced:
• Antigravity
• Gemini
• Gemini Deep Research
• Gemini Notebook
• Gmail
• Google
• Google Cloud
• Google's Associate Product Manager (APM) Program
• Inside PM at Meta
• Inside PM at Meta 2
• Inside PM at Stripe
• Inside PM at Waymo
• Nano Banana
• Simon Tokumine
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Where to find Nikhyl:
• Twitter/X
• LinkedIn
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Where to find Tulsee:
• Twitter/X
• LinkedIn
–
Join The Skip:
• Skip Coach
• Skip Community
–
Find The Skip:
• Website
• Substack
• YouTube
• Spotify
• Apple Podcasts
–
Don't forget to subscribe to The Skip to hear me coach you through timely career lessons. Access exclusive sessions from 100+ top product leaders at skip.coach. If you're interested in joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at nikhyl@skip.community


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit theskip.substack.com

In this episode, Jagjit Chawla, the VP who runs Facebook's Feed and Reels, returns to see how his predictions from our June conversation have landed. Back in the spring, he described Meta as a company racing to turn PMs into builders. Since then, Meta has become a smaller, flatter company. We get into how that version of Meta, with fewer PMs and layers, pulled in record revenues with its smallest team in years.
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Key topics:
• A smaller, flatter Meta building more, not less
• Why "the glory days of being a PM in big tech are still ahead of us"
• Pointing AI agents at Meta's old codebase to scaffold a new app in weeks
• The new IC9 and IC10 ladder
• Why design and data science aren't shrinking
• Why Jagjit reversed his opinion on PMs shipping production code
• Explaining AI evals using bath towels
• The interview question that screens for "AI PM" judgment
• Why he isn't worried about the industry's next hiring swing
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Timestamps:
00:00 Introduction
02:02 A return visit to see how Meta's AI predictions landed
03:28 Facebook's super-app problem
07:58 Pointing AI agents at Meta's old codebase to scaffold a new app in weeks
11:15 Where Bolt, Lovable, and Replit still can't compete
13:59 Why the new apps aren't cannibalizing Facebook
18:01 Why PMs get the first mile and designers get the last
23:07 Why Jagjit reversed his opinion on PMs shipping production code
24:37 How homegrown AI habits became company-wide baseline tools
29:06 Why "the glory days of being a PM in big tech are still ahead of us"
31:38 "Facebook is like the world's largest Jenga tower"
37:52 The test for converting a manager back into an IC
39:48 The new IC9 and IC10 ladder 42:35 Explaining AI evals using bath towels
46:26 How to coach someone into becoming an "AI PM"
49:37 Should you do a tour of duty at big tech?
53:44 Why Jagjit isn't worried about the industry's next hiring swing
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Brought to you by:
• Jira—Do the right work with Jira
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Referenced:
• Bolt
• Facebook
• Facebook Creator Studio
• Forum, a Facebook app
• Google
• How Meta Is Reinventing Product Management
• Instagram
• Instagram Edits
• Lovable
• Messenger
• Meta
• Meta's Rotational Programs
• Replit
• Seller, a Facebook app
• Threads
• TikTok
• WhatsApp
• YouTube
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Where to find Nikhyl:
• Twitter/X
• LinkedIn
–
Where to find Jagjit:
• LinkedIn
–
Join The Skip:
• Skip Coach
• Skip Community
–
Find The Skip:
• Website
• Substack
• YouTube
• Spotify
• Apple Podcasts
–
Don't forget to subscribe to The Skip to hear me coach you through timely career lessons. Access exclusive sessions from 100+ top product leaders at skip.coach. If you're interested in joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at nikhyl@skip.community


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit theskip.substack.com

In this episode, Saswat Panigrahi, Waymo's CPO, joins me for the third conversation in the "Inside PM" series. Saswat joined Waymo in 2016, back when it was still Google's self-driving car project and the entire product team was fewer than five people, and has spent all ten years since on the same product. In this episode, we discuss how his product org had to invent its own way of measuring good when there was no dashboard to check, why he hires and promotes for competence, courage, and compassion, and what it takes to be an executive builder at Waymo.
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Key topics:
• Cutting severe injuries "sixteen-fold"
• Why measuring good driving became its own product, staffed by dedicated eval PMs
• Why specifying what good looks like is AI's hardest problem
• Injecting rain and fog into simulated scenes instead of waiting a decade for the real thing
• The living room pitch to Waymo's first driverless riders
• Avoiding "Brownian motion": channeling vision into tracks a team can actually execute
• Spotting curiosity and grit in candidates in the age of AI
• Training to the point of failure
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Timestamps:
00:00 Introduction
03:25 Joining Google's self-driving car project before it was Waymo
07:15 Why "feeling the pain" of failures builds real product leadership
08:56 Motivating a team a decade away from a real product
14:38 Was there ever a moment you thought this wouldn't work
16:15 Why measuring "good" driving became its own product, staffed by dedicated eval PMs
18:55 The living room pitch to Waymo's first driverless riders
21:11 Confronting the 40,000 deaths US roads accept every year
23:46 Cutting severe injuries "sixteen-fold"
27:59 Training to the point of failure
33:27 Spotting curiosity and grit in candidates in the age of AI
37:14 Integrity, and sleeping at night over what you approved
41:02 A tree of metrics, not a union list of 37 dashboards
47:14 Competence, courage, and compassion: what builds followership
53:53 What AI has democratized for product discovery and research
57:41 Why specifying "what good looks like" is AI's hardest problem
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Brought to you by:
• Firecrawl—the web data API for AI agents. Use code THESKIP for 10K free credits
• Jira—Do the right work with Jira
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Referenced:
• AMD
• Edwin Markham's poem on preparedness
• Google X
• Inside PM at Meta
• Inside PM at Stripe
• MMLU
• NASA
• Piccadilly Circus
• Transformers
• Waymo
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Where to find Nikhyl:
• Twitter/X
• LinkedIn
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Where to find Saswat:
• Twitter/X
• LinkedIn
–
Join The Skip:
• Skip Coach
• Skip Community
–
Find The Skip:
• Website
• Substack
• YouTube
• Spotify
• Apple Podcasts
–
Don't forget to subscribe to The Skip to hear me coach you through timely career lessons. Access exclusive sessions from 100+ top product leaders at skip.coach. If you're interested in joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at nikhyl@skip.community


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit theskip.substack.com

This is the next episode in a series on what product management becomes when the AI hype meets real constraints. I sat down with three CPOs living about a year ahead of the rest of us: Sharmeen Chapp, Midjourney's first-ever product hire; Jiaona Zhang (JZ), CPO at Laurel; and Henrik Berggren, who runs product and design at Mutiny. Their teams are tiny on purpose, yet these are companies with years of history, paying customers, and enterprise contracts—not the frictionless blank slates that "AI-native" suggests. We get into who should actually be building, how customer signal should move through a company, and how each of them installed an AI-first operating system without tipping into theater.
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Key topics:
• What never changes in PM
• Laurel's "captain" model: everyone is a builder
• Zoning the codebase like a garden so everyone can build safely
• Making the whole company understand the customer
• The AI Operations team: pairing hackers with leaders
• Treating the AI transformation as a product, with employees as the users
• Moving at "Cheetah speed": sprint when the tools jump, then rest
• Current PMs are managing a fleet, not an empire
• Why the strongest leaders are going hands-on now
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Timestamps:
(00:00) Introduction
(03:30) Meet the three CPOs: Midjourney, Laurel, Mutiny
(08:45) Laurel's "captain" model: everyone is a builder
(13:03) Zoning the codebase like a garden
(17:19) Governing change when anyone can ship to production
(18:23) Sharmeen at Midjourney: installing product judgment
(21:53) Henrik on finding the line by stepping over it
(24:57) A Slack channel that pings on every meaningful action
(26:59) Running AI in public so skeptics convert
(29:29) The AI Operations team: pairing hackers with leaders
(32:15) Incentives, public systems, and evergreen context
(36:46) Managing context overload with distributed PM
(39:45) A user interview to shareable clips in 45 minutes
(45:16) First-party vs. third-party: what to build, what to buy
(47:34) The token-maximization "blip" and raising the floor
(49:31) Managing a fleet, not an empire
(53:40) "Cheetah speed": sprint when the tools jump, then rest
(56:37) Why the strongest leaders are going hands-on now
(57:29) Does the pendulum swing back to old-school PM?
(59:48) What never changes: business, customer, orchestration
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Brought to you by:
• Firecrawl—Power AI agents with clean web data
• Use code THESKIP for 10K free credits
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Referenced:
• Anthropic
• Cursor
• Devin
• Dropbox
• Dust
• GitHub
• Google Drive
• Grain
• Granola
• Laurel
• Meta
• Midjourney
• Mutiny
• Notion
• Procter & Gamble
• Slack
• Stripe
• Twitch
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Where to find Nikhyl:
• Twitter/X
• LinkedIn
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Where to find Sharmeen:
• Twitter/X
• LinkedIn
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Where to find JZ:
• Twitter/X
• LinkedIn
–
Where to find Henrik:
• Twitter/X
• LinkedIn
–
Join The Skip:
• Skip Coach
• Skip Community
–
Find The Skip:
• Website
• Substack
• YouTube
• Spotify
• Apple Podcasts
–
Don't forget to subscribe to The Skip to hear me coach you through timely career lessons. Access exclusive sessions from 100+ top product leaders at skip.coach. If you're interested in joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at nikhyl@skip.community


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit theskip.substack.com