Presented by Zapier
https://zapier.com/

Episode Highlights / Timestamps
00:00 The first billion-dollar solo company (Minecraft)
00:27 Elad’s investing track record
01:12 What “making it” really means
04:03 Where today’s “toys” become tomorrow’s giants
08:51 AI puts building power in millions of hands
09:45 Will more builders mean smaller outcomes?
13:03 AI service shops and vertical software
15:00 AI cutting permitting time from months to hours
16:39 Does AI replace CRMs and SaaS?
19:12 Is off-the-shelf software dead?
23:15 The shift from seats to AI labor units
27:36 Alexandria: translating the world’s most important books
30:36 How Elad uses AI personally
35:06 Where new AI ideas come from
37:48 What’s exciting for the next decade

“The first billion-dollar one-person company? That already happened. It was Minecraft.”

In this episode of The Next New Thing, Andrew Warner sits down with legendary investor Elad Gil — early backer of companies like Airbnb, Coinbase, Stripe, Instacart, and more — to talk about where AI is really going… and what founders are getting wrong.

Elad argues that we’re still in the early innings of AI — and that “software is AI.” The shift isn’t just better SaaS. It’s a move from seat-based software to metered digital labor. From buying tools… to buying units of work.

They discuss:

Whether “toy” AI apps can become real businesses
Why small vibe-coded projects can turn into giant companies
The agent shift (and why it changes TAM completely)
How AI eats into labor markets, not just software categories
Whether CRMs, ERPs, and landing page tools survive
Why some companies should be bought and rebuilt with AI
The real opportunity in foundation models beyond language

Elad also shares what he’s personally experimenting with — scraping and interrogating large datasets using Claude, OpenAI, and Deep Research — and why he believes the next decade will look like the early SaaS boom… but bigger.

And in a surprising turn, he talks about something very un-Silicon Valley: monuments, art, and rebuilding public beauty — including a project called Alexandria aimed at translating the world’s most important books into languages covering 80%+ of humanity.

Presented by Zapier
https://zapier.com/

Episode Highlights / Timestamps

00:00 $7M ARR as a solo founder
01:21 Profit, margins, and team size
02:51 Josh’s path from Uber to Wave
05:24 Choosing ideas in the early AI days
06:18 Why summarization felt like the killer app
08:15 Competing with Otter, Fireflies, and others
10:21 Recording real-world audio vs meeting bots
12:18 Spending more on AI to improve quality
13:39 Knowing you’re onto something from user emotion
15:09 Why Wave stayed general instead of vertical
16:12 Learning to build with ChatGPT
18:00 How Wave’s architecture evolved
19:39 Using Claude Code day-to-day
21:00 AI agents analyzing analytics and logs
25:21 The tools behind Wave (Cursor, Twilio, Adapt)
27:27 Building instead of buying SaaS tools
30:00 Using AI to ship features faster
32:06 Why Zapier matters for data portability
34:03 The future of cheap, abundant software
36:09 Running Wave like a corner store, not a startup
40:12 Growth goals without VC pressure
42:18 How Wave gets customers today
49:03 Why SEO side projects didn’t convert
50:24 “If you’re good, things might work out”
54:45 Revenue breakdown and take-home profit

What does it look like when a single founder builds a profitable AI company — alone — and quietly grows it to millions in revenue?

In this episode of The Next New Thing, Andrew Warner sits down with Josh Mohrer, creator of Wave AI, to unpack how he built a $7M ARR AI business with no full-time team — and how modern AI tools fundamentally changed what’s possible for solo founders.

Josh previously helped scale Uber in its early days, but Wave AI is a very different story. It’s a one-person, profitable SaaS built around a deceptively simple idea: record real-world conversations, transcribe them, and generate high-quality summaries people actually trust. No hype. No venture capital. No big team.

Presented by Zapier
https://zapier.com/

Episode Highlights / Timestamps

00:00 Why every email should be personalized
00:18 Ryan’s background and what Untangle does
00:45 Rethinking traditional email drips
01:12 Customizing emails based on user situations
01:39 A real example that led to a signup
02:06 Daily automated marketing insights via email
03:00 Doing things that don’t scale with AI
04:03 Walking through the AI email system
05:06 Using lead magnets and contextual data
06:09 Enriching leads and storing user context
06:45 Hourly cron jobs and email scheduling
07:39 Feeding context into the LLM correctly
08:15 Preventing hallucinated features
08:24 Sending emails with Resend
09:18 Measuring clicks instead of opens
10:12 Layering engagement-based follow-ups
10:39 Long-term personalized nurture loops
12:00 Turning marketing emails into real value
13:03 Building vertical-specific AI agents
14:15 Using Zapier and modern automations
16:12 Building systems with AI coding agents
18:27 Running multiple AI agents at once
21:27 Deciding what to build in a world of “free code”
24:09 Daily AI-generated growth recommendations
27:45 Using AI to generate and validate ideas
31:03 Increasing insight frequency, not brilliance
34:21 Why personalized email is a massive opportunity
34:48 Final takeaways

Why isn’t every email completely customized for the person receiving it — especially now that AI can do it for us?

In this episode of The Next New Thing, Andrew Warner sits down with Ryan Carson, a three-time founder currently building Untangle, to walk through a very practical, very real AI system he uses every day to grow his business.

Ryan has spent over 25 years building startups, but while setting up a “standard” email drip for Untangle, he stopped and asked a simple question: why are we still sending the same emails to completely different people? Instead of writing dozens of templates, he built an AI-powered workflow that generates fully personalized emails — based on each user’s situation, behavior, and engagement — and adapts over time.