The Next New Thing

Andrew Warner

Creating with AI is fun. Turning it into a growing business is even more fun.

  1. 3 FEB

    How Josh Mohrer built Wave AI

    Presented by Zapierhttps://zapier.com/ Episode Highlights / Timestamps 00:00 $7M ARR as a solo founder01:21 Profit, margins, and team size02:51 Josh’s path from Uber to Wave05:24 Choosing ideas in the early AI days06:18 Why summarization felt like the killer app08:15 Competing with Otter, Fireflies, and others10:21 Recording real-world audio vs meeting bots12:18 Spending more on AI to improve quality13:39 Knowing you’re onto something from user emotion15:09 Why Wave stayed general instead of vertical16:12 Learning to build with ChatGPT18:00 How Wave’s architecture evolved19:39 Using Claude Code day-to-day21:00 AI agents analyzing analytics and logs25:21 The tools behind Wave (Cursor, Twilio, Adapt)27:27 Building instead of buying SaaS tools30:00 Using AI to ship features faster32:06 Why Zapier matters for data portability34:03 The future of cheap, abundant software36:09 Running Wave like a corner store, not a startup40:12 Growth goals without VC pressure42:18 How Wave gets customers today49:03 Why SEO side projects didn’t convert50:24 “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.

    56 min
  2. 26 GEN

    Ryan Carson uses AI to customize email drip

    Presented by Zapierhttps://zapier.com/ Episode Highlights / Timestamps 00:00 Why every email should be personalized00:18 Ryan’s background and what Untangle does00:45 Rethinking traditional email drips01:12 Customizing emails based on user situations01:39 A real example that led to a signup02:06 Daily automated marketing insights via email03:00 Doing things that don’t scale with AI04:03 Walking through the AI email system05:06 Using lead magnets and contextual data06:09 Enriching leads and storing user context06:45 Hourly cron jobs and email scheduling07:39 Feeding context into the LLM correctly08:15 Preventing hallucinated features08:24 Sending emails with Resend09:18 Measuring clicks instead of opens10:12 Layering engagement-based follow-ups10:39 Long-term personalized nurture loops12:00 Turning marketing emails into real value13:03 Building vertical-specific AI agents14:15 Using Zapier and modern automations16:12 Building systems with AI coding agents18:27 Running multiple AI agents at once21:27 Deciding what to build in a world of “free code”24:09 Daily AI-generated growth recommendations27:45 Using AI to generate and validate ideas31:03 Increasing insight frequency, not brilliance34:21 Why personalized email is a massive opportunity34:48 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.

    35 min
  3. AI Automation that makes cold calls

    8 GEN

    AI Automation that makes cold calls

    Presented by Zapierhttps://zapier.com/ Episode Highlights / Timestamps [00:00] A broker replaces himself with an AI voice agent[00:45] Early pricing and first customers[01:30] The reality of cold calling expired listings[04:21] Why off-the-shelf AI voice tools weren’t good enough[05:15] First AI-booked listing appointment[08:15] Launching without a website using Meta lead forms[12:27] Using Zapier to glue the system together[14:51] Why this model works beyond real estate[16:12] Fine-tuning models for sales conversations[19:12] Shutting down a profitable agency to build SaaS[22:12] Founder roles and co-founder fit[30:00] What AI coding tools really do (and don’t) replace[32:42] Breaking down the early revenue[35:24] Naming the company and what comes next  What happens when someone is so fed up with cold calling that they build an AI to do it for them — and it actually works? In this episode of  The Next New Thing, Andrew Warner sits down with Yevgeniy Matsay and Aidan Richards, co-founders of Rezora. They share how a frustrating real-estate sales job turned into an AI voice-agent business that generated real revenue — and why they ultimately shut down a profitable agency model to build scalable software instead. Yevgeniy started as a real estate agent, spending entire days cold calling expired listings. When early AI voice agents emerged, he decided to build one tailored specifically for sales conversations. It landed listing appointments almost immediately. Instead of keeping it to himself, he sold it as a service to other brokers, validating demand fast — but also running into the limits of manual setup and constant customization. From there, the conversation digs into how they: Proved demand with a scrappy agency-style rolloutUsed tools like Zapier and voice AI to stitch together a working system before SaaS existedLearned why “just prompting” breaks down for sales callsTransitioned from custom workflows to a self-serve product built on fine-tuned language modelsThought about scalability, founder roles, and when to pause revenue to build the right thing This is a grounded, technical, and honest look at turning AI automations into a real business — including the tradeoffs, the hard parts, and what actually works in practice.

    36 min
  4. He keeps selling AI

    30/12/2025

    He keeps selling AI

    Episode highlights: [00:00:00] Joe’s businesses and revenue breakdown[00:00:45] Five ways to make money with AI[00:00:54] Selling AI headshots as a done-for-you service[00:02:06] Delivering with VAs and prompts[00:03:36] Getting customers via LinkedIn polls and ads[00:06:00] Teaching AI while learning it yourself[00:08:24] Selling ideas before creating the product[00:09:27] Building a course entirely with AI[00:14:15] Selling AI-generated infographics to franchises[00:17:24] Using AI to build landing pages and funnels[00:22:21] ChatGPT as a co-founder and therapist[00:25:30] Scaling an agency without adding employees[00:30:00] Monetizing AI education and communities[00:34:03] Building basic software and prompt generators[00:40:03] Creating MVPs without developers[00:45:27] Focusing ideas into one scalable product[00:49:03] Rebuilding after COVID, divorce, and burnout In this episode, Andrew Warner sits down with Joe Apfelbaum, founder of Ajax Union and EvyAI, to break down five practical ways to make money using AI right now — without needing to code, raise money, or build complex software. Joe walks through real examples from his own businesses, including AI-powered services, courses, and lightweight software tools that generate revenue fast. More importantly, he explains why these models work: people want outcomes, not software — and AI lets you deliver those outcomes with tiny teams and massive leverage. This is a raw, tactical conversation about turning AI into income, rebuilding after setbacks, and designing businesses that scale without adding people.

    51 min
  5. He’s building an AI media empire

    29/12/2025

    He’s building an AI media empire

    Episode highlights: [00:00:00] The vision: media customized to one person[00:02:15] Why revenue isn’t the point — yet[00:03:18] Seeing early personalization at Spotify[00:06:00] Why kids’ content felt broken[00:07:48] Making the child the hero of the story[00:08:42] The hardest problem: image consistency[00:11:24] Why scaling AI products is nothing like demos[00:14:06] Personalized media won’t replace broadcast — it adds new behavior[00:16:21] Why parents are the buyer, not the consumer[00:20:51] Bedtime as a repeatable ritual[00:23:42] Why Dream Stories is a service, not a novelty product[00:28:12] Distribution is the real bottleneck[00:32:15] Why repeat purchases beat subscriptions[00:39:00] From “pull” products to “push” experiences[00:45:00] Context and memory as the real moat[00:50:06] Learning directly from customers[00:54:09] Synthetic data and AI-generated avatars[00:59:06] Automating PR and support with AI In this episode, Andrew Warner talks with Ricardo, founder of Dream Stories, a company using AI to create fully personalized children’s books where each child becomes the hero of their own story. Ricardo shares how a simple idea — making a better bedtime story for his own son — turned into a scalable business with tens of thousands of unique characters created. But more importantly, he lays out a bold vision: a future where movies, TV shows, books, and media are customized for a single person, not the masses. They dive deep into what it actually takes to build a consumer AI company beyond demos and hype — from image consistency problems and synthetic data, to distribution, paid acquisition, and turning one-time novelty purchases into repeat behavior. This is a rare, honest look at where AI-generated media is headed — and what founders should really be building right now.

    1 h
  6. Easy Zapier AI Automations - ft founder Wade Foster

    19/12/2025

    Easy Zapier AI Automations - ft founder Wade Foster

    Episode highlights: [00:00:00] Businesses built entirely on Zapier[00:01:30] The roofer-turned-automation-agency story[00:03:54] What AI enables that wasn’t possible before[00:07:12] OpenAI Agents vs. Zapier workflows[00:11:15] Connecting AI agents to real business tools[00:13:03] Building a meeting-prep agent live[00:18:00] Why AI is great at building workflows, not just running them[00:23:06] Zapier customers, revenue, and bootstrapping discipline[00:28:57] AI-powered lead qualification in real time[00:33:18] Automation agencies and speed-to-lead economics[00:40:03] Why Zapier is positioned to last[00:42:45] Using AI as a neutral leadership coach[00:47:06] AI tools Wade personally uses In this episode, Andrew Warner sits down with Wade Foster, co-founder and CEO of Zapier, to explore how AI agents, automation, and workflows are reshaping how modern businesses operate — from solo founders to companies doing hundreds of millions in revenue. Wade shares real examples of people who’ve gone from running local service businesses to launching automation agencies powered almost entirely by Zapier. Together, they break down how AI changes what workflows can do, why agents and automations are complementary (not competitors), and how founders can turn speed-to-lead, personalization, and internal tooling into real revenue. You’ll see a live walkthrough of building AI agents inside Zapier — including meeting prep, lead qualification, and internal coaching — all without writing code. 👉 Join us: https://thenextnewthing.ai/ 👉 Team member feedback Zap: https://l.thenextnewthing.ai/r/Pdja7P

    52 min

Descrizione

Creating with AI is fun. Turning it into a growing business is even more fun.

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