What does it take to spot a generational founder before there’s a product, revenue, or even a fully formed company?

Jeffrey Becker has built his career around that question. As General Partner at Antler, he co-leads the firm’s US Fund from New York, backing founders at inception through Antler’s day-zero, residency-based pre-seed model. With 27 offices globally, roughly 1,900 portfolio companies, and standout names like Lovable, Airalo, Micro1, and Pixverse, Antler is making a bold bet: the best time to understand a founder is before the startup noise begins.

Before Antler, Jeff spent nine years at LinkedIn during its hypergrowth era, holding nine roles across sales and leadership as the company scaled from post-IPO momentum into one of the defining platforms of the modern internet. That experience shaped how he thinks about culture, focus, communication, and what separates high-performing teams from average ones.

In Today's Episode We Discuss:

00:01 - Introducing Jeffrey Becker and Antler’s Day-Zero Model

00:57 - Jeff’s Origin Story: Competition, Sales, LinkedIn, and Angel Investing

03:48 - Backing Maniacs at Inception

04:33 - Lessons from LinkedIn’s Hypergrowth Era

05:58 - Why Jeff Tells People Not to Become VCs

08:22 - How Antler Works Before a Company Exists

10:54 - Why Antler Increased Its Check Size to $600K

12:49 - How Antler Differs from YC and Traditional Accelerators

14:52 - Antler’s Global Founder Funnel and Selection Process

16:05 - How Founders Can Stand Out in an AI-Generated Pitch World

18:43 - Why “I Want to Build a Billion-Dollar Company” Can Be a Red Flag

21:57 - The Magic of Founders Doing Their Life’s Work

23:00 - Risk, Diversification, and the Math of Inception Investing

24:30 - Why More Early-Stage Bets Can Improve Venture Outcomes

26:40 - Using SPVs and Follow-On Capital to Double Down on Winners

29:03 - The LP Retreat and the Future of Emerging Managers

30:56 - How AI Is Collapsing the Cost of Building Startups

32:44 - Agentic Company Builders and the Limits of AI-Generated Startups

34:24 - Jeff’s Content Engine: Substack, Podcasts, and AI Workflows

36:35 - The Hidden Risk of Overfunding and High Valuations

38:42 - Boards, Governance, and Staying Aligned with Founders

40:31 - Antler Founders Who Redefined What a Maniac Looks Like

43:12 - Why Meeting Great Founders Keeps VCs in the Game

45:06 - The Sharpest Writing in Venture Today

46:26 - The Best Advice Jeff Lives By: Be Different to Be Better

47:48 - A Cold Intro That Turned Into a Standout Founder Bet

50:15 - The Most Overrated Metric in Pre-Seed Venture

53:14 - Why Jeff Changed His Mind on Valuation Discipline

54:18 - Breaking Rules to Avoid Missing Generational Founders

Pull quotes:

“Don’t do VC unless I can’t talk you out of it.”

“To be better than average, you have to be different.”

Jeff’s story started with competition—as a younger brother, athlete, sales leader, founder, and angel investor. Today, that same instinct shows up in how he evaluates founders: not by who looks polished on paper, but by who is wired to keep going when the game gets brutal.

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Jonathan David Nelson has lived a stranger founder journey than most: missionary kid in Latin America, trauma nurse, software engineer, founder community builder, and now capital markets contrarian. After building Hackers and Founders from a bar meetup into a global startup community, Jonathan now runs HF Capital—an AI-native investment bank focused on IPOs, secondaries, and M&A.

In this episode, Jonathan breaks down why he believes the U.S. public markets are failing most companies below decacorn scale, why the London Stock Exchange may be a better path for growth-stage startups than another brutal private round, and how AI could rebuild the infrastructure behind investment banking.

In Today's Episode We Discuss:

00:01 - Introduction to Jonathan David Nelson and HF Capital

01:23 - From Missionary Kid in Latin America to Trauma Nurse

03:10 - How Hackers and Founders Started as a Bar Meetup

04:26 - Why Fundraising Is a Brute Force Algorithm

05:37 - Understanding Capital Flow Like Blood Flow

08:15 - Advising the SEC and the Limits of Crowdfunding

09:40 - Why Startup Exits Remain the Broken Piece

10:47 - Why U.S. Public Markets Fail Smaller Companies

13:02 - The Origin of HF Capital and Tokenized Stock

15:26 - Discovering the London Stock Exchange Alternative

17:05 - Lower IPO Costs, Sponsor Banks, and Less Litigation

19:23 - Why Founders Still Default to U.S. Markets

21:19 - The “50 and 50” Growth-Stage Startup Profile

24:28 - When an IPO May Not Be the Right Move

26:34 - SPACs Explained and Why They Often Collapse

30:32 - Private Rounds vs. IPOs for Growth-Stage Companies

31:37 - Liquidation Preferences and Founder Dilution

35:24 - Why Boards Resist Alternative IPO Paths

36:23 - Capital Markets as a “Capital API”

38:02 - Building an AI-Native Investment Bank

40:14 - Why HF Capital Is Becoming the Bank, Not Just Selling Software

41:11 - The Coming Explosion of Smaller AI-Native Startups

42:26 - Secondaries, Latin America, and Undervalued Growth Companies

44:39 - What Startup Secondaries Actually Are

45:30 - Anthropic Hype, SPVs, and Risky Secondary Deals

47:13 - Custody, Forward Contracts, and Secondary Market Due Diligence

Jonathan is blunt, funny, and allergic to sacred cows. His view is simple: venture, IPOs, secondaries, and capital formation are not laws of nature. They are systems. And broken systems can be hacked.

Pull quote: “The system is broken, must fix. The ecosystem is sick, must heal.”

Pull quote: “I think of capital markets, stock markets as a capital API.”

From wiping asses and saving lives in the ER to reengineering how founders access liquidity, Jonathan’s story is a reminder that sometimes the best person to fix finance is the outsider who never agreed to pretend it made sense.

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What does a founder learn after selling four companies, burning one to the ground, and spending years building AI agents before “AI agents” became the phrase of the moment?

Dennis Mortensen has the scars to answer that. A Danish-born, New York-based serial founder, Dennis has built and exited companies across analytics, media optimization, and AI, including X.ai, the AI scheduling assistant that raised $44 million from FirstMark and others before being acquired by Bizzabo in 2021. Today, he is building LaunchBrightly, a company automating product screenshots for help centers—a problem that sounds painfully unsexy until you realize every software company has it, every product team pays for it, and every outdated screenshot quietly creates support debt.

In this episode, Dennis joins Brian Bell for a wide-ranging masterclass on founder judgment, painful pivots, and the unglamorous infrastructure problems that make or break software companies.

In Today's Episode We Discuss:

00:01 – Meet Dennis Mortensen

01:25 – From IBM Dreams to Serial Founder

03:51 – Selling His First Company During the Dot-Com Era

05:00 – Building in Budapest and Moving to New Yor

07:08 – Why European Founders Look West

09:25 – The “Expensive MBA” Startup Failure

11:52 – Why Dramatic Pivots Are Overrated

13:51 – The Marketplace Mistake That Killed the Business

16:27 – When the Market Is Telling You You’re Wrong

18:23 – The Twitter Pivot and Founder Mythology

20:46 – Why Business Model Flexibility Matters

22:35 – Founder Bias, Persistence, and Not Dying

24:30 – Shutting Down and Moving On

26:34 – Building IndexTools and Real-Time Analytics

31:34 – Why Founders Should Take M&A Calls

35:05 – How Optionality Creates Future Exits

36:45 – From Yahoo to Visual Revenue

40:01 – The “List of Hate” Startup Ideation Process

44:57 – Why Founder Focus Beats Angel Investing

48:43 – Building Visual Revenue for Digital Publishers

53:44 – Selling Visual Revenue to Outbrain

54:58 – The Pain Behind X.ai

55:26 – Market Challenge vs. Science Challenge

56:59 – Why Scheduling Was a Worthy AI Problem

01:00:40 – Testing X.ai with Human Assistants First

01:02:31 – Wizard-of-Oz Testing and Scheduling Complexity

01:05:34 – Building AI Before Modern LLMs

01:06:07 – 47 Intents and 32 Million Labeled Data Points

01:10:13 – Lessons from the X.ai Journey

01:11:14 – Why Winning the Turing Test Was the Wrong Goal

01:14:55 – When Customers Stop Being Sold and Start Buying

01:17:04 – Introducing LaunchBrightly

01:17:43 – Building for the Love of the Sport

01:19:20 – Why LaunchBrightly Exists

Pull quotes:

“If you can just figure out a way to just not die, that’s probably the best way you can somehow win.”

“I have a little list of hate on my phone.”

“It’s okay to be a machine doing machine things in a machine-like way.”

Dennis’s story is not the sanitized founder mythology of perfect timing and clean wins. It is a sharper, more useful version: build, sell, fail, learn, repeat—and keep choosing problems painful enough that someone already has a human doing the work.

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What if the hardest part of raising venture capital isn’t building the company — but understanding the game being played across the table?

Charlie O’Donnell has spent more than two decades inside the venture machine: first on the LP side at the General Motors Pension Fund, then as the first analyst at Union Square Ventures, then helping First Round Capital build its New York presence, where he sourced early deals like GroupMe and SinglePlatform. In 2012, he founded Brooklyn Bridge Ventures, the first VC fund based in Brooklyn, writing first checks into more than 100 companies and becoming one of New York’s most accessible early-stage investors.

Now, after stepping away from active fund investing, Charlie is focused on helping founders understand what investors often won’t say out loud. His new book, Founder Unfriendly: What Investors Won’t Tell You About Getting Funded, pulls back the curtain on why good companies get passed on, why mediocre companies still get funded, and why fundraising is less about “being impressive” than proving fund-returning potential.

In Today's Episode We Discuss:

03:55 — Surviving the Dot-Com Crash and Negative Returns

06:29 — What LPs Don’t See About Venture Capital

09:39 — Why VCs Are Still Middlemen in the Startup Ecosystem

11:33 — Lessons from Being the First Analyst at Union Square Ventures

14:02 — Building a Network Without Money or an Ivy League Background

17:10 — Creating Access Through Community and Events

19:57 — Joining First Round Capital After a Failed Startup

20:31 — Pitching During the 2008 Financial Crisis

21:01 — Helping Spark the Foursquare Funding Race

22:28 — Why New York Needed a Different VC Playbook

24:26 — GroupMe, SinglePlatform, and Early Wins at First Round

25:33 — Price Sensitivity vs. Price Takers in Early-Stage VC

28:05 — Why One Lucky Deal Is Not an Investment Strategy

32:15 — Leaving First Round to Launch Brooklyn Bridge Ventures

34:21 — Why Charlie Walked Away From Active Fund Investing

37:09 — Writing Founder Unfriendly for the 99% of Founders

39:20 — Why Good Businesses Still Get Rejected by VCs

41:00 — Pitching Potential Instead of Conservative Promises

45:35 — Why Fundraising Is a Potential Conversation

46:10 — What Founders Can Learn From Parenting a Small Child

47:30 — Why Every Slide Needs to Scream Fund-Returning Outcome

48:30 — Team, Market, and Traction as the Core Pitch Narrative

50:48 — How Founders Can Redirect Bad Investor Questions

53:28 — Controlling the VC Meeting Without Being Obnoxious

55:47 — Why Founders Should Read Founder Unfriendly

56:41 — The One Deal Charlie Wishes Hadn’t Fallen Through

Charlie’s advice is blunt: venture capital is not a validation system. It is a financial product with its own incentives, blind spots, and pattern-matching problems. Founders who understand that can stop treating rejection as a judgment on their worth — and start pitching the upside investors are actually paid to chase.

As Charlie puts it: “This is not a promise conversation. This is a potential conversation.”

And that may be the real founder lesson: the best pitch is not the safest version of the truth. It is the clearest version of the possible.

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What does it take to design products people trust enough to wear, install in their homes, and use to manage their money?

Lauren Von Dehsen has spent 15 years at the intersection of hardware, software, and human behavior, shaping products that quietly become part of everyday life. She worked on the UX of Nike FuelBand when connected devices were still experimental, helped define how smart home products worked together at Nest, contributed to the foundations that later became Matter, built Google Health’s consumer UX organization from scratch, and scaled SoFi’s design and research team into a 100-person operation.

In this episode, Lauren joins Brian Bell to unpack what great design really means when the stakes move beyond pixels. From the early days of wearables to smart homes, healthcare, fintech, and now AI-driven design tools, Lauren shares how product teams can move faster without losing the thing that matters most: what actually reaches the customer.

In Today's Episode We Discuss:

00:01 — Introducing Lauren Von Dehsen

00:48 — Lauren’s Origin Story in Design

01:25 — Choosing Design Over Math and Science

02:56 — Discovering the Design of Everyday Things

04:31 — The Product Lauren Is Most Proud Of

05:43 — Joining Nest During the Google Acquisition

06:48 — Why Nest Changed the Smart Home Market

08:11 — The Timing Behind Nest’s Breakthrough

10:28 — Design the Product, Not the Documentation

11:21 — Why Great Concepts Often Never Ship

13:14 — Taking Ownership of What Customers Actually Use

13:40 — Designing Across Hardware and Software

15:09 — Inside the Secret Nike FuelBand Project

16:27 — Asking the Questions Nobody Had Answered

17:21 — Designing Before and After Figma

18:01 — From InDesign Specs to Collaborative Design Tools

19:56 — How Figma Accelerated Product Design

21:16 — How AI Is Changing the Design Landscape

22:19 — Why Prompting Is Harder for Visual Work

24:15 — Claude Design, Noon, and the Future of AI Design Tools

25:20 — Why Design Needs More Than Words

26:13 — Lauren’s SoFi Chapter

26:30 — Leaving Google for a Faster-Stage Company

28:03 — Why New Problem Spaces Create Better Design Thinking

29:34 — Joining SoFi Right Before COVID

30:27 — Building a Mature Design and Research Organization

31:11 — Designing Across Banking, Loans, Investing, Crypto, and Insurance

32:04 — What Founders Get Wrong About Design

33:19 — When to Use Familiar Patterns vs. Diverge

34:26 — What Nest Got Right About Design Culture

35:21 — Trusting Designers to Make the Final Call

36:24 — Moving Design From Execution to Strategy

37:54 — Applying “Product, Not Documentation” to Design Leadership

38:21 — Rituals, Reviews, and Scaling Design Teams

40:10 — Thread, Weave, Matter, and Smart Home Interoperability

41:23 — Designing for Devices That Need to Work Together

42:17 — The Most Common Early-Stage Design Mistake

43:32 — Bringing Designers Into the Conversation Earlier

One of Lauren’s sharpest lessons is simple: customers do not care how clean your spec was, how elegant your process looked, or how many rituals your team invented. They judge the thing in their hands.

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What happens when the future of transportation depends on infrastructure that still fails one out of every five times?

Brad Crist, co-founder and CEO of ChargeMate, is tackling one of the least glamorous—but most important—problems in EV adoption: broken charging experiences. Before founding ChargeMate, Brad spent more than a decade in climate tech, working across energy, automotive, and EV charging at companies like Accenture, Faraday Future, Volta, and Spring Free EV. After helping scale EV charging networks from hundreds to thousands of stations, he saw the real problem up close: chargers may look “online,” but the driver experience often tells a very different story.

ChargeMate is building an AI operating layer for EV charging reliability—combining chat, voice agents, backend charger diagnostics, remote commands, and human escalation to help operators resolve issues faster, reduce support costs, and recover lost revenue. In this episode, Brad breaks down why charging failures are often not about broken hardware, but about payments, apps, user confusion, software glitches, vehicle-charger handshakes, and fragmented operating systems.

In Today's Episode We Discuss:

00:01 – Brad Crist, ChargeMate, and the EV Reliability Gap

00:34 – From Utilities to EV Charging Startups

01:16 – The Rivian Road Trip Problem

02:39 – Tesla, Non-Tesla EVs, and Market Fragmentation

04:07 – Why Public Charging Fails

05:55 – ChargeMate’s AI Support Layer

06:18 – Why Incumbents Struggle with Reliability

08:09 – AI-Enabled Support and Call Deflection

09:33 – The First Design Partner Breakthrough

11:16 – The Pivot Away from Consumer Route Planning

13:39 – Why Zendesk and Intercom Are Not Enough

15:38 – Complexity, Protocols, and Charging Standards

16:42 – Autonomous Vehicles and Future Infrastructure

18:11 – Natural Language Interfaces for Energy Assets

19:25 – Early Decisions That Nearly Killed the Company

20:55 – Contrarian Beliefs About EV Infrastructure

21:37 – Enterprise Sales Challenges

22:38 – Starting with Voice First

Brad also shares the hard lessons of selling into EV infrastructure, the danger of building too much before finding a painful wedge, and why the next decade of mobility will depend not just on more chargers—but smarter, self-healing infrastructure.

“The charger can look online, but the actual driver experience is very different.”

“People don’t necessarily want to talk to a human. They want to solve their problem.”

Brad started as an early EV believer trying to impress friends with a Rivian road trip. Now he’s building the AI layer that may determine whether the rest of the market trusts electric vehicles at all.

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What happens when the entrepreneur who taught Silicon Valley to “move fast” decides the real threat isn’t failure — it’s success?

Eric Ries, creator of The Lean Startup movement, is back with a far more uncomfortable thesis: the companies we admire don’t usually die because they lose. They die because they win — and then get financially engineered into irrelevance.

In this episode, Eric breaks down the core argument behind his new book Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great: that modern capitalism increasingly rewards extraction over value creation — and that most founders are structurally unprepared to resist it.

In Today's Episode We Discuss:

00:01 — Intro: Eric Ries Returns to Ignite

00:40 — Why Good Companies Go Bad

02:16 — Good to Great vs Incorruptible

03:10 — Financial Extraction & Corporate Decline

06:53 — The Long-Term Stock Exchange Experiment

08:33 — Financial Gravity Explained

10:26 — Why Founders Succumb to Short-Term Pressure

14:16 — The Moment Companies Become Corrupted

14:48 — The FedMart & Costco Story

19:35 — Why Markets Reward Extraction

22:47 — Shareholder Primacy vs Mission Primacy

25:04 — Organizations as Emergent Intelligence

28:13 — Ethos vs Company Culture

31:34 — Why Founders Lose Control of Their Companies

36:24 — Governance Mistakes That Destroy Companies

40:10 — Jeff Bezos, Amazon & Long-Term Thinking

43:20 — Leadership, Profit & Human Flourishing

48:32 — Mission-Driven Business Models

49:11 — Does Human Flourishing Break Capitalism?

52:34 — Blueprint for Building Incorruptible Companies

Some of the sharpest moments:

“Success makes you a target. It doesn’t just give you freedom and power — it makes you worth capturing.”

“We are in an era of disposable organizations being led by temporary managers on behalf of absentee owners.”

If The Lean Startup was about building products that survive uncertainty, Incorruptible is about building companies that survive success.

Because sometimes the thing that kills a company isn’t competition.

It’s the spreadsheet.

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What if the biggest risk in a startup isn’t hidden in the product, the team, or the market—but buried inside the data no one is auditing?

Attila Tóth is the co-founder and chief strategist of Cognitive Creators and the author of Hyper: The Untold Story of Marketing Data. His path started far from boardrooms: as a teenage professional cyclist who built a scrappy webshop for his father’s business, saw the first sale come in, and immediately asked the question that would shape his career: why only one? That curiosity pulled him into analytics, consumer behavior, digital strategy, and eventually digital due diligence—where his team once uncovered roughly €2.5 million in hidden risk inside an €80 million M&A deal.

In this episode, Attila breaks down why most companies are trapped in a paid-marketing treadmill: rising CAC, shrinking organic reach, messy first-party data, and platforms that make companies play by rules they don’t fully understand. He argues that the escape isn’t abandoning Google, Meta, TikTok, or AI tools—it’s learning how to use your own data strategically before your competitors do.

In Today's Episode We Discuss:

00:01 — Intro to Attila Tóth and Cognitive Creators

00:25 — Attila’s origin story

00:29 — From teenage cyclist to accidental web builder

02:54 — The first online sale

03:10 — Discovering analytics, tracking, and consumer behavior

04:29 — Launching Sight Doctor at 18

05:00 — Early startup failure and hard lessons

05:40 — Digital business modeling for traditional industries

06:45 — The M&A audit that exposed €2.5M in risk

08:57 — Writing Hyper and the frustration behind marketing data

11:14 — The rising cost-per-click problem

12:18 — The bakery ad-spend analogy

14:52 — The paid marketing trap

16:43 — The marketing spend treadmill

18:10 — Searching for an escape from platform dependency

20:00 — Turning years of experiments into a book

22:04 — Self-publishing Hyper

22:34 — Defining the marketing data trap

24:00 — First-party data as the escape plan

24:22 — The tire purchase example

26:29 — Banks, bad segmentation, and irrelevant offers

28:26 — Data silos inside large companies

31:00 — B2B marketing stacks and startup tooling

31:40 — Why there is no perfect tool list

32:35 — The hidden cost of startup cloud credits

34:04 — Questioning the tech stack after credits expire

35:33 — What founders and VCs misread in campaign performance

36:08 — CAC sustainability beyond the first beachhead

38:35 — The UK-to-US expansion problem

40:16 — Digital brand value as startup resilience

42:29 — Brand connection beyond logos and colors

44:01 — Category-defining startups

44:43 — Slack, Teams, and category creation

46:43 — The unsolved interoperability gap

47:50 — Market digital footprint as a VC diligence lens

50:49 — AI, marketing sameness, and lazy prompting

53:41 — The coming wave of AI-generated marketing noise

55:12 — Iteration, personalization, and AI-assisted campaign testing

56:28 — Event-driven marketing and localized campaign signals

He started by chasing speed on a bicycle. Now he helps founders and investors spot the hidden drag inside digital businesses before it costs them millions.

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