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