YC to 200K users without a marketing budget? HeRA is trying to become the Figma of motion design and put After Effects on notice.

This is a builder’s story: fast pivots, AI-native product, and a bold bet to scale from Berlin, not SF.

In this episode, Chia, co-founder & CTO of HeRA breaks down how they pivoted into AI motion design, grew to hundreds of thousands of users, and why they’re betting on an onsite Berlin team post-YC.

We cover PMF vs. virality, the UI/UX of AI video, the Figma vs. Adobe playbook, and how HeRA wants to power every SaaS launch video.

You’ll learn:

- Why the motion graphics wedge beat “all-in-one” AI video editors

- The YC pivot moment: prototype in two days → interview in a week

- Berlin vs. SF: talent, costs, and staying plugged into the Valley

- PMF litmus test for AI video: “1 min product video in less than 30 minutes”

- How HeRA generates code to animate motion (and why time makes it hard)

- The Figma analogy: AI-native UX vs. legacy add-ons—and why Adobe should worry

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters

00:00 The Origin of Hera: From Video Editor to Motion Graphics

00:29 Sponsorship Message: Stable's Virtual Address Service

01:28 Introduction to the Podcast and Guest

02:07 Chia's Journey with YC and Hera's Evolution

02:51 The Birth of Hera's Core Idea

05:25 Decision to Move Back to Berlin

14:53 Technical Insights: How Hera Works

19:46 Marketing Success and Product Market Fit

25:00 Creating Continuous Motion Graphics

25:22 Challenges in Long Video Generation

27:55 Competing with Adobe After Effects

30:28 The Future of Motion Graphics with AI

31:20 Collaborative Features and Market Vision

36:38 Trends in AI and Video Creation

43:23 Hera's Impact on the Industry

48:32 Closing Remarks and Future Outlook

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@lobstercap

This podcast episode is sponsored by Stable. Click here to sign up for a virtual address:

https://dashboard.usestable.com/onboard/begin?utm_source=youtube&utm_medium=description&utm_campaign=influencer_lobster&promoCode=lobster50

YC Fall ’25 Demo Day isn’t here yet, but the signal is already loud. We went through 150+ companies and picked the ones we’d fight to get allocation in.

From AI-native banks and eBay killers to fusion reactors in space and crowdsourced drug discovery, this episode is a pre–Demo Day breakdown of YC’s Fall ’25 batch. We go category by category (B2B, Consumer, Fintech, Healthcare, Industrial/Real Estate) and call our shots before founders hit the stage. No hindsight bias, just real-time conviction.

In this episode, we cover:

- Why AI video tool Waffer might become the Canva of motion, not just another Sora clone.

- How Sorce hit 500k+ users and got Drew Houston to Venmo them a $200K angel check.

- The AI-native consumer plays: SellRaze (the “AI eBay”) and Sunflower (sobriety companion that actually prevents relapse).

- Fintech 2.0 with Selfin (AI bank aggregator) and Fernstone (AI-powered insurance brokerage in a Berkshire-sized market).

- Wild upside in healthcare and deeptech: Exonic’s crowdsourced drug discovery and LunaBill’s AI phone agents for U.S. healthcare billing.

- The industrial moonshots: Axial Composites’ next-gen carbon fiber and Zephyr Fusion’s bid to do fusion… in orbit.

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters:

00:00 The Crazy Story of Sorce's Founding

00:56 Introducing Stable: The Business Address Solution

01:56 Welcome to Lobster Talks: Fall 25 Demo Day Preview

03:28 Diving into B2B Startups: Laurie's Top Pick

08:43 Exploring B2B Startups:Gabriel's Top Pick

16:31 Consumer Startups: Laurie's Favorite Pick

21:09 Consumer Startups: Gabriel's Top Pick

25:10 FinTech Startups: Laurie's Top Pick

28:43 AI Native Banking Revolution

29:45 AI in Insurance: Fernstone's Disruption

32:01 Healthcare Innovations: Exonic and LunaBill

38:21 Industrial and Real Estate Picks

42:21 Fusion Energy in Space: Zephyr Fusion

47:17 YC's Hardware and Deep Tech Push

50:36 Demo Day and Final Thoughts

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@GJarrosson

This podcast episode is sponsored by Stable. Click here to sign up for a virtual address:

https://dashboard.usestable.com/onboard/begin?utm_source=youtube&utm_medium=description&utm_campaign=influencer_lobster&promoCode=lobster50

Hospitals are bleeding $260 billion a year to denied insurance claims — and AI is making it worse. One YC founder decided to fight back, using AI to beat insurers at their own game.

In this episode, we dive deep into how Aegis, a Y Combinator startup, is using AI agents to help healthcare providers recover billions lost to claim denials. Founder Ong shares his journey from Calcutta to Carnegie Mellon to YC, the inside story of getting into YC at the last minute, and how his team is tackling one of healthcare’s most entrenched problems.

What you’ll learn:

- How YC companies are attacking trillion-dollar industries with AI

- Why healthcare loses $260B a year to denied insurance claims

- The hidden incentives driving insurers to deny payments

- How Aegis built real traction in just 10 weeks

- What YC really teaches founders beyond the playbook

- The power of the YC network and why it still compounds after demo day

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters:

00:00 The YC Application Journey

00:48 Introducing Krishang from Aegis

01:21 Krishang's Entrepreneurial Background

02:30 The Birth of Aegis

04:53 The Power of YC Content

07:03 Getting into YC: The Application Process

10:00 The YC Batch Experience

14:25 Maintaining Momentum Post-YC

17:59 Advice for Aspiring YC Applicants

19:09 Tackling the Healthcare Industry

21:41 Targeting Medical Billing Companies

22:07 AI in Insurance: A Growing Challenge

22:21 The Impact on Hospitals

24:31 Investor Perspectives on AI in Healthcare

26:48 Strategies for Success in Healthcare Startups

33:12 The YC Advantage

33:49 The Power of the YC Network

38:14 Silicon Valley's Collaborative Ecosystem

39:58 Conclusion and Final Thoughts

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@GJarrosson

They applied to YC with 90 minutes on the clock—and got in. Then they pivoted into the most operationally gnarly corner of fintech: global payroll. Avi Konduru (Shor) breaks down how AI agents + stablecoins can vertically rebuild EOR, cut costs by an order of magnitude, and expand the market beyond today’s incumbents.

In this episode, we go deep on YC as an ambition amplifier, pivot mechanics under real pressure, price vs. TAM strategy, and why launch videos (done right) are still YC’s most underrated distribution hack.

You’ll learn:

• How a 90-minute YC application (and one-take demo) still cleared the bar
• The precise wedge: vertically owning entities + automating back office with AI
• Why “someone else’s margin is your opportunity” actually maps to EOR
• Pricing strategy: undercut to expand TAM vs. match to maximize margin
• How YC Launch video distribution compresses customer discovery into days
• The pitfalls: agent reliability, compliance debt, and scaling beyond the batch

Chapters

00:00 The Last-Minute Application Rush

00:42 Welcome to Lobster Talks

01:07 Introducing Shor: Reinventing Global Payroll

02:38 The YC Experience: A Rollercoaster Journey

05:02 The Pivot: From Stablecoin Infra to EOR

10:29 Bootstrapping Challenges and Lessons Learned

18:00 The Unexpected Turn: Applying to YC Again

23:27 Competing with Deel and Rippling

27:07 Understanding Reseller Margins and Fees

27:27 Deel's Automation and Disruption in Entity Management

27:46 Setting Up Entities in High-Traffic Countries

28:49 Challenges and Regulatory Issues in Global Payroll

30:06 AI Agents Revolutionizing EOR Operations

32:33 Pricing Strategy and Market Expansion

40:11 The Power of Launch Videos in YC

44:07 The Role of Influencers in Marketing

48:07 Future Challenges and Customer Acquisition

51:31 Conclusion and Final Thoughts

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@GJarrosson

We finally found a voice assistant that actually ships work. Not a demo, not a hype reel—April closes the loop on email and calendar while you’re driving, lifting, or walking to your next meeting.

In this YC-insider conversation, Neha (co-founder of April) breaks down how a narrow, vertical agent can outperform “do-everything” assistants, why dogfooding—not retention dashboards—built their product moat, and what a screen-lite future means for founders and operators. We also cover YC batch dynamics in a crowded voice category, Demo Day strategy, and the roadmap to a true “voice OS.”

What you’ll learn:

- Why narrowing scope (email + calendar first) beats generalist agents for real outcomes

- The dogfood standard: building to a founder’s own bar, then scaling

- How YC treats multiple “competing” companies—and why that can help you ship faster

- Demo Day tactics: being live, iterating weekly, and selling the founder, not the fantasy

- Voice vs. screens: trust, closed-loop execution, and the path to screenless workflows

- April’s roadmap: LinkedIn, WhatsApp, Slack, Notion—and verticalizing for sales & investors

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters

00:00 Introduction to April: The AI Voice Assistant

00:24 Welcome to Lobster Talks: Meet Neha from April

01:12 Diving into April's Features and Use Cases

02:46 The Journey of Building April

03:58 Challenges and Successes in the Voice AI Space

05:36 The Future of Voice AI and Investor Insights

07:37 YC Experience and Investor Reactions

08:47 The Competitive Landscape and Collaboration

12:25 The Role of YC and the Voice AI Market

20:08 The Vision for a Screenless Future

23:06 Preparing for YC Demo Day

25:38 The Importance of Execution in Business

26:16 Advice for Startups: Ship Quickly and Get Feedback

26:50 Future Integrations and Features

28:37 Challenges and Strategies During YC Journey

32:31 Maintaining Momentum Post-YC

33:20 Mental Resilience and Personal Well-being

38:10 Exciting Future Plans for April

40:17 Predictions and Insights on AI Assistants

41:09 Lessons from Zoho and Book Recommendations

43:23 Conclusion and Final Thoughts

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@lobstercap

A Netflix storage engineer walks into YC and ships an “infinite, shareable disk” on top of S3—30× faster and up to 90% cheaper—then dials GTM for the AI era. This is the file system’s comeback story.

Today I sit down with Hunter Leath (ARL) to unpack how a decade inside AWS + Netflix revealed a gap the hyperscalers won’t close: developers want storage that feels local, scales like S3, and doesn’t nuke the budget. We get into: YC as confidence engine, moving a family to SF, rebuilding for speed, why AWS won’t copy this, and why the file system—not object storage—becomes AI’s universal interface.

You’ll learn

-Why the clouds won’t ship a product that cannibalizes billions in revenue

-The architecture that makes ARL 30× faster and up to 90% cheaper

-How to catch customers exactly when new AI workloads start (the real ICP)

-Post-batch velocity: how SF energy kills the YC slump

-Why “serverless everything” needs a serverless disk to persist state

-The contrarian bet: the file system is the future data interface for AI

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters

00:00 The Risk of Leaving Big Tech

00:33 Introducing Hunter Leh and Aril

01:32 Hunter's Journey from AWS to Netflix

02:47 The Birth of Aril

06:55 Challenges and Insights from YC

07:26 The Solo Founder Experience

19:39 Building and Launching Aril

21:01 Go-to-Market Strategy and Customer Acquisition

24:04 The AI Industry's Growing Demand

24:49 Fundraising Journey and Investor Insights

26:35 AWS and Market Dynamics

29:17 Innovations in Data Storage

36:23 Maintaining Momentum Post-YC

38:27 Future Predictions in Data Infrastructure

42:22 Contrarian Views on AI and Data Storage

44:20 Conclusion and Contact Information

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@GJarrosson

YC just changed the rules—and the market is catching up. We break down why seed is the power position, how CVCs are reshaping Series A, and what YC’s new Early Decision really means for founders and investors.

In this episode, we cover Lobster Capital updates (first Series A, first DPI), how we decide follow-ons from an insider vantage point, the rise of “seed-strapping,” Coinbase Ventures x YC’s RFS on Fintech 3.0, and why stablecoins + AI agents may be the next real on-chain wedge. We also unpack YC’s Early Decision—who it actually benefits—and what to expect heading into the next Demo Day.

You’ll learn:

Why seed has asymmetric leverage (and why top YC teams don’t optimize for dollars)

How we evaluate follow-ons: revenue quality, NRR, churn, hiring, and real signal vs noise

CVCs at Series A: when specialization beats the “Tier-1” logo

“Seed-strapping”: profitability at seed, and why some teams skip A entirely

Coinbase Ventures x YC’s Fintech 3.0 RFS and the stablecoin/AI-agent stack

YC Early Decision: who it helps (hardware/bio) and how YC captures talent earlier

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters

00:00 Introduction to Investing Insights

00:23 Welcome to Lobster Talks

00:45 Lobster Capital Updates

03:16 Series A Graduation Rates

04:08 Fund Strategy and Follow-Ons

05:38 YC Companies and Profitability

10:33 Fundraising and Strategic Alliances

17:28 Crypto and FinTech 3.0

25:23 Global Currency Dynamics

26:20 The Rise of Stablecoins

27:27 AI and Crypto Synergy

32:03 Speculative Trading and Meme Coins

38:42 YC's Early Decision Program

44:01 The Future of YC and Startup Ecosystem

51:04 Conclusion and Upcoming Content

🎧 Listen on the go:

Spotify: https://open.spotify.com/show/1u1JyRKH8JYFjhBkvTUOAP

Apple: https://apple.co/4cZ8RMm

My other YouTube Channel: https://www.youtube.com/@GJarrosson

A robotaxi playbook… for dirt. Flywheel AI is turning excavators into remotely operated, camera-first machines — collecting the data to make them autonomous next.

In this YC-insider episode, we unpack Flywheel AI’s “Waymo for excavators” strategy: retrofit any machine in hours, deliver value with tele-op now, and use that profitably collected data to train autonomy later. We get into labor shortages, safety economics (OSHA penalties), competitor traps (drive-by-wire only), and how to actually do hardware at YC in 90 days without getting stuck in pilot hell.

You’ll learn

Why construction’s bottleneck is skilled operators — and how tele-op removes it

The dangerous blind-spot reality on sites and the true cost of safety incidents

Flywheel’s retrofit + single-screen UX that works on any excavator brand/size

The autonomy roadmap: camera-only stack, data flywheel, edge-case capture

How to win data rights on site (be the only retrofit, own the dataset)

The YC hardware playbook: sell first, build last; parallelize to kill lead-time

📌 Watch now and subscribe for more smart, fast, founder-first interviews.

Chapters:

00:00 From Sandbox to Real Excavator: The Journey Begins

00:20 Introducing Flywheel AI: Revolutionizing Excavators

01:49 The Labor Shortage Crisis in Construction

03:51 The Dangers of Operating Excavators

05:58 Teleoperation: Enhancing Safety and Efficiency

11:28 The Path to Autonomous Excavators

16:34 Competing in the Autonomous Excavator Market

22:26 Demo Day: Bringing an Excavator to YC

24:37 Returning the Excavator

24:47 Demo Day Setup and Reactions

26:04 Autonomy and Data Training

26:38 Joining YC and Initial Thoughts

28:03 YC's Impact on Hardware Startups

29:18 Building and Iterating Hardware

33:13 Advice for Hardware Startups

34:49 Final Thoughts and Reflections

45:03 Accelerating Iteration Cycles

48:38 Conclusion and Contact Information