Astro has run X, Alphabet's Moonshot Factory, for 16 years. His teams created Waymo, Wing, and Google Brain—by testing over 1,000 ideas a decade and killing nearly all of them. His whole system rests on one uncomfortable rule: celebrate the people who kill their own projects.

In this episode, Astro breaks down why you should do the hard thing first, how pre-written kill criteria force intellectual honesty, and why X maximizes learning per dollar instead of progress—and never tracks whose idea it was.

Why You Should Listen

• Why working on the riskiest part first is the key to testing new ideas
• How writing kill criteria a year in advance stops you from running a zombie startup.
• Why progress doesn't matter when launching a new startup.
• How to come up with big ideas like Waymo and Wing.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, Astro Teller, Google X, moonshot factory, Alphabet, Waymo, innovation process, kill criteria, idea validation, deep tech

Chapters

• 00:00:00 Intro
• 00:04:15 Inside Alphabet's Moonshot Factory
• 00:07:22 The Card Counters of Innovation
• 00:14:00 Learning per Dollar, Not Progress
• 00:23:04 Killing Ideas with Testable Hypotheses
• 00:26:34 Train the Monkey First
• 00:35:16 Kill Criteria: A Message to Your Future Self
• 00:41:59 The Moment of True Product Market Fit

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Cos was the CTO of Brex, which he helped scale from 40 people to over 1,000. Before that, he led engineering at Stripe. When he finally left, he had no startup idea—just a co-founder he trusted and one rule: whatever they built had to have massive impact. Six months of brainstorming later, they landed on accounting.

In this episode, Cos breaks down why he capped the company at 21 people after raising $75M, why everyone—engineers and salespeople alike—earns the exact same salary, how he hit a 100% pilot-to-production conversion rate with top accounting firms, and the counterintuitive process he used to pick accounting over every other industry.

Why You Should Listen

• Why the only reason to join an early-stage company should be the equity, never the cash.
• How Accrual hit a 100% pilot-to-production conversion rate selling to the largest accounting firms.
• Why he raised $75M but refuses to grow past 21 people.
• How to tell real product market fit from the "just one more feature" trap.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, AI accounting, vertical AI, enterprise sales, pilot to production, Brex, Stripe, Cosmin Nicolaescu, Accrual, lean team

Chapters

• 00:00:00 Intro
• 00:01:56 The Moment of True Product Market Fit
• 00:09:46 Collapsing 6+ Tools Into One Platform
• 00:18:07 Leaving Brex to Start From Scratch
• 00:31:41 Landing H&R Block and Armanino
• 00:34:57 A 100% Pilot-to-Production Playbook
• 00:43:26 A 21-Person Company by Design
• 00:51:38 One Salary for Everyone

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Anurag was employee #8 at Stripe, set for life and free to do anything next. Instead he spent a year and a half hunting for a problem worth decades of his life. He chose to build a product to make it simple for developers to ship apps, going head-to-head with AWS.

In this episode, Anurag breaks down how he hit $10M ARR in 4 years with zero marketing spend, why refusing to launch a free tier was his most expensive mistake, and how putting engineers on customer support rotations quietly shaped the entire product roadmap.

Why You Should Listen

• Why you don't have real product market fit until your users sell the product for you.
• How a sub-2-minute setup turned developers into a word-of-mouth machine.
• Why skipping a free tier for years was his most expensive mistake.
• How engineers doing support on rotation built the roadmap—and 6M+ developers.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, developer tools, cloud infrastructure, PaaS, Render, word of mouth growth, product-led growth, AI infrastructure, Stripe

Chapters

• 00:00:00 Intro
• 00:01:44 The Moment of True Product Market Fit
• 00:04:14 The #1 Driver of Word of Mouth
• 00:13:25 Why He Left Stripe to Build Render
• 00:23:48 Why AWS Would Never Build This
• 00:30:33 $10M ARR With No Marketing Spend
• 00:36:43 Engineers as the Support Team
• 00:42:19 Riding the AI Boom

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George had to wind down his last startup and give investors their money back. He went deep into the valley of despair, certain he'd missed his window to build something big. Then he met a co-founder, decided to start over, and started selling.

In this episode, George breaks down how a customer signed a $36K pilot off nothing but a Loom and a one-pager, how cold email took him from zero to $1M ARR with no sales team, and why a "seven out of ten" is the most dangerous hire you can make.

Why You Should Listen

• How a customer signed a $36K pilot after a single Loom and zero calls.
• Why he gave the money back on his last startup—and what "follow your energy" really means.
• How cold outbound email built his first $1M ARR with no sales team.
• Why a "seven out of ten" is the most dangerous hire you can make.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, fintech, accounts receivable automation, AI agents, cold outbound email, B2B SaaS, Series A fundraising, services as software

Chapters

• 00:00:00 Intro
• 00:01:39 The Moment of True Product Market Fit
• 00:03:33 Shutting Down a Small-Market Startup
• 00:07:44 Picking Fintech From Five Ideas
• 00:17:12 From Black Box to Full App
• 00:24:47 $1M ARR on Cold Email Alone
• 00:36:11 Why a "Seven" Is the Most Dangerous Hire
• 00:42:15 Compressing a $25M Series A

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Dan founded and scaled a $50M ARR, SoftBank-backed startup—and could've stayed to make tens of millions. Instead, he handed it to his chief of staff and started from scratch. He wanted something bigger. He took an entry-level paralegal job to learn everything about law hands on. Then he built Manifest, which just raised a $60M Series A.

In this episode, Dan breaks down why he did intake calls for 1,000 legal clients before building anything, how free Slack communities turned Fortune 500 HR managers into buyers without a dollar of ads, and why he refused to sell software to law firms even when investors told him he was crazy.

Why You Should Listen

• How 2 months working as a paralegal beat years of customer discovery.
• How free Slack communities turned Fortune 500 HR managers into clients.
• Why earned media compounds like an asset while paid ads burn like an expense.
• Why impact is the best driver for starting startups.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, legal tech, legal AI, AI-native law firm, immigration law, services as software, community-led growth, earned media, customer discovery, Dan Mishin, Manifest


Chapters

• 00:00:00 Intro
• 00:06:34 Walking Away from $50M ARR
• 00:13:12 Why Immigration Law Has AI Leverage
• 00:18:01 The AI-Native Law Firm Model
• 00:21:49 1,000 Intake Calls Before Building Anything
• 00:30:21 Turning Free Communities Into Buyers
• 00:37:20 Earned Media That Compounds

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Ali quit his job a few months after ChatGPT launched, convinced AI would eat labor marketplaces like Upwork. With no co-founder and no code, he collected $12K from real customers—using a faked demo and a cloned voice. Then he pitched 100 VCs in 10 days and got 47 straight 'no's.

In this episode, Ali breaks down how he banked $12K in revenue before writing a single line of code, how a $20/month Slack community drove Amigo's first $1M in ARR, and why he churned every existing customer to go all-in on $100K+ healthcare enterprise deals.

Why You Should Listen

• Why validation only counts when dollars exchange hands.
• How a $20/month paid community turned into $1M in ARR.
• Why he refunded every customer and churned 100% of his revenue.
• Why founders must sell the first $2M themselves before hiring an AE.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, AI agents, healthcare AI, enterprise sales, pre-seed fundraising, community-led growth, customer validation, pivot, Amigo AI

Chapters

• 00:00:00 Intro
• 00:08:37 From Upwork to Starting Amigo
• 00:13:30 $12K in Revenue Before Writing Code
• 00:23:24 Pitching 100 VCs in 10 Days
• 00:30:20 47 No's—Then FOMO Took Over
• 00:37:12 The $20/Month Community Behind the First $1M
• 00:45:47 Churning 100% of Revenue on Purpose
• 00:01:49 The Moment of True Product Market Fit

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Mark was running a startup out of a tiny annex office in Dublin with zero product usage. Then one customer turned it on and overnight he saw usage spike to thousands of simulations. He got to $1M ARR 100% through outbound, by sending 500,000 cold emails. A few months ago he closed a $25M Series A.

In this episode, Mark breaks down the pivot from sales roleplay to customer support that unlocked his first real traction, the cold outbound playbook that took him to $1M ARR (500K emails, 250 meetings, 40 customers), and why doorstepping customers in Utah is what drove his net revenue retention to 186%.

Why You Should Listen

• Exactly how to use a cold outbound strategy to hit $1M ARR.
• Why getting on 56 flights last year to visit customers led to 186% NRR.
• How he closed a $25M Series A in just 6 days.

Keywords startup podcast, startup podcast for founders, product market fit, finding pmf, AI startup, customer support, cold outbound, Y Combinator, Series A, enterprise sales, SaaS, Solid Road

Chapters

• 00:00:00 Intro
• 00:06:10 The Pivot From Sales to Customer Support
• 00:12:54 Why Moving to SF Changed Everything
• 00:22:34 Cold Outbound to $1M ARR
• 00:32:47 Doorstepping Customers for 186% NRR
• 00:39:17 Closing a $25M Series A in 6 Days

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The AI boom is making founders feel like the market is wide open, but the data tells a sharper story: valuations are up, round sizes are bigger, and the bar to “count” in a top-tier fund’s Monday meeting keeps rising. We sit down with Peter to translate Q1 2026 venture capital trends into founder reality, from seed-stage pricing distortions driven by AI infrastructure to the quieter pressure building across the rest of the startup market.

We get specific on early-stage fundraising benchmarks and why Series A now looks riskier than many people assume. Median Series A valuations have climbed close to 2x in a few years, while typical raises jumped from roughly $8M to $10M to $13M to $15M. That changes everything: ownership targets, follow-on costs, and the outcome math that pushes investors (and founders) toward “decacorn-plus” expectations. If you are pitching $100M ARR as the endgame, you may already be behind.

Then we zoom out to the forces shaping who wins: Bay Area gravity, a real valuation gap versus other hubs, and practical tactics like visiting the Bay to capture network effects without uprooting your life. We also dig into defensibility in AI application startups, where building is faster but competition is fiercer, plus the rise of smaller teams and solo founders, and what that means for hiring, equity, and motivation on early teams.


Chapters

• 00:00:00 LLM Hype And Bubble Warning
• 00:02:13 Five Stars Then We Begin
• 00:03:02 Seed Prices Spike In AI Infra
• 00:07:10 2026 Benchmarks For Pre-Seed To A
• 00:09:36 Series A Doubles And Exit Math
• 00:12:54 Bay Area Gravity And Valuation Gap
• 00:18:22 Defensibility Gets Harder In AI Apps
• 00:23:22 Smaller Teams Solo Founders Talent Shifts
• 00:35:20 VC Fund Shakeout And Final Share Ask

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