The Insider's Guide to Tech Compensation, Negotiation, and Career Growth

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 Introduction 02:58 Meet the three leaders who just landed AI roles at Lilly, Runway, and Google 09:19 Anthony's search criteria: proximity to the frontier, talent density, and fit 14:30 How research breakthroughs become products at Runway 15:57 Why a 200-person company beat the big labs 19:32 What Eli Lilly built with 150 years of data, and why the bet will last 23:09 Optimizing for 2026 Chandra, not 2016 Chandra 26:05 Startup-style ownership at scale: Chandra's "false dichotomy" 29:08 What surprised them about interviews 33:44 How to speak credibly about agents when your job doesn't build them 39:44 What Eli Lilly wanted from a product leader with no pharma background 41:20 The questions interviewers are asking about AI 43:10 Why continuous experiments beat one big project 48:31 What past experience still counts, and what to stop highlighting 50:31 How candidates stand out now: auditing the product and prototyping fixes after a first conversation 52:58 Finding a company's real edge: proprietary data, domain expertise, feedback loops 56:23 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 Chandra: • 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 [email protected]

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 – 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 – 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 – Brought to you by: • Chargebee—Billing and monetization infrastructure for the AI era – Where to find Nikhyl • Twitter/X • LinkedIn – Where to find Lindsay • LinkedIn – Where to find Andrew • LinkedIn – Where to find Caroline • 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 [email protected]

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 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" – 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 • 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 [email protected]

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 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 – 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 joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at [email protected]

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 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 – 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, or Twitter. You can also email me at [email protected]