In Depth

In the latest episode of Executive Function, Brett sits down with Jay Parikh, Executive Vice President of CoreAI at Microsoft. Before joining Microsoft, Jay spent over a decade as Facebook's global head of engineering, scaling the company from a few hundred engineers to billions of users, then ran the cybersecurity company Lacework as CEO through its acquisition by Fortinet. In this conversation, he breaks down the five ingredients of great engineering leadership, discusses why he'd rather run two competing bets in parallel than forecast a winner, and explains why company culture remains more important than ever for teams to get right.

In today's episode, we discuss:

The five ingredients that separate excellent engineering leadership from the rest

How to protect your team from large shifts in public perception

The mindset shift organizations need to maintain speed at scale

How every layer of the organization needs to stay connected to the customer

Why Jay runs "brain trusts" of senior ICs with zero managers in the room

References

Akamai: https://www.akamai.com/

AWS: https://aws.amazon.com/

Facebook: https://www.facebook.com/

George Conrades: https://www.linkedin.com/in/georgeconrades/

Mark Zuckerberg: https://x.com/finkd

Microsoft: https://www.microsoft.com/

Paul Sagan: https://www.linkedin.com/in/paul-sagan-59654a1/

Tom Leighton: https://www.linkedin.com/in/tleighton/

Where to find Jay

LinkedIn: https://www.linkedin.com/in/jayparikh/

Twitter/X: https://x.com/jayparikh

Where to find Brett

LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/

Twitter/X: https://twitter.com/brettberson

Where to find First Round Capital

Website: https://firstround.com/

First Round Review: https://review.firstround.com/

Twitter/X: https://twitter.com/firstround

YouTube: https://www.youtube.com/@FirstRoundCapital

This podcast on all platforms: https://review.firstround.com/podcast

Timestamps

00:00 Introduction

00:36 How leadership changes through exponential growth

02:21 The five ingredients that define excellent engineering leadership

07:51 What actually drives culture at a company as it scales

12:05 The physics behind why everything slows down at scale

18:57 The fastest team of Jay's career, and why size mattered

22:44 Why every team should think like an FDE

26:20 Managing a team through wild swings in public perception

29:07 What's different about leading through the steepest S-curve moments

33:58 Why onboarding well means going slow to go fast

37:41 Is AI actually new, or is history just repeating?

41:35 What actually counts as a "big bet" worth taking

45:01 The concrete big bets that reshaped Facebook's entire technology stack

47:35 Why vertical integration keeps being the right call as companies scale

51:46 How being a startup CEO reshaped Jay as a leader

1:01:26 Why Jay overruled Zuckerberg's instinct to skip efficiency

In the latest episode of Executive Function, Brett sits down with Lindsey Scrase, COO of Checkr. Before joining Checkr as CRO and later stepping into the COO seat, Lindsey spent nearly a decade at Google Cloud as global managing director for SMB, mid-market, and startups. In this conversation, she breaks down why moving upmarket into enterprise trips up so many startups looking to scale, how Checkr rebuilt its sales compensation model to keep pace with growth, and where AI is already reshaping her operations and go-to-market teams.

In today's episode, we discuss:

Why operators who thrive at massive-scale companies often struggle when they join a startup

The hard-won lessons from Checkr's early enterprise push that nearly failed

Why Checkr’s C-suite meets every morning with no specific agenda

The surprising challenges moving from CRO to COO

How Checkr turned AI experiments into operating systems

References

Amazon: https://www.amazon.com

Checkr: https://checkr.com

Claude: https://claude.com

Daniel Yanisse: https://www.linkedin.com/in/yanisse/

DoorDash: https://www.doordash.com

Google: https://www.google.com

Lovable: https://lovable.dev

Microsoft: https://www.microsoft.com

Where to find Lindsey

LinkedIn: https://www.linkedin.com/in/lindsey-scrase-0702442/

Twitter/X: https://twitter.com/Lscrase

Where to find Brett

LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/

Twitter/X: https://twitter.com/brettberson

Where to find First Round Capital

Website: https://firstround.com/

First Round Review: https://review.firstround.com/

Twitter/X: https://twitter.com/firstround

YouTube: https://www.youtube.com/@FirstRoundCapital

This podcast on all platforms: https://review.firstround.com/podcast

Timestamps

00:00 Introduction

00:06 Why big-company executives often struggle in startups

02:18 What Checkr's first CRO needed to accomplish

03:33 How to take on an entrenched category leader

06:58 Why leaders underestimate how hard the jump to enterprise really is

10:23 Separating a true deal-blocker from a customer's nice-to-have request

18:30 Why Lindsey hired enterprise-scarred sales leader over a market leader's résumé

22:08 The biggest challenges of moving from CRO to COO

28:03 Why Checkr names a single decision-maker for every major decision

34:42 Why Checkr rebuilt their sales compensation model

40:39 What actually separates a team's best seller from everyone else

45:03 Inside Checkr’s daily, no-agenda, c-suite meeting

50:23 How following data can sometimes lead you in the wrong direction

57:27 Why hitting 130% of a goal isn’t always a good thing

58:57 Where AI has changed how Checkr's teams operate day to day

1:04:33 Advice for all aspiring COOs

In this episode of In Depth, Brett sits down with Jon Noronha, co-founder and CPO of Gamma, the AI-native presentation platform used by more than 100 million people. In this conversation, he walks through Gamma’s distinct eras of product-market fit: from a pre-AI struggle with a year of runway left, to an overnight AI-fueled explosion, to today’s unplanned scramble into enterprise sales. Jon also unpacks his hard-won lessons on horizontal versus vertical bets, monetizing AI products, and why nailing onboarding turned out to be the whole game.

In today's episode, we discuss:

Why Gamma's all-in AI launch in March 2023 saved their startup

How fixing a simple onboarding problem accidentally uncovered Gamma’s entire product-market fit

Why Jon bet Gamma on a horizontal product against the advice of nearly every investor

How Gamma's daily signups climbed from hundreds to over 100,000 with zero paid marketing

What building three pricing tiers taught Jon about monetizing AI

References

Canva: https://www.canva.com/

Corgi: https://www.corgi.insure/

Facebook: https://www.facebook.com/

Gamma: https://gamma.app/

Google: https://www.google.com/

Linear: https://linear.app/

Loom: https://www.loom.com/

Microsoft: https://www.microsoft.com/

Notion: https://www.notion.com/

Optimizely: https://www.optimizely.com/

Salesforce: https://www.salesforce.com/

Slack: https://slack.com/

Zoom: https://www.zoom.us/

Where to find Jon Noronha

LinkedIn: https://www.linkedin.com/in/jonnoronha/

Twitter/X: https://twitter.com/thatsjonsense

Where to find Brett

LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/

Twitter/X: https://twitter.com/brettberson

Where to find First Round Capital

Website: https://firstround.com/

First Round Review: https://review.firstround.com/

Twitter/X: https://twitter.com/firstround

YouTube: https://www.youtube.com/@FirstRoundCapital

This podcast on all platforms: https://review.firstround.com/podcast

Timestamps:

00:00 Introduction

01:47 Gamma’s three-era journey to product-market fit

03:41 Spotting the blank page problem pre-ChatGPT

05:11 How Gamma survived with only one year of runway

07:17 How onboarding fixes revealed the whole product

09:31 Choosing horizontal over investors' vertical playbook

13:41 Prototyping by hand before AI coding

15:36 How Gamma builds with future models in mind

20:06 The Kool-Aid mistake of a late PowerPoint export

24:31 Why the presentation industry hadn't evolved since 1987

33:30 How Gamma solves evals for taste, not just data

40:21 Jon's hardest lessons monetizing AI since 2023

44:16 The fast leap from prosumer to enterprise

47:01 Why product still beats distribution

52:06 The metric that proved product-market fit

57:36 Pricing advice for prosumer AI founders

59:01 The toils and realities of founder life

In the latest episode of Executive Function, Brett sits down with Eric Sager, COO of Plaid, following stints as CRO of Bluevine and Head of Sales at Square. During his seven-year tenure at Plaid, Eric has helped lead the business through a pandemic, Visa's collapsed acquisition, a fintech downturn, and the AI boom. In today’s conversation, he unpacks how he kept teams focused during turbulent times, why he refuses to run at 100% capacity, and how he re-architected the go-to-market function as Plaid scaled.

In today's episode, we discuss:

How Plaid stayed focused after the Visa acquisition fell through and then raised at nearly 3x the price

Why great COOs deliberately make themselves obsolete

Why Eric treats speed, risk, and cost as a three-way trade-off, and why sometimes going slower wins

How refusing to run at 100% capacity helped Plaid win OpenAI, Perplexity, and Replit

Why Eric personally cold-calls brand-new employees

References

Bain & Company: https://www.bain.com

Bluevine: https://www.bluevine.com

Chase: https://www.chase.com

Citibank: https://www.citi.com

Eyal Lifshitz: https://www.linkedin.com/in/eyallifshitz/

Françoise Brougher: https://x.com/FrancoiseBr

Gokul Rajaram: https://www.linkedin.com/in/gokulrajaram1/

Jack Dorsey: https://x.com/jack

Michael Mankins: https://www.linkedin.com/in/michaelcmankins

OpenAI: https://openai.com

Perplexity: https://www.perplexity.ai

Plaid: https://plaid.com

Replit: https://replit.com

Sarah Friar: https://www.linkedin.com/in/sarah-friar/

Square: https://squareup.com

Visa: https://www.visa.com

William Hockey: https://www.linkedin.com/in/william-hockey-04536710

Zach Perret: https://www.linkedin.com/in/zperret/

Where to find Eric Sager

LinkedIn: https://www.linkedin.com/in/eric-sager-a529516

Where to find Brett

LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/

Twitter/X: https://twitter.com/brettberson

Where to find First Round Capital

Website: https://firstround.com/

First Round Review: https://review.firstround.com/

Twitter/X: https://twitter.com/firstround

YouTube: https://www.youtube.com/@FirstRoundCapital

This podcast on all platforms: https://review.firstround.com/podcast

Timestamps

00:00 Introduction

00:40 Leading a company through turbulent times

04:24 How to build a resilient team culture

08:33 How Plaid avoids bureaucracy, while operating at scale

10:58 The speed-quality tradeoff: Going faster isn't always better

15:32 When to move from generalists to specialized customer segments

20:14 Why Plaid has one owner for entire customer relationships

22:06 The "quarterback" model: one owner, experts on call

24:08 Why you should never run your org at 100% capacity

29:47 "Always available, never needed": the support mantra

36:49 Eric’s unusual "hit by a bus" test to measure job success

43:57 Why Eric cold calls brand-new employees

52:14 Eric's week: 25% ecosystem, 50% business, 25% team

55:15 How to spot fake mission alignment in interviews

59:04 The one thing a founder has that no hire can replicate

In this episode of In Depth, Brett sits down with Paul Copplestone, co-founder and CEO of Supabase, the open-source Postgres platform now serving more than seven million developers. Before Supabase, Paul launched a Thumbtack-style marketplace in Southeast Asia and co-founded an office-management startup called Nimbus, experiences that taught him to separate fundraising from building and to find product-market fit before blitzscaling. He breaks down how a single tagline change for Supabase unlocked product-market fit, why he runs a fully distributed async team with near-zero attrition, and how he turned PLG signals into a product-led sales motion comped only on incremental uplift.

In today's episode, we discuss:

How changing one tagline helped Supabase go to #1 in Hacker News - an early sign of product market fit

Why Paul ran Supabase like it had only $100K in the bank despite raising real money

How Supabase rode three distinct AI waves, from pgvector to Bolt and Lovable, to Claude Code

Why Supabase built a sales team comped only on the incremental uplift over a control group

What the Toyota production system's "kaizen" taught Paul about unblocking a scaling team

References:

Ant Wilson: https://www.linkedin.com/in/ant-wilson-46179937

Bolt: https://bolt.new/

Claude Code: https://www.anthropic.com/claude-code

Codex: https://openai.com/codex/

Entrepreneurs First: https://www.joinef.com/

Firebase: https://firebase.google.com/

Lovable: https://lovable.dev/

MongoDB: https://www.mongodb.com/

Next.js: https://nextjs.org/

PostgreSQL: https://www.postgresql.org/

Supabase: https://supabase.com/

Thumbtack: https://www.thumbtack.com/

Y Combinator: https://www.ycombinator.com/

Where to find Paul:

LinkedIn: https://www.linkedin.com/in/paulcopplestone

Twitter/X: https://x.com/kiwicopple

Where to find Brett:

LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/

Twitter/X: https://twitter.com/brettberson

Where to find First Round Capital:

Website: https://firstround.com/

First Round Review: https://review.firstround.com/

Twitter/X: https://twitter.com/firstround

YouTube: https://www.youtube.com/@FirstRoundCapital

This podcast on all platforms: https://review.firstround.com/podcast

Timestamps:

00:00 Introduction

01:32 Why Paul's earlier startups were never destined to be huge

07:14 Unlearning the "tall poppy" mindset and going all-in on async

09:54 Reverse-engineering why Supabase was an outstanding idea

12:04 The accidental Hacker News launch and tagline lesson

13:58 Where the early roadmap came from: demand vs. technical taste

17:28 Skill vs. luck, and operating like you have $100K in the bank

21:42 What actually makes a great developer experience

23:10 Solving the "graduation problem" Firebase never could

24:58 The role of open source in Supabase's success

26:10 The three distinct AI tailwinds: From pgvector to Claude Code

35:24 Supabase’s egoless, hyper-competitive open-source culture

42:58 A tactical playbook for raising capital

48:37 Product-led sales comped on incremental uplift only

59:27 The production philosophy behind Supabase’s operations