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The Skip Podcast: Daily Summaries Delivered
by Nikhyl Singhal
The Skip podcast helps tech professionals get ahead in their career. It's hosted by Nikhyl Singhal, a three-time founder, CPO, and product executive at Meta and Google. Nikhyl has helped scale four of the most successful tech products ever: Facebook, Credit Karma, Google Photos, and Google Hangouts. He now runs Skip Coach, a career service powered by the world's top CPO community, and has coached hundreds of product leaders through career decisions, management challenges, and transitions.
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- 2 weeks ago1h 0m
Job-Search Advice Now Expires Every Six Months
In this episode, three leaders who recently took on AI roles break down their job search: Anthony Maggio, who left Airtable after five and a half years to become CPO at Runway, Gadi Ben-Zvi, who leads AI platform and products at Eli Lilly, and Chandra Raghavan, a principal PM on Search AI at Google. This is the third conversation in our job-search series, where about every 100 days I check in with executives who just landed new roles to see what has changed. We get into why Anthony passed on the frontier labs for a 200-person company, why Gadi joined Eli Lilly, a company willing to spend years on its AI bets, and why Chandra says choosing between a startup and big tech is “a false dichotomy.” –Key topics:• The interview questions that test AI judgment, starting with "Where did it fail?"• Why a side project of your own became the credential• How to avoid becoming "the person who tried ChatGPT in 2022"• Why a senior IC role on Google Search AI feels more like a startup than big tech• How to tell if a company has a real edge in AI• What hasn’t changed in senior PM interviews, and the new baseline• What to stop highlighting: managing through layers and cross-functional coordination• How candidates stand out now: auditing the product and prototyping fixes after a first conversation –Timestamps:00:00 Introduction02:58 Meet the three leaders who just landed AI roles at Lilly, Runway, and Google09:19 Anthony's search criteria: proximity to the frontier, talent density, and fit14:30 How research breakthroughs become products at Runway15:57 Why a 200-person company beat the big labs19:32 What Eli Lilly built with 150 years of data, and why the bet will last23:09 Optimizing for 2026 Chandra, not 2016 Chandra26:05 Startup-style ownership at scale: Chandra's "false dichotomy"29:08 What surprised them about interviews33:44 How to speak credibly about agents when your job doesn't build them39:44 What Eli Lilly wanted from a product leader with no pharma background41:20 The questions interviewers are asking about AI43:10 Why continuous experiments beat one big project48:31 What past experience still counts, and what to stop highlighting50:31 How candidates stand out now: auditing the product and prototyping fixes after a first conversation52:58 Finding a company's real edge: proprietary data, domain expertise, feedback loops56:23 How Google Search moves like a startup, and why you onboard yourself– Brought to you by:• Chargebee—Billing and monetization infrastructure for the AI era• Stripe Treasury—Bring payments and finances together –Referenced:• 10 Job Search Rules That Just Broke• Airtable• Airtable Omni and Field Agents• Anthropic• ChatGPT• Claude• Eli Lilly• Google• Google AI Mode• Google AI Overviews• Google Photos• Meta• OpenAI• Runway• Runway Solaris• Three Job Searches, Three AI Roles –Where to find Nikhyl:• Twitter/X• LinkedIn– Where to find Anthony:• Twitter/X• LinkedIn –Where to find Gadi:• LinkedIn –Where to find C
- Oct 1, 202659 min
Three Top Executive Recruiters on Where Product Management Is Going
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.–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–Timestamps00:00 Introduction02:28 Meet our guests from Daversa, Fusion Talent, and a16z04:58 How much has demand for product leaders grown this year?06:14 The two types of companies hiring a CPO right now09:34 Why founders under-hired and are now up-leveling the role12:15 How companies assess whether an executive is really hands-on14:25 Working sessions have shifted from presenting to building together18:00 The profile of candidates closing searches in the last 90 days20:50 Why later-stage companies want builders who can attract AI-pilled PMs23:30 Should executives found a company to boost their careers?25:00 The attributes that matter27:10 Do AI companies need leaders with AI experience?31:04 Building AI reps outside your day job33:08 In-office expectations and whether 9-9-6 has cooled35:15 Can executives with families keep up with the pace?39:12 How to assess a company's culture before you join44:25 How to evaluate a paper-rich offer at a high valuation49:05 Competing with Meta, Google, and the labs on comp51:58 Predictions for next summer: researchers, physical AI, and technical depth56:18 Why AI fluency will stop differentiating candidates57:24 Domain depth as the next differentiator–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• <a target="_blank" href="https:
- Sep 17, 202659 min
Inside Gemini: How Google Runs Product for Its Model
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.–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"–Timestamps:00:00 Introduction03:28 Welcoming Tulsee Doshi to break down how Google builds Gemini04:10 Eleven years at Google, from Search and YouTube to leading Gemini06:20 Why the model team works like an engine maker for a garage of cars08:40 Why stack-ranking every request would produce "a boring product"11:25 "Nothing can replace a great eval": evals as the new PRD14:36 The "20 prompts" trick for turning a vague ask into a great eval18:44 How to know a model is ready to ship without waiting a year22:40 "Vibes": why Simon Tokumine's gut check on a model carries real weight27:20 Why speed beats trying to build the perfect product today29:35 Prototyping features that "don't quite work yet," on purpose31:05 The 60/20/20 rule for building against a model that keeps improving33:58 The five traits she looks for in a research PM40:35 Why "technical" on her team means thorough, not a CS degree44:25 How AI tools are changing what Google's PMs do all day48:30 Why Google's I/O still matters as a forcing function52:50 The vibe inside Gemini right now: hype and chaos at once55:20 What she'd change running product outside a model lab57:15 The Nano Banana moment that "fuels all of the other chaos"–Brought to you by:• Chargebee—Billing and monetization infrastructure for the AI era–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–Where to find Nikhyl:• Twitter/X• LinkedIn–Where to find Tulsee:• Twitter/X• LinkedIn–Join The Skip:• Skip Coach• Skip Community–Find The Skip:• Website• Substack• YouTube• <a target="_blank" href="https://open.spotify.com/show/4oT2rxMsRP
- Sep 3, 202655 min
What the Past Year Taught Meta
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.–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–Timestamps:00:00 Introduction02:02 A return visit to see how Meta's AI predictions landed03:28 Facebook's super-app problem07:58 Pointing AI agents at Meta's old codebase to scaffold a new app in weeks11:15 Where Bolt, Lovable, and Replit still can't compete13:59 Why the new apps aren't cannibalizing Facebook18:01 Why PMs get the first mile and designers get the last23:07 Why Jagjit reversed his opinion on PMs shipping production code24:37 How homegrown AI habits became company-wide baseline tools29:06 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 IC39:48 The new IC9 and IC10 ladder 42:35 Explaining AI evals using bath towels46:26 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–Brought to you by:• Jira—Do the right work with Jira–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–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 join
- Aug 20, 202659 min
To Invent Waymo, They Had to Reinvent PM
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.–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–Timestamps:00:00 Introduction03:25 Joining Google's self-driving car project before it was Waymo07:15 Why "feeling the pain" of failures builds real product leadership08:56 Motivating a team a decade away from a real product14:38 Was there ever a moment you thought this wouldn't work16:15 Why measuring "good" driving became its own product, staffed by dedicated eval PMs18:55 The living room pitch to Waymo's first driverless riders21:11 Confronting the 40,000 deaths US roads accept every year23:46 Cutting severe injuries "sixteen-fold"27:59 Training to the point of failure33:27 Spotting curiosity and grit in candidates in the age of AI37:14 Integrity, and sleeping at night over what you approved41:02 A tree of metrics, not a union list of 37 dashboards47:14 Competence, courage, and compassion: what builds followership53:53 What AI has democratized for product discovery and research57:41 Why specifying "what good looks like" is AI's hardest problem–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–Referenced:• AMD• Edwin Markham's poem on preparedness• Google X• Inside PM at Meta• Inside PM at Stripe• MMLU• NASA• Piccadilly Circus• Transformers• Waymo–Where to find Nikhyl:• Twitter/X• LinkedIn–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,
- Aug 5, 20261h 1m
Lessons From Three Product Leaders Living in the Future
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.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 nowTimestamps: Introduction Meet the three CPOs: Midjourney, Laurel, Mutiny Laurel's "captain" model: everyone is a builder Zoning the codebase like a garden Governing change when anyone can ship to production Sharmeen at Midjourney: installing product judgment Henrik on finding the line by stepping over it A Slack channel that pings on every meaningful action Running AI in public so skeptics convert The AI Operations team: pairing hackers with leaders Incentives, public systems, and evergreen context Managing context overload with distributed PM A user interview to shareable clips in 45 minutes First-party vs. third-party: what to build, what to buy The token-maximization "blip" and raising the floor Managing a fleet, not an empire "Cheetah speed": sprint when the tools jump, then rest Why the strongest leaders are going hands-on now Does the pendulum swing back to old-school PM? What never changes: business, customer, orchestrationBrought to you by:• Firecrawl—Power AI agents with clean web data• Use code THESKIP for 10K free creditsReferenced:• Anthropic• Cursor• Devin• Dropbox• Dust• GitHub• Google Drive• Grain• Granola• Laurel• Meta• Midjourney• Mutiny• Notion• Procter & Gamble• Slack• Stripe• TwitchWhere to find Nikhyl:• Twitter/X• LinkedInWhere to find Sharmeen:• Twitter/X• LinkedInWhere to find JZ:• Twitter/X• LinkedInWhere to find Henrik:• Twitter/X• LinkedInJoin The Skip:</stro
- Jul 22, 20261h 1m
Inside PM at Stripe: What Comes After "Become a Builder"?
Kevin Yien is the Head of Product for Merchant Experiences at Stripe. Before that he led Product at Mutiny and Square. In this episode, Kevin and I discuss how to keep AI from becoming theater, why a PM shipping to production can be a red flag, and why AI is pulling product management back to its fundamentals of strategy, opinion, and judgment. –Key topics:• Why "PM is dead" is the wrong frame, and every function is "shifting left"• The three PM archetypes, and how zero-to-one changed most"Killing your darlings" and keeping the blast radius small• From a personal knowledge corpus to a shared "team brain"• The "floors and ceilings" of a shared knowledge base• Why building 10 prototypes no one sees is just theater• Writing as "clarity at scale," and why LLMs still can't do it• Why vibe coding is a wasted learning opportunity unless you interrogate it• The "eight and 80 test" for joy, pace, and hard family seasons– Timestamps:00:00 Introduction03:40 What Kevin owns across Stripe's merchant experiences05:24 Stop asking which role dies, focus on the outcomes08:05 The three PM archetypes, and why zero-to-one changed most10:50 Kill your darlings: keeping the blast radius small14:30 The PM as the "arbiter of context"17:55 Floors and ceilings of a shared "team brain"20:43 "Does this obsolete me?" The PM layoff fear22:50 Are wikis and knowledge artifacts back?28:42 How Stripe incentivizes sharing: carrots over sticks31:35 The pet peeve: 10 prototypes, zero users35:20 Onboarding as a product: the first 100 days38:16 Writing as "clarity at scale," and why LLMs still can't do it45:35 The "piano scales" for a PM: forming an opinion48:37 Do engineering-background PMs still win?52:30 Are product, design, and engineering roles merging?55:30 Joy, pace, and the "eight and 80 test"–Brought to you by:• Asana—The operating system for human agent teams–Referenced:• Andrej Karpathy• Block• Claude Code• Contentful• Dovetail• GitHub• Kevin on Lenny's Podcast• Lindy effect• Lovable• Obsidian• Patrick Collison• Stripe• v0• Writer–Where to find Nikhyl:• Twitter/X• LinkedIn–Where to find Kevin:• Twitter/X• LinkedIn• Website–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 s
- Jul 15, 202639 min
Builder-Executives Are Getting Paid Like Pro Athletes
Product pay is detaching from the old bands the way it did for AI researchers. In the past few weeks I've seen three offers go out to product executives at $10 million a year, and while almost nobody gets that number, it pulls the whole field up. The builder-executive who can build with modern tools and operate at scale now commands two to three times what the same profile did a year ago. In this episode, my co-host Carly Malatskey and I walk three real career decisions end to end: a leader worried the AI bubble will pop and playing it too safe, a consultant trying to become a product builder, and an elite executive trying to match joy, purpose, and income in one role. The throughline is the "Skip" question: not how to maximize today's job, but which next move opens the path to elite a few years out.–Key topics:• Why builder-executive pay detached from the bands• The three questions every career-maximizer should ask themselves• Thinking of constraints as a risk budget• Why staying current beats the biggest job at the best company• How to test whether a company is actually "current" from the outside• Why top-of-market pay comes with strings, and how to sequence what you optimize for• The mercenary vs. missionary approachTimestamps: Introduction The 100-day shift: builder execs and $10M offers Case 1, Angie: two safe offers and an AI-bubble fear Optimizing to be elite, or just to be prudent? Why a failed hot startup can leave you better off Thinking about what your next role sets up, not just the salary Case 2, Gary: Series A vs. Fortune 20 Working backward from the PE operating-partner dream The biggest job at the most current company, not the best How to tell if a company is actually "current" Case 3, Monica: elite, comfortable, and chasing joy One more operating role, then founding Choosing mercenary over missionary Would the right company help her find a co-founder The three questions that shape modern career advice–Brought to you by:Asana—The operating system for human agent teams–Referenced:• Anthropic• Meta• Microsoft• OpenAI• Stripe–Where to find Nikhyl:• Twitter/X• LinkedIn–Where to find Carly:• 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
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About The Skip Podcast
The Skip podcast helps tech professionals get ahead in their career. It's hosted by Nikhyl Singhal, a three-time founder, CPO, and product executive at Meta and Google. Nikhyl has helped scale four of the most successful tech products ever: Facebook, Credit Karma, Google Photos, and Google Hangouts. He now runs Skip Coach, a career service powered by the world's top CPO community, and has coached hundreds of product leaders through career decisions, management challenges, and transitions.
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