They didn’t sell to insurance brokers — they replaced them.

Dakotah Rice didn’t build AI tools for the industry. He built an AI-first insurance company — and now Harper is scaling faster than they can handle.

In this episode, Dakotah shares how Harper went from kitchen-table experiments to a high-growth, fully autonomous insurance brokerage. He breaks down the real bottlenecks, the AI architecture behind their workflows, and the bold bets that could reshape an entire industry.

What you’ll learn:

Why Harper ditched SaaS and chose vertical integration

How to embed engineers directly in operational workflows

The underrated bottlenecks to AI-first company scaling

Why relationships are overrated in insurtech

How to build trust with real-world customers — without mentioning AI

The real limits (and future) of fully autonomous firms

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

Chapters

00:00 Introduction to Harper and Dakota Rice

00:38 Dakota's Background and Harper's Mission

02:13 Challenges and Pivots in Building Harper

04:29 Entering Y Combinator and Scaling Up

06:19 The Importance of Workflow Understanding

13:17 Lessons from Past Failures

18:34 Vision for AI in the Future

21:51 Building Complex AI Systems

22:49 Human Element in AI Services

23:53 Customer Perception of AI

27:37 Scaling Challenges and Solutions

35:14 AI's Role in Future Business Models

37:58 Future Predictions and Industry Insights

42:46 Conclusion and Contact Information

🎧 Listen on the go:

Spotify: https://spoti.fi/4m2K7ah

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

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

What if a single AI voice agent could handle 100,000 calls a day and free up your entire support team?

Episode Summary:

In this episode of Lobster Talks, Gabriel sits down with Kevin Wu, founder of Leaping AI, to unpack how voice-powered AI is automating 50–70% of repetitive support calls, self-optimizing over time, and achieving 90% customer satisfaction. We dive into the origin story, technical stack, ROI metrics, human-in-the-loop safeguards, and bold predictions for 2030.

You’ll learn:

How Leaping AI began: from BCG ideation to the first major enterprise customer

The differentiator: combining voice AI with evaluation and self-optimization modules

Managing edge cases and human fallback to maintain 90% satisfaction

Tech stack overview: orchestration layer, Twilio, multiple TTS/ASR providers, LLMs

Calculating ROI and setting realistic metrics with weekly check-ins

Future bets: AI vs. human empathy, integration challenges, market structure by 2030

Practical advice for CX leaders overwhelmed by AI hype

Chapters:

00:00 Introduction to Leaping AI with Kevin Wu

00:59 Kevin Wu's Journey and Inspiration

02:10 Winning the First Customer

02:41 Leaping AI's Unique Selling Points

03:59 Self-Improving AI Agents

05:17 Handling Edge Cases and Human Involvement

06:32 Early Days and First AI Call

07:33 Challenges and Continuous Improvement

09:00 Market Position and Competitor Insights

13:47 Customer Metrics and ROI

17:18 Technical Stack and Partnerships

19:09 Sponsor Message and Text-to-Speech Choices

19:32 The Best AI Voice Provider: Does It Exist?

21:10 Challenges in Voice AI for Sales

23:31 Implementing AI in Customer Support

25:37 Customer Reactions to AI

29:32 Future Predictions for AI in Customer Service

37:45 Getting Started with AI in Customer Service

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

🎧 Listen on the go:

Spotify: https://spoti.fi/4m2K7ah

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

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

What if you could edit your face and voice like a Google Doc?

That’s exactly what Prady Modukuru is building at Sync—an AI company making video editing fully editable in post-production. No more re-recording. Just fix it like text.

In this high-velocity episode of Lobster Talks, we go deep on Sync’s origin story, how Prady and his team ship insanely fast, and why their AI-powered content tools are poised to redefine modern storytelling. It's a masterclass in product, research, and distribution.

🔑 You’ll learn:

Why the future of video is editable—not generative

How Sync’s AI makes lip-sync edits invisible

The secret to shipping faster than anyone else in YC

What most AI startups get wrong about growth

How content became Sync’s unfair advantage

The risks—and responsibilities—of powerful AI models

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

Chapters

00:00 Introduction to Lobster Talks

00:05 Meet Prade Moku and Sync

00:48 How Sync Revolutionizes Video Editing

02:49 The Journey and Growth of Sync

06:44 The Importance of Speed and Culture

12:44 Content Strategy and Its Impact

23:23 AI Modified vs. AI Generated Videos

25:43 Future of Video Editing

25:57 Challenges in Human Editing

27:55 AI in Video Production

28:18 Common Mistakes in AI Video Companies

30:58 Organic vs Paid Content

32:00 Content Creation and Distribution

38:10 Future of Small Content Teams

41:56 Risks and Ethical Concerns

49:21 Exciting Developments at Sync

50:34 Conclusion and Farewell

🎧 Listen on the go:

Spotify: https://spoti.fi/4m2K7ah

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

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