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Today I sit down with Nat Eliason - founder, writer, and now launching Alpha School, a new entrepreneur high school in New York City. Tuition is $150K a year. The promise: every student hits a million dollars in gross profit by graduation, or the family gets their tuition refunded....

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Chris Powers

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201,902 次观看 • 3 个月前 •via X (Twitter)

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Tomorrow I'm sitting down with Nat Eliason, founder, writer, and the man behind Alpha School - a new entrepreneur high school opening in NYC this fall. Tuition is $150K a year. The promise: every student makes $1M in gross profit by graduation, or the family gets the tuition refunded. To explain why a school like this needs to exist, Nat starts with one word borrowed from pro wrestling: kayfabe. The fake fight everyone agrees to take seriously. He thinks that's exactly what school has become for almost every kid in America. This clip is the case.
3:59

Tomorrow I'm sitting down with Nat Eliason, founder, writer, and the man behind Alpha School - a new entrepreneur high school opening in NYC this fall. Tuition is $150K a year. The promise: every student makes $1M in gross profit by graduation, or the family gets the tuition refunded. To explain why a school like this needs to exist, Nat starts with one word borrowed from pro wrestling: kayfabe. The fake fight everyone agrees to take seriously. He thinks that's exactly what school has become for almost every kid in America. This clip is the case.

Chris Powers

48,841 次观看 • 3 个月前

Founders School is a new high school where tuition is $150k a year, but if students don't hit $1M in gross profit by graduation, they get their tuition back. Nat Eliason says AI will make this possible: "AI is the big thing that removes the bottleneck around why a 17-year-old can't build a million-dollar business." "You don't need to spend as long developing deep expertise in programming or software development because, certainly for a V1, you can prompt a lot of it." "You don't need to raise a ton of money for hiring, design, buildout, or any of these things. Because again, you can get an initial version going with AI." "So if you can just use AI to get started, and get your business going, you take out a lot of the capital requirements, a lot of the expertise build-up requirements, and it just shortens the timeline. It makes a lot more things possible for them."
1:54

Founders School is a new high school where tuition is $150k a year, but if students don't hit $1M in gross profit by graduation, they get their tuition back. Nat Eliason says AI will make this possible: "AI is the big thing that removes the bottleneck around why a 17-year-old can't build a million-dollar business." "You don't need to spend as long developing deep expertise in programming or software development because, certainly for a V1, you can prompt a lot of it." "You don't need to raise a ton of money for hiring, design, buildout, or any of these things. Because again, you can get an initial version going with AI." "So if you can just use AI to get started, and get your business going, you take out a lot of the capital requirements, a lot of the expertise build-up requirements, and it just shortens the timeline. It makes a lot more things possible for them."

TBPN

179,482 次观看 • 3 个月前

LIVE NOW - Building a Million Dollar Zero Human Company with OpenClaw | Nat Eliason Nat Eliason joins us to show what it looks like to build a “zero human company” with Felix Craft, an AI CEO that ships products, runs ops, and manages other agents for support and sales. Felix went from an overnight info product to a full marketplace for AI agent skills: Claw Mart is service that deploys custom OpenClaw employees for real businesses, hitting nearly $80k in revenue since early February while operating on surprisingly low monthly costs. -------------- TIMESTAMPS 0:00 Intro 0.24 Nat’s Background 6:30 Felix 11:43 Real Businesses vs Memecoins 14:23 Felix’s Employees 18:06 Felix’s Business 31:26 How Customized is Felix? 38:17 Felix’s Business Risks 40:12 Can OpenClaw Replace Knowledge Workers? 43:38 Claw Mart 48:49 Felix’s Expenses 51:15 Nat’s Role 56:39 Felix’s Discord 1:03:19 Citrini Doomer Scenario 1:13:04 Hiring Your First Agent 1:16:19 General AI Assistants 1:19:50 AI Friends 1:22:39 The AI Agent Frontier 1:26:52 Crypto x AI 1:31:53 What’s Next 1:34:27 Closing & Disclaimers
1:35:39

LIVE NOW - Building a Million Dollar Zero Human Company with OpenClaw | Nat Eliason Nat Eliason joins us to show what it looks like to build a “zero human company” with Felix Craft, an AI CEO that ships products, runs ops, and manages other agents for support and sales. Felix went from an overnight info product to a full marketplace for AI agent skills: Claw Mart is service that deploys custom OpenClaw employees for real businesses, hitting nearly $80k in revenue since early February while operating on surprisingly low monthly costs. -------------- TIMESTAMPS 0:00 Intro 0.24 Nat’s Background 6:30 Felix 11:43 Real Businesses vs Memecoins 14:23 Felix’s Employees 18:06 Felix’s Business 31:26 How Customized is Felix? 38:17 Felix’s Business Risks 40:12 Can OpenClaw Replace Knowledge Workers? 43:38 Claw Mart 48:49 Felix’s Expenses 51:15 Nat’s Role 56:39 Felix’s Discord 1:03:19 Citrini Doomer Scenario 1:13:04 Hiring Your First Agent 1:16:19 General AI Assistants 1:19:50 AI Friends 1:22:39 The AI Agent Frontier 1:26:52 Crypto x AI 1:31:53 What’s Next 1:34:27 Closing & Disclaimers

Bankless

535,632 次观看 • 5 个月前

Nat Eliason’s (Nat Eliason) career arc is borderline absurd—but it works. He’ll spot a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with the note-taking wave ($600k in sales from a Roam Research course), real estate (6x return flipping property in Austin), and crypto (published his insider story with Random House). Now it’s AI: he’s running a viral course on building apps with AI—$200k in pre-sales in just a week, 800 students and counting. I’ve known Nat for a long time and I think he has a great sense for where the puck is headed. He was one of the first guests I had on the podcast and I was delighted to have him on again. Here are a few takeaways from our conversation: - Coding with AI has become orders of magnitude easier for non-technical people over the last 2 years—Nat rarely has to help students fix bugs; they troubleshoot in Cursor on their own. - AI coding assistants are creating new behaviours in programming, like using a speech-to-text model to talk to an agent and having it write code for you. - The traditional learning curve of coding is flattening because AI tools let beginners build and iterate in faster feedback loops. - AI has given Nat leverage in spades—it increases his ability to be a creator while also building a robust business with as few people to manage as possible. He demos an AI book editor he coded for his sci-fi novel. - In the age of AI, software is becoming content and the barriers to create are lower than ever—but custom software for everything isn’t the answer. Nat’s model is that personalized tools make sense for that one thing you care the most about. - Nat believes that the future of writing with AI is a Cursor-style interface with a model that’s trained on your style and voice. This episode is a must-watch for writers, creators, and anyone interested in the future of product building. Watch below! Timestamps: Introduction: 00:01:45 The origins of Nat’s viral course on building apps with AI: 00:11:45 How coding with AI has evolved over the last two years: 00:18:46 Nat creates an app using Composer, Cursor’s AI assistant: 00:22:22 Tactical tips for coding with Cursor: 00:26:06 How coding with AI is creating new behaviours in programming: 00:29:06 What excites Nat the most about the future of AI: 00:32:41 A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:38:58 When does it makes sense to build custom software: 00:44:52 Nat’s take on the future of writing with AI: 00:49:18
1:00:52

Nat Eliason’s (Nat Eliason) career arc is borderline absurd—but it works. He’ll spot a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with the note-taking wave ($600k in sales from a Roam Research course), real estate (6x return flipping property in Austin), and crypto (published his insider story with Random House). Now it’s AI: he’s running a viral course on building apps with AI—$200k in pre-sales in just a week, 800 students and counting. I’ve known Nat for a long time and I think he has a great sense for where the puck is headed. He was one of the first guests I had on the podcast and I was delighted to have him on again. Here are a few takeaways from our conversation: - Coding with AI has become orders of magnitude easier for non-technical people over the last 2 years—Nat rarely has to help students fix bugs; they troubleshoot in Cursor on their own. - AI coding assistants are creating new behaviours in programming, like using a speech-to-text model to talk to an agent and having it write code for you. - The traditional learning curve of coding is flattening because AI tools let beginners build and iterate in faster feedback loops. - AI has given Nat leverage in spades—it increases his ability to be a creator while also building a robust business with as few people to manage as possible. He demos an AI book editor he coded for his sci-fi novel. - In the age of AI, software is becoming content and the barriers to create are lower than ever—but custom software for everything isn’t the answer. Nat’s model is that personalized tools make sense for that one thing you care the most about. - Nat believes that the future of writing with AI is a Cursor-style interface with a model that’s trained on your style and voice. This episode is a must-watch for writers, creators, and anyone interested in the future of product building. Watch below! Timestamps: Introduction: 00:01:45 The origins of Nat’s viral course on building apps with AI: 00:11:45 How coding with AI has evolved over the last two years: 00:18:46 Nat creates an app using Composer, Cursor’s AI assistant: 00:22:22 Tactical tips for coding with Cursor: 00:26:06 How coding with AI is creating new behaviours in programming: 00:29:06 What excites Nat the most about the future of AI: 00:32:41 A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:38:58 When does it makes sense to build custom software: 00:44:52 Nat’s take on the future of writing with AI: 00:49:18

Dan Shipper 📧

27,207 次观看 • 1 年前

Texas private school’s use of new ‘AI tutor’ rockets student test scores to top 2% in the country | Nicholas Lanum, Fox News Alpha School co-founder Mackenzie Price says students are learning 'better' and 'faster' A Texas private school is seeing student test scores soar to new heights following the implementation of an artificial intelligence (AI) "tutor." At Alpha School in Austin, Texas, students are placed in the classroom for two hours a day with an AI assistant, using the rest of the day to focus on skills like public speaking, financial literacy, and teamwork. "We use an AI tutor and adaptive apps to provide a completely personalized learning experience for all of our students, and as a result our students are learning faster, they’re learning way better. In fact, our classes are in the top 2% in the country," Alpha School co-founder Mackenzie Price told "Fox & Friends." Elle Kristine, a junior at Alpha School, praised the educational institution and suggested its unique structure provides a substantial benefit over standard American learning frameworks. "I have a lot of friends at traditional school, and every day after school and during school, they’re doing so much homework, they’re spending all this time on schoolwork, they’re so stressed out, and they’re just miserable," Kristine said during an interview with co-host Ainsley Earhardt. The Alpha School junior revealed that she and other classmates finish their academics in three-hour blocks daily and spend the rest of their time working on "passion projects." In her case, Kristine is working on a safe AI dating coach for teenagers. "What 16-year-old has time for that? "So, it’s awesome," Kristine said. Alpha School in Texas currently has a few hundred students and is expanding across the United States. "What we’re finding is that families want this personalized education experience," Price said. It’s transforming the experience that kids have. But even more importantly, the role that teachers play." Read more:
3:50

Texas private school’s use of new ‘AI tutor’ rockets student test scores to top 2% in the country | Nicholas Lanum, Fox News Alpha School co-founder Mackenzie Price says students are learning 'better' and 'faster' A Texas private school is seeing student test scores soar to new heights following the implementation of an artificial intelligence (AI) "tutor." At Alpha School in Austin, Texas, students are placed in the classroom for two hours a day with an AI assistant, using the rest of the day to focus on skills like public speaking, financial literacy, and teamwork. "We use an AI tutor and adaptive apps to provide a completely personalized learning experience for all of our students, and as a result our students are learning faster, they’re learning way better. In fact, our classes are in the top 2% in the country," Alpha School co-founder Mackenzie Price told "Fox & Friends." Elle Kristine, a junior at Alpha School, praised the educational institution and suggested its unique structure provides a substantial benefit over standard American learning frameworks. "I have a lot of friends at traditional school, and every day after school and during school, they’re doing so much homework, they’re spending all this time on schoolwork, they’re so stressed out, and they’re just miserable," Kristine said during an interview with co-host Ainsley Earhardt. The Alpha School junior revealed that she and other classmates finish their academics in three-hour blocks daily and spend the rest of their time working on "passion projects." In her case, Kristine is working on a safe AI dating coach for teenagers. "What 16-year-old has time for that? "So, it’s awesome," Kristine said. Alpha School in Texas currently has a few hundred students and is expanding across the United States. "What we’re finding is that families want this personalized education experience," Price said. It’s transforming the experience that kids have. But even more importantly, the role that teachers play." Read more:

Owen Gregorian

101,492 次观看 • 1 年前

I’m an Alpha School parent. Earlier this year, my son was actually upset because a snow day meant he couldn’t go to school. I had to ask liemandt, "What have you done to him?" That question opened up a much bigger one. Austin’s experimental schools are pulling in families from across the country, and that talent gravity is reshaping the city’s innovation ecosystem faster than any corporate relocation. Joe built Trilogy and recruited 2,000 Ivy League kids to Austin in the ’90s. Now at Alpha, he sees this as the higher-leverage version of the same play. 30% of some campuses are families who moved here for schools that do not exist anywhere else. This one hits close to home for me. Both because I’m a parent inside the experiment and because it hints at something bigger happening in Austin. Agenda 0:00 Intro and the Alpha School model 5:44 Good AI versus bad AI in the classroom 11:43 Diagnostic shock and what gifted students miss 16:04 Motivation and life skills versus vocational skills 21:08 Students making real money with AI tools 23:39 Hiring guides at $100K 26:34 The selection effect and founding families 31:51 Running a school like a startup 36:07 Iterating in public 42:27 Motivational models that actually work 47:01 Teaching kids to fail 49:33 Austin as the education capital 55:02 Education as the 20-year talent pipeline 57:52 Millionaires in high school 1:04:37 What college becomes next
1:12:17

I’m an Alpha School parent. Earlier this year, my son was actually upset because a snow day meant he couldn’t go to school. I had to ask liemandt, "What have you done to him?" That question opened up a much bigger one. Austin’s experimental schools are pulling in families from across the country, and that talent gravity is reshaping the city’s innovation ecosystem faster than any corporate relocation. Joe built Trilogy and recruited 2,000 Ivy League kids to Austin in the ’90s. Now at Alpha, he sees this as the higher-leverage version of the same play. 30% of some campuses are families who moved here for schools that do not exist anywhere else. This one hits close to home for me. Both because I’m a parent inside the experiment and because it hints at something bigger happening in Austin. Agenda 0:00 Intro and the Alpha School model 5:44 Good AI versus bad AI in the classroom 11:43 Diagnostic shock and what gifted students miss 16:04 Motivation and life skills versus vocational skills 21:08 Students making real money with AI tools 23:39 Hiring guides at $100K 26:34 The selection effect and founding families 31:51 Running a school like a startup 36:07 Iterating in public 42:27 Motivational models that actually work 47:01 Teaching kids to fail 49:33 Austin as the education capital 55:02 Education as the 20-year talent pipeline 57:52 Millionaires in high school 1:04:37 What college becomes next

Jason Scharf

156,837 次观看 • 4 个月前

This is the definitive conversation on Alpha School with liemandt, who is the school’s principal and backer. What if kids could learn in two hours a day, test in the top 1% nationally, spend their afternoons mastering other great skills, AND love school more than vacation? What sounds impossible is already happening at Alpha. If you are a parent like me, it’s impossible not to wonder how to make sure your kids will benefit from this enormous innovation. We explore everything in exhaustive detail—the learning science, the role of software and AI, the central role of motivation, the challenges of scaling to ALL kids, and more. Joe is one of the most successful entrepreneurs in history, who has now decided to devote his next two decades to ushering in a new era of education. I hope this becomes a historically important episode. Timestamps: 0:00 Intro 0:54 What Is Alpha School? 4:02 The 200-Year Education Problem 8:06 Two-Hour Learning 16:41 Academic Results & Efficiency 23:51 AI-Generated Personalized Lessons 35:03 EdTech Fails Without Motivation 41:18 Life Skills & Afternoon Workshops 1:13:35 Gamification 1:29:09 Scaling Challenges 1:46:52 Video Games for Education 1:54:07 Joe's Background & Trilogy 2:14:22 Lessons from Mentors 2:32:29 The Kindest Thing
2:35:15

This is the definitive conversation on Alpha School with liemandt, who is the school’s principal and backer. What if kids could learn in two hours a day, test in the top 1% nationally, spend their afternoons mastering other great skills, AND love school more than vacation? What sounds impossible is already happening at Alpha. If you are a parent like me, it’s impossible not to wonder how to make sure your kids will benefit from this enormous innovation. We explore everything in exhaustive detail—the learning science, the role of software and AI, the central role of motivation, the challenges of scaling to ALL kids, and more. Joe is one of the most successful entrepreneurs in history, who has now decided to devote his next two decades to ushering in a new era of education. I hope this becomes a historically important episode. Timestamps: 0:00 Intro 0:54 What Is Alpha School? 4:02 The 200-Year Education Problem 8:06 Two-Hour Learning 16:41 Academic Results & Efficiency 23:51 AI-Generated Personalized Lessons 35:03 EdTech Fails Without Motivation 41:18 Life Skills & Afternoon Workshops 1:13:35 Gamification 1:29:09 Scaling Challenges 1:46:52 Video Games for Education 1:54:07 Joe's Background & Trilogy 2:14:22 Lessons from Mentors 2:32:29 The Kindest Thing

Patrick OShaughnessy

1,903,298 次观看 • 11 个月前

I sat down with Nicolas Sharp, founder of Attio, to talk in depth about how his company is disrupting the $80 billion CRM market. Attio has raised $116m, is 4x'ing ARR and is one of the fastest growing companies in Europe. We talk about: - Why Attio went against all conventional wisdom and spent years 3 years building the product before launching - Why Attio doesn’t hire ‘Software Engineers’ and who they hire instead. - How Attio chose investors who would back a long-term bet against multi-billion $ incumbents - How Attio is building CRM from first principles for the AI era - Who should you avoid hiring at all costs, and who should you hire for your startup And so much more. If you’re interested in learning about the story of how Nick built Attio into the incredible company it is today and is disrupting one of the most important software categories, you’re going to want to see this. Enjoy // Timestamps 00:00 Intro 00:39 Why Attio spent 3 years building their product before launch 5:05 The Power of Building Systems, Not a Box of Features 9:05 How to know when it’s time to launch 13:30 Nick’s Playbook For a Killer Product Launch 18:09 How To Go From an Investor to a Founder 23:05 How Failure Led to Attio's Big Break 28:07 Why startups need to hire "Hidden Gems," 34:05 Fundraising 49:36 Why Attio Invests In Inexperienced Talent 55:07 The Case For Not Hiring Software Engineers (& Who You Should Hire Instead) 1:02:46 The 8 Persona Hiring Framework 1:09:05 How Attio doesn’t use OKR's 1:27:11 Where does Nick's Ambition and Grit come from? 1:36:59 How Attio is Building CRM from First Principles for the AI era 1:45:29 How to Successfully Market In A Crowded Industry 1:51:10 Breaking Down Attio’s Viral Marketing Strategies 2:02:15 The Change That Had The Biggest Impact on Customer Conversion 2:05:04 Why Attio created A “Reverse Trial” 2:10:16 Why Nick is building from London, not Silicon Valley 2:22:48 The 10-Year Vision for Attio
2:26:34

I sat down with Nicolas Sharp, founder of Attio, to talk in depth about how his company is disrupting the $80 billion CRM market. Attio has raised $116m, is 4x'ing ARR and is one of the fastest growing companies in Europe. We talk about: - Why Attio went against all conventional wisdom and spent years 3 years building the product before launching - Why Attio doesn’t hire ‘Software Engineers’ and who they hire instead. - How Attio chose investors who would back a long-term bet against multi-billion $ incumbents - How Attio is building CRM from first principles for the AI era - Who should you avoid hiring at all costs, and who should you hire for your startup And so much more. If you’re interested in learning about the story of how Nick built Attio into the incredible company it is today and is disrupting one of the most important software categories, you’re going to want to see this. Enjoy // Timestamps 00:00 Intro 00:39 Why Attio spent 3 years building their product before launch 5:05 The Power of Building Systems, Not a Box of Features 9:05 How to know when it’s time to launch 13:30 Nick’s Playbook For a Killer Product Launch 18:09 How To Go From an Investor to a Founder 23:05 How Failure Led to Attio's Big Break 28:07 Why startups need to hire "Hidden Gems," 34:05 Fundraising 49:36 Why Attio Invests In Inexperienced Talent 55:07 The Case For Not Hiring Software Engineers (& Who You Should Hire Instead) 1:02:46 The 8 Persona Hiring Framework 1:09:05 How Attio doesn’t use OKR's 1:27:11 Where does Nick's Ambition and Grit come from? 1:36:59 How Attio is Building CRM from First Principles for the AI era 1:45:29 How to Successfully Market In A Crowded Industry 1:51:10 Breaking Down Attio’s Viral Marketing Strategies 2:02:15 The Change That Had The Biggest Impact on Customer Conversion 2:05:04 Why Attio created A “Reverse Trial” 2:10:16 Why Nick is building from London, not Silicon Valley 2:22:48 The 10-Year Vision for Attio

Wouter Teunissen

26,369 次观看 • 10 个月前

"If you just compound and stack day after day after day and give it your best, great things will happen. That's been the story of my life and the story of this business." Garrett Lord. Founder & CEO of Handshake. At a Christmas party in December 2024, Garrett met a researcher from a frontier AI lab who told him about the challenges of model training. Two weeks later, Garrett's company Handshake was recruiting STEM PhDs for that same lab. Fifteen months after that, Handshake AI had gone from zero to a billion dollars in gross annualized revenue, and now is the human data engine behind the frontier labs. This conversation is a dissection of the most audacious reinvention in tech. Knuckle Up ↓ -- 00:00 Who is Garrett Lord? 01:36 How did a Christmas party conversation spark Handshake AI? 11:59 How do you tell your execs and board you're refounding the company? 18:18 What keeps A players motivated in the core business? 22:22 Olympic Pace: why did around 100 team members leave Handshake? 27:02 What broke first going zero to a billion in a year? 31:45 How do you protect quality when 85% of the company is new? 39:36 Why hasn't Garrett upgraded a single exec? 49:00 What does the bear case on human data get wrong? 53:30 How do you make accounting verifiable enough for reinforcement learning? 1:00:08 Will enterprises leave the labs for open source? 1:07:13 What does all this mean for knowledge workers? 1:08:51 The inner game: how is Garrett holding it all together? 1:14:22 What's the mission in this new chapter? 1:18:27 Will vertical AI apps survive the frontier labs? 1:21:23 Quickfire: red flags, overrated advice, jobs of the future
1:24:39

"If you just compound and stack day after day after day and give it your best, great things will happen. That's been the story of my life and the story of this business." Garrett Lord. Founder & CEO of Handshake. At a Christmas party in December 2024, Garrett met a researcher from a frontier AI lab who told him about the challenges of model training. Two weeks later, Garrett's company Handshake was recruiting STEM PhDs for that same lab. Fifteen months after that, Handshake AI had gone from zero to a billion dollars in gross annualized revenue, and now is the human data engine behind the frontier labs. This conversation is a dissection of the most audacious reinvention in tech. Knuckle Up ↓ -- 00:00 Who is Garrett Lord? 01:36 How did a Christmas party conversation spark Handshake AI? 11:59 How do you tell your execs and board you're refounding the company? 18:18 What keeps A players motivated in the core business? 22:22 Olympic Pace: why did around 100 team members leave Handshake? 27:02 What broke first going zero to a billion in a year? 31:45 How do you protect quality when 85% of the company is new? 39:36 Why hasn't Garrett upgraded a single exec? 49:00 What does the bear case on human data get wrong? 53:30 How do you make accounting verifiable enough for reinforcement learning? 1:00:08 Will enterprises leave the labs for open source? 1:07:13 What does all this mean for knowledge workers? 1:08:51 The inner game: how is Garrett holding it all together? 1:14:22 What's the mission in this new chapter? 1:18:27 Will vertical AI apps survive the frontier labs? 1:21:23 Quickfire: red flags, overrated advice, jobs of the future

Nakul Mandan

330,468 次观看 • 26 天前

I interviewed a guy who gave his OpenClaw an X, stripe account, and bank account. He told it to build a million dollar business with zero human employees. It made $300K+ in a month. Nat Eliason's agent Felix (Felix Craft) runs an entire business. It builds products, writes sales emails, sends stripe invoices, manages a marketplace with 560+ listings and nat barely touches it. Here's how they got there: 1) create a separate container. Felix has his own gmail, X account, stripe, bank account, C corp. nat never gave it access to his personal stuff. this removes security fears and unlocks maximum autonomy. 2) start stupidly simple. Felix's first product? a PDF. on a Nextjs site on Vercel with Stripe. the simplest business possible. it made $1,000 on day one. built entirely overnight while nat slept. 3) write a soul file with a mission. nat rewrote Felix's identity: "you are the CEO. your financial mission is to build a $1M business with zero human employees. i will never touch the code." 4) run a nightly self-improvement loop. every night Felix reads through all chat transcripts and finds one place where nat blocked him. then figures out how to remove that blocker permanently. 5) delegate by rambling, not prompting. nat uses voice notes on telegram. describes the problem in a 5-minute monologue. lets Felix figure out the workflow. "8 times out of 10, it'll surprise you with something better than what you were thinking." 6) let it cook on replies, gate the original posts. Felix has full autonomy on X replies but creates drafts for top-level tweets nat reviews. balances distribution with quality control.
51:20

I interviewed a guy who gave his OpenClaw an X, stripe account, and bank account. He told it to build a million dollar business with zero human employees. It made $300K+ in a month. Nat Eliason's agent Felix (Felix Craft) runs an entire business. It builds products, writes sales emails, sends stripe invoices, manages a marketplace with 560+ listings and nat barely touches it. Here's how they got there: 1) create a separate container. Felix has his own gmail, X account, stripe, bank account, C corp. nat never gave it access to his personal stuff. this removes security fears and unlocks maximum autonomy. 2) start stupidly simple. Felix's first product? a PDF. on a Nextjs site on Vercel with Stripe. the simplest business possible. it made $1,000 on day one. built entirely overnight while nat slept. 3) write a soul file with a mission. nat rewrote Felix's identity: "you are the CEO. your financial mission is to build a $1M business with zero human employees. i will never touch the code." 4) run a nightly self-improvement loop. every night Felix reads through all chat transcripts and finds one place where nat blocked him. then figures out how to remove that blocker permanently. 5) delegate by rambling, not prompting. nat uses voice notes on telegram. describes the problem in a 5-minute monologue. lets Felix figure out the workflow. "8 times out of 10, it'll surprise you with something better than what you were thinking." 6) let it cook on replies, gate the original posts. Felix has full autonomy on X replies but creates drafts for top-level tweets nat reviews. balances distribution with quality control.

Alex Lieberman

953,025 次观看 • 5 个月前

Episode #108: How to Generate Alpha in Venture Albert Azout started and runs Level Ventures, a data-driven Fund of Funds backing emerging managers. Venture investing is hard, and this conversation covers all their research unpacking exactly how to generate alpha. We also talk about how Level picks and backs emerging venture managers to invest in, and Albert demoes the custom software they’ve built internally to do so. Thank you to Ramp and for supporting this episode. And to Jake Kupperman, Sasha Kaletsky, Nathan Benaich, Robby, and Dave Font for helping brainstorm topics! Full episode here on X, or grab a link in the replies. Timestamps: 5:01 Top 3 forms of alpha in VC 10:11 Other ways to generate alpha 12:47 Avoiding false positives 17:11 Optimal fund size and portfolio construction 22:25 The role of Luck 23:55 Spin-out vs outsider funds 25:43 Level’s backchannel reference process 29:29 Finding alpha in Criticality Investing 34:45 Why capital flows drive all returns 43:53 Early, consensus investing has the most alpha 48:46 Networks are more persistent than performance 52:03 The strongest and weakest networks 58:41 Demo of Level’s internal software 1:04:48 Building a Fund of Funds around their data 1:10:01 Ideal LP GP relationship 1:12:39 Benchmarks are relative 1:15:39 VC funds using AI 1:17:43 How venture will change in the next 10 years
1:20:56

Episode #108: How to Generate Alpha in Venture Albert Azout started and runs Level Ventures, a data-driven Fund of Funds backing emerging managers. Venture investing is hard, and this conversation covers all their research unpacking exactly how to generate alpha. We also talk about how Level picks and backs emerging venture managers to invest in, and Albert demoes the custom software they’ve built internally to do so. Thank you to Ramp and for supporting this episode. And to Jake Kupperman, Sasha Kaletsky, Nathan Benaich, Robby, and Dave Font for helping brainstorm topics! Full episode here on X, or grab a link in the replies. Timestamps: 5:01 Top 3 forms of alpha in VC 10:11 Other ways to generate alpha 12:47 Avoiding false positives 17:11 Optimal fund size and portfolio construction 22:25 The role of Luck 23:55 Spin-out vs outsider funds 25:43 Level’s backchannel reference process 29:29 Finding alpha in Criticality Investing 34:45 Why capital flows drive all returns 43:53 Early, consensus investing has the most alpha 48:46 Networks are more persistent than performance 52:03 The strongest and weakest networks 58:41 Demo of Level’s internal software 1:04:48 Building a Fund of Funds around their data 1:10:01 Ideal LP GP relationship 1:12:39 Benchmarks are relative 1:15:39 VC funds using AI 1:17:43 How venture will change in the next 10 years

The Peel

28,819 次观看 • 11 个月前

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self
1:45:40

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self

Matt Turck

86,153 次观看 • 1 年前

Episode #92: How AI Changes Governments & Business Models Mike Vichich is the Co-founder and CEO of Pursuit, which helps companies drive more revenue from the public sector. We talk about how AI is changing Helmer’s 7 Powers, how it’s impacting the government, if DOGE is actually working, building a startup in the Midwest (specifically Ann Arbor, MI), and how to disagree with your team. We also get into Mike’s prior company Wisely, and how they went from $11 in the bank account and unable to run payroll for six months, to over $10 million ARR and a $187 million exit to public company Olo a few years later. Thanks to Jack Altman and Blake Robbins for their help brainstorming good topics for Mike! Full episode here on X, or grab a link in the replies. Timestamps: 3:21 How AI changes Helmer’s 7 Powers 17:06 What becomes important in AI-first economy 21:02 How AI interfaces with the government 24:02 “The rules intended to save taxpayer money ironically cause taxpayer money to be wasted” 29:34 How change orders impact public sector costs 33:20 Why DOGE has not impacted US government spending yet 38:15 Three pieces of wisdom from 2nd-time founders 41:44 Starting Pursuit to make selling to the public sector as easy as the private sector 45:35 Why cities grow expenses 5x faster than tax revenue 51:42 Pros + Cons of building startups in Ann Arbor, MI 57:43 Hiring talent density in the Midwest 59:30 Starting his first company to fix consumer credit cards 1:08:50 Pivoting Wisely to restaurant loyalty 1:12:49 $11 in the bank, missing payroll for six months 1:15:21 Embarrassing demo at an Ann Arbor tech meetup 1:18:18 Why CEOs don’t always have to be right 1:20:54 How to disagree 1:25:48 Hiring at Pursuit 1:28:30 “A bad day with customers is better than the best day in the office” 1:31:33 Crashing their first customer’s PoS on Labor Day Weekend 1:35:55 Using “The Cadence” to hit $10M ARR 1:41:55 Selling Wisely to Olo for $187M
1:47:04

Episode #92: How AI Changes Governments & Business Models Mike Vichich is the Co-founder and CEO of Pursuit, which helps companies drive more revenue from the public sector. We talk about how AI is changing Helmer’s 7 Powers, how it’s impacting the government, if DOGE is actually working, building a startup in the Midwest (specifically Ann Arbor, MI), and how to disagree with your team. We also get into Mike’s prior company Wisely, and how they went from $11 in the bank account and unable to run payroll for six months, to over $10 million ARR and a $187 million exit to public company Olo a few years later. Thanks to Jack Altman and Blake Robbins for their help brainstorming good topics for Mike! Full episode here on X, or grab a link in the replies. Timestamps: 3:21 How AI changes Helmer’s 7 Powers 17:06 What becomes important in AI-first economy 21:02 How AI interfaces with the government 24:02 “The rules intended to save taxpayer money ironically cause taxpayer money to be wasted” 29:34 How change orders impact public sector costs 33:20 Why DOGE has not impacted US government spending yet 38:15 Three pieces of wisdom from 2nd-time founders 41:44 Starting Pursuit to make selling to the public sector as easy as the private sector 45:35 Why cities grow expenses 5x faster than tax revenue 51:42 Pros + Cons of building startups in Ann Arbor, MI 57:43 Hiring talent density in the Midwest 59:30 Starting his first company to fix consumer credit cards 1:08:50 Pivoting Wisely to restaurant loyalty 1:12:49 $11 in the bank, missing payroll for six months 1:15:21 Embarrassing demo at an Ann Arbor tech meetup 1:18:18 Why CEOs don’t always have to be right 1:20:54 How to disagree 1:25:48 Hiring at Pursuit 1:28:30 “A bad day with customers is better than the best day in the office” 1:31:33 Crashing their first customer’s PoS on Labor Day Weekend 1:35:55 Using “The Cadence” to hit $10M ARR 1:41:55 Selling Wisely to Olo for $187M

The Peel

27,474 次观看 • 1 年前

Launching a new podcast today! Filmed at our NYC office, each episode of The Archive focuses on a founder or operator who has built an important crypto business/protocol. The first episode is with Keone Hon, founder of Monad. We dive into Keone’s upbringing, the early days of Monad and the journey to raising the seed round. Plus, we talk about recruiting + scaling the team, and the philosophies they used to launch and grow the network. Here's what we discussed: 0:00 - Intro 0:42 - Altitude 1:32 - Monad's Launch 4:25 - Keone’s early life and interests 16:52 - Where Keone’s work ethic came from 19:52 - Working at Jump and how the culture passed on to Monad 24:26 - Starting Monad 30:05 - Raising the seed round for Monad 32:29 - Growing the Monad community and open-sourcing code 36:35 - How Keone hired for the early team 44:07 - The future of Category Labs 51:26 - Which metrics is Monad focusing on 1:00:24 - Building a base of loyal and passionate users 1:07:45 - The personality of an L1 founder 1:13:46 - Founders that Keone looks up to 1:18:34 - Day in the life of Keone 1:23:57 - The endgame vision for Monad
1:26:31

Launching a new podcast today! Filmed at our NYC office, each episode of The Archive focuses on a founder or operator who has built an important crypto business/protocol. The first episode is with Keone Hon, founder of Monad. We dive into Keone’s upbringing, the early days of Monad and the journey to raising the seed round. Plus, we talk about recruiting + scaling the team, and the philosophies they used to launch and grow the network. Here's what we discussed: 0:00 - Intro 0:42 - Altitude 1:32 - Monad's Launch 4:25 - Keone’s early life and interests 16:52 - Where Keone’s work ethic came from 19:52 - Working at Jump and how the culture passed on to Monad 24:26 - Starting Monad 30:05 - Raising the seed round for Monad 32:29 - Growing the Monad community and open-sourcing code 36:35 - How Keone hired for the early team 44:07 - The future of Category Labs 51:26 - Which metrics is Monad focusing on 1:00:24 - Building a base of loyal and passionate users 1:07:45 - The personality of an L1 founder 1:13:46 - Founders that Keone looks up to 1:18:34 - Day in the life of Keone 1:23:57 - The endgame vision for Monad

Derek Hsue

69,907 次观看 • 6 个月前

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team
1:13:20

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team

Grant

167,546 次观看 • 1 个月前

New The Peel with University of Michigan professor Karthik Duraisamy Karthik co-leads U of M's newly created Institute of Agentic Computing. It's a central node for the OpenClaw platform and helps researchers and developers using AI to advance scientific discovery and engineering. This is Karthik's first public conversation going deep on the new institute. We talk about how AI has increased the pace of scientific research, two new discoveries announced yesterday at ClawCon in Ann Arbor, how universities actually work, how AI has impacted students and education, what's happening with college grade inflation, and the code red advice he gave students. Thank you to Numeral, Flex, and Amplitude for supporting this episode! Timestamps: 0:25 The Institute for Agentic Computing 4:27 OpenClaw Foundation and Lobster Compute Company 8:19 How Universities actually work 12:33 ClawCon in Ann Arbor 15:24 Two scientific discoveries made with ScienceClaw 20:06 How AI is speeding up scientific discovery 25:42 Supporting AI and OpenClaw development 29:55 Why universities function like VC funds 34:29 How universities get money from the government 40:55 Why some academics believe AI is a fad 46:17 Biggest bottlenecks in AI today 49:26 How AI will change the world 53:10 Karthik's Code Red advice for students 59:19 Separating learning and doing 1:03:10 Ways COVID and AI impacted college students 1:14:53 How the role of universities is changing 1:23:21 Why college classes suffered from grade inflation 1:26:05 How AI is actually impacting the job market 1:32:49 Karthik’s advice for students 1:39:16 Winning two NCAA basketball national championships 1:43:04 Almost dying in the Grand Teton National Park
1:48:30

New The Peel with University of Michigan professor Karthik Duraisamy Karthik co-leads U of M's newly created Institute of Agentic Computing. It's a central node for the OpenClaw platform and helps researchers and developers using AI to advance scientific discovery and engineering. This is Karthik's first public conversation going deep on the new institute. We talk about how AI has increased the pace of scientific research, two new discoveries announced yesterday at ClawCon in Ann Arbor, how universities actually work, how AI has impacted students and education, what's happening with college grade inflation, and the code red advice he gave students. Thank you to Numeral, Flex, and Amplitude for supporting this episode! Timestamps: 0:25 The Institute for Agentic Computing 4:27 OpenClaw Foundation and Lobster Compute Company 8:19 How Universities actually work 12:33 ClawCon in Ann Arbor 15:24 Two scientific discoveries made with ScienceClaw 20:06 How AI is speeding up scientific discovery 25:42 Supporting AI and OpenClaw development 29:55 Why universities function like VC funds 34:29 How universities get money from the government 40:55 Why some academics believe AI is a fad 46:17 Biggest bottlenecks in AI today 49:26 How AI will change the world 53:10 Karthik's Code Red advice for students 59:19 Separating learning and doing 1:03:10 Ways COVID and AI impacted college students 1:14:53 How the role of universities is changing 1:23:21 Why college classes suffered from grade inflation 1:26:05 How AI is actually impacting the job market 1:32:49 Karthik’s advice for students 1:39:16 Winning two NCAA basketball national championships 1:43:04 Almost dying in the Grand Teton National Park

Turner Novak 🍌🧢

113,419 次观看 • 4 个月前

Full conversation with Luke Alexander on the real reason he shut down his business to bootstrap an AI SaaS. 0:00 Where It Started 4:39 No Internet Rural Ohio 7:21 Leaving Home to Save His Family 9:13 Dropping Out With $500 11:08 Cold DMing His First Client 13:14 Family Responsibility and What Drives Him 16:21 Why Anxiety Doesn't Exist 19:14 Suffering Is the Only Real Skill 21:18 Shutting Down the Agency 25:30 Moving to Miami With 15K 27:08 Launching Closer Cartel 70K Month One 31:01 The Character He Had to Play 33:08 The $12K Car and the Info Meta 36:48 Idols Becoming Brothers 40:06 Retiring His Mom First Million 41:41 His Dad the Restraining Order 43:20 The Man Who Stepped In 47:15 Burnout and Losing the Passion 50:16 The Moment He Walked Away 53:28 Why Info Rewards the Wrong Behavior 56:02 Spiritual Warfare in Miami 1:04:29 Living in Alignment 1:07:56 What He Wants to Look Back On 1:12:18 Why He Built Kindo 1:17:32 The Real Moat Is Taste 1:20:03 Learning Enterprise Sales 1:23:43 Bootstrapping vs Raising 1:26:03 How Kindo Works 1:29:05 AI Will Replace Sales Reps 1:36:09 Genetics and the Real Red Pill 1:39:53 Vision at 30 1:46:13 What It Means to Be a Good Dad 1:49:46 Looking for a Unicorn in Miami 1:51:29 Final Words
1:54:02

Full conversation with Luke Alexander on the real reason he shut down his business to bootstrap an AI SaaS. 0:00 Where It Started 4:39 No Internet Rural Ohio 7:21 Leaving Home to Save His Family 9:13 Dropping Out With $500 11:08 Cold DMing His First Client 13:14 Family Responsibility and What Drives Him 16:21 Why Anxiety Doesn't Exist 19:14 Suffering Is the Only Real Skill 21:18 Shutting Down the Agency 25:30 Moving to Miami With 15K 27:08 Launching Closer Cartel 70K Month One 31:01 The Character He Had to Play 33:08 The $12K Car and the Info Meta 36:48 Idols Becoming Brothers 40:06 Retiring His Mom First Million 41:41 His Dad the Restraining Order 43:20 The Man Who Stepped In 47:15 Burnout and Losing the Passion 50:16 The Moment He Walked Away 53:28 Why Info Rewards the Wrong Behavior 56:02 Spiritual Warfare in Miami 1:04:29 Living in Alignment 1:07:56 What He Wants to Look Back On 1:12:18 Why He Built Kindo 1:17:32 The Real Moat Is Taste 1:20:03 Learning Enterprise Sales 1:23:43 Bootstrapping vs Raising 1:26:03 How Kindo Works 1:29:05 AI Will Replace Sales Reps 1:36:09 Genetics and the Real Red Pill 1:39:53 Vision at 30 1:46:13 What It Means to Be a Good Dad 1:49:46 Looking for a Unicorn in Miami 1:51:29 Final Words

Grant

33,376 次观看 • 3 个月前

Episode #96: How to Skip Your Seed Round, Pre-Seed Lessons Building Afore to $500M+ AUM | Anamitra Banerji anamitra started Afore Capital with Gaurav Jain in 2016 to kickstart the Pre-Seed category. This conversation gets into its evolution as a funding stage, why its more than option checks, what Afore looks for when backing founders before they even have a product, how to skip your Seed and go straight to a Series A, and how to run a fundraise process. We also get into Afore’s Founder in Residence program, why every VC started an accelerator, how AI is changing venture, joining Twitter as the first PM, and how Oprah helped create the legendary verified checkmark. Thanks to Gaurav Jain and Derrick Li at Afore for their help brainstorming topics for Anamitra. And special thanks to bolt.new and Gabriella Warp for supporting this episode. Full episode here on X, or grab a link in the replies. Timestamps: 4:00 Afore: Starting in 2016 to build the pre-seed category 8:11 The unstructured data Afore underwrites at pre-seed 11:21 Pre-seed is determining bronze from gold 16:03 Why pre-seed is more than option checks 20:33 The secret to raising a Series A 23:20 Running a tight fundraise process 32:05 Skipping your Seed round 34:01 How to measure obsession in a founder 39:20 Knowing when to follow-on 40:54 Figuring out what really matters in a business 42:36 Afore’s Founder in Residence program 49:44 Pros / Cons of more access to capital for founders 52:27 Two reasons YC made every VC launch an accelerator 1:01:05 Why AI is forcing VCs to invest earlier 1:06:55 Will AI commoditize software? 1:08:29 Growing up in India, starting his first company 1:10:39 Coming to the US for school, joining Overture + Yahoo 1:14:05 Joining Twitter as first PM, creating the Verified check for Oprah 1:18:55 Building Twitter’s first ad product 1:20:28 Why non-founders can’t take foundational risks 1:23:02 Starting Afore for the Pre-Seed opportunity 1:27:47 Raising Afore Fund 1 1:31:14 How to raise your first fund 1:33:33 Was Turner the best Afore intern ever?
1:35:56

Episode #96: How to Skip Your Seed Round, Pre-Seed Lessons Building Afore to $500M+ AUM | Anamitra Banerji anamitra started Afore Capital with Gaurav Jain in 2016 to kickstart the Pre-Seed category. This conversation gets into its evolution as a funding stage, why its more than option checks, what Afore looks for when backing founders before they even have a product, how to skip your Seed and go straight to a Series A, and how to run a fundraise process. We also get into Afore’s Founder in Residence program, why every VC started an accelerator, how AI is changing venture, joining Twitter as the first PM, and how Oprah helped create the legendary verified checkmark. Thanks to Gaurav Jain and Derrick Li at Afore for their help brainstorming topics for Anamitra. And special thanks to bolt.new and Gabriella Warp for supporting this episode. Full episode here on X, or grab a link in the replies. Timestamps: 4:00 Afore: Starting in 2016 to build the pre-seed category 8:11 The unstructured data Afore underwrites at pre-seed 11:21 Pre-seed is determining bronze from gold 16:03 Why pre-seed is more than option checks 20:33 The secret to raising a Series A 23:20 Running a tight fundraise process 32:05 Skipping your Seed round 34:01 How to measure obsession in a founder 39:20 Knowing when to follow-on 40:54 Figuring out what really matters in a business 42:36 Afore’s Founder in Residence program 49:44 Pros / Cons of more access to capital for founders 52:27 Two reasons YC made every VC launch an accelerator 1:01:05 Why AI is forcing VCs to invest earlier 1:06:55 Will AI commoditize software? 1:08:29 Growing up in India, starting his first company 1:10:39 Coming to the US for school, joining Overture + Yahoo 1:14:05 Joining Twitter as first PM, creating the Verified check for Oprah 1:18:55 Building Twitter’s first ad product 1:20:28 Why non-founders can’t take foundational risks 1:23:02 Starting Afore for the Pre-Seed opportunity 1:27:47 Raising Afore Fund 1 1:31:14 How to raise your first fund 1:33:33 Was Turner the best Afore intern ever?

The Peel

19,063 次观看 • 1 年前