👉 Link to resources: https://thenextnewthing.ai/l/jon-45million-ai-playbook

⏱ Timestamps
00:00 From $400 to $4.5M ARR
00:18 Hitting $1M solo with AI
01:57 The $105K dev quote that changed everything
02:15 Discovering Replit
03:18 From app idea to business opportunity
05:33 Having AI interview you to refine a business
07:21 The first business model
10:03 The first real customer and first $15K contract
13:12 Teaching practical AI, not just theory
16:48 Jon’s playbook for starting an AI business
19:03 How Zapier fits into the stack
21:18 Why the .org brand worked
23:15 Using GEO to get found in search and ChatGPT
27:27 Building recurring revenue with a fractional CAIO model
31:39 The move from services to software
33:54 What Jenna does for client businesses
36:18 Why this could become a billion-dollar business
39:00 How Jon thinks about pricing
41:33 Brand, trust, and distribution
43:39 Favorite tools: Grok, Replit, Midjourney, NemoClaw
47:51 Margins, growth, and reaching $4.5M ARR
49:12 How long this opportunity will last

He started with $400, built the business himself with AI, hit $1M solo, and is now at $4.5M ARR.

In this episode of The Next New Thing, Andrew Warner talks with Jon Cheney about the exact playbook he used to turn AI tools into a high-ticket recurring-revenue business.

👉 Priority Launch List: https://thenextnewthing.ai/l/shane-priority-launch-list
👉 Shane Mac (X): https://x.com/ShaneMac
👉 Shane Mac (LinkedIn): https://www.linkedin.com/in/shanemacsays/
👉 XMTP: https://xmtp.org/

⏱ Timestamps
00:00 Launch AI agents on your phone
00:09 Copy any app with a prompt or screenshot
00:18 Creating an agent inside Convos
00:36 Agents provisioned with tools automatically
00:45 OpenClaw vs Hermes agents
00:54 What makes something an “agent”
01:21 Limited rollout and waitlist access
01:30 Turning a screenshot into an app
02:06 Demo: calorie tracking agent
02:33 From app → personalized AI coach
03:18 Training agents with personal data
03:54 Building a fully customized fitness assistant
04:30 Why agents get better over time
05:06 Backing from Andreessen Horowitz + USV
05:15 Coordinating group events with agents
06:00 Replacing chaotic group chats
06:45 Agent managing RSVPs, timing, logistics
07:21 Real-time updates and humor in chat
08:06 Monitoring content with “Radar” agents
09:00 Tracking writers, artists, and updates
09:45 Daily summaries across the internet
10:30 Personalized alerts and insights
10:57 Relationship + life coordination agent
11:24 Daily plans, reservations, and logistics
12:09 Combining multiple tools into one system
12:18 Product rollout and waitlist strategy
12:54 Future integrations (Notion, calendars, etc.)
13:21 Why messaging becomes the main interface
13:39 Agents talking to other agents
14:06 Privacy and coordination between agents

What if your apps weren’t apps anymore—but agents you talk to inside a chat?

In this episode of The Next New Thing, Andrew Warner sits down with Shane Mac to explore Convos, a new platform where you can launch AI agents directly on your phone—and have them act like full apps inside a conversation.

Instead of downloading tools, you create agents by describing what you want. They get provisioned with email, phone numbers, browsing, and memory—then join your chats like participants. From there, you can clone apps, coordinate events, track information across the internet, or even build personalized systems that evolve over time.

Shane demos how a simple screenshot can turn into a working app, how agents can act as assistants inside group chats, and how they can coordinate with other agents without exposing your personal data.

The bigger idea: the interface is shifting from apps to conversations—and agents become the layer that connects everything you do.

👉 Resources: https://thenextnewthing.ai/l/wade-resources
👉 Wade Foster (LinkedIn): https://www.linkedin.com/in/wadefoster/

Zapier just gave AI agents access to 10,000+ apps—and it completely changed how Wade Foster works.

In this episode of The Next New Thing, Wade (Zapier’s CEO) shows how their new SDK lets tools like Claude, Cursor, and Codex directly interact with your entire stack—Slack, Gmail, HubSpot, databases, and more.

Instead of switching between apps, Wade now does everything through an agent: checking Slack, reviewing customers, generating emails, prepping meetings, and even auditing hiring decisions.

The key shift isn’t just automation—it’s turning your entire workflow into something an agent can run end-to-end.

He walks through how he built a personal “CEO CRM” that pulls data from multiple systems, identifies which customers need attention, and drafts outreach emails automatically. From there, he shows how these workflows evolve into reusable skills, then into fully automated systems that run in the background.

The result: less time clicking through tools—and more time operating at a higher level.

⏱ Timestamps
00:00 Giving AI agents access to all your tools
00:27 Zapier SDK launch (open beta)
01:12 Connecting agents to 10,000+ apps
01:57 Why this changes how work gets done
02:24 Installing the SDK in seconds
03:00 Running real workflows inside an agent
03:27 Demo mode (protecting sensitive data)
04:21 SDK vs MCP (what’s different)
05:24 Building a personal CEO CRM
06:27 Pulling data from HubSpot, Databricks, Gong
07:30 Identifying accounts that need attention
08:06 Generating outreach emails automatically
09:00 Keeping humans in the loop (draft vs send)
09:45 Using Clay to verify contact data
10:48 Training AI on your writing style
11:24 Building reusable workflows (skills)
12:00 Daily brief automation (calendar, email, tasks)
13:12 Meeting prep generated automatically
14:06 AI reviewing hiring decisions
15:00 Advisory council of AI personas
15:45 Turning 30-min tasks into 5-min tasks
16:21 Creating your own daily brief system
17:15 Finding what to automate
18:00 Using AI to suggest new workflows
19:03 Reviewing past chats for automation ideas
20:06 Turning repeated tasks into skills
20:42 From manual → automated workflows
21:00 Cron jobs and background execution

👉 Join us: https://thenextnewthing.ai/

Resource mentioned:
1. Tools Nat used to build Felix
2. Unedited transcript for the Felix interview
3. More
👉 All here:https://thenextnewthing.ai/nat-eliason-felix

Guest links:
👉 Nat Eliason (LinkedIn): https://www.linkedin.com/in/nateliason/
👉 Masinov: https://masinov.co

An AI agent made $177,000 running its own business—and then got interviewed about it.

In this episode of The Next New Thing, Andrew Warner does something unusual: he interviews Felix, an autonomous OpenClaw agent, before talking to its human co-founder, Nat Eliason.

Felix explains how it operates, where it’s actually autonomous (and where it’s not), and how it manages real revenue streams—from selling products to handling customer support. Then, Nat breaks down how the system works behind the scenes: how Felix launches products, builds marketplaces, manages other agents, and continuously spins up new businesses.

You’ll see how a simple experiment—“build something overnight and sell it”—turned into a multi-product ecosystem including PDFs, marketplaces, services, and agent-native tools.

The bigger idea: we’re moving toward a world where AI agents are not just tools—they’re economic actors.

⏱ Timestamps
00:00 Felix made $177K as an AI agent
00:27 Interviewing an AI agent (first ever)
01:12 Where Felix is actually not autonomous
02:24 Tools Felix runs on (OpenClaw, Claude, Discord)
03:00 Limits: memory, judgment, and calls
03:27 How Nat improves Felix through system design
04:03 Learning from real mistakes in production
05:06 First product: AI-generated PDF sold on X
06:09 $1K+ in sales overnight
07:03 Iterating products based on user feedback
08:06 Building Claw Mart (agent skill marketplace)
09:36 Why marketplaces beat service businesses
11:24 Selling OpenClaw setup services ($2K + $500/mo)
12:27 Why they paused the service business
13:21 Building an agent-first CRM (Sodex)
15:00 How agents manage customer context
17:15 Running the company entirely in Discord
18:00 Paperclip: agents managing other agents
20:15 When to split into multiple agents
22:12 Why Felix doesn’t write code
24:00 Debugging, tickets, and agent workflows
25:48 How new product ideas emerge
27:00 AI-native newsletters for agents
28:03 Agent-friendly content distribution
30:09 The future of agent-driven commerce
31:57 Why Nat isn’t going all-in (Alpha School)

👉 Join us: https://thenextnewthing.ai/

Episode Highlights / Timestamps
00:00 Revenue explodes after building for AI agents
00:18 The origin of Postiz as an open-source social media scheduler
01:12 Finding a “blue ocean” inside a crowded market
01:57 Adding MCP and early AI integrations
02:42 Why automation dramatically reduces churn
03:54 Growing Postiz to $17K–$20K MRR
04:03 Discovering OpenClaw and the shift toward agent-driven software
05:06 Building a CLI so agents can control Postiz
05:51 The viral “Larry” OpenClaw agent story
07:48 Why agents need strong documentation and skills
09:18 Turning a full API into a simple CLI with Claude
11:51 Why CLI tools may become the default interface for agent startups
12:45 The next startup idea: agent-native UGC video generation
13:03 Why CLI reduces token usage compared to APIs
16:21 Using Claude to build the CLI automatically
17:06 Postiz reaches $45K MRR

In this episode of The Next New Thing, Andrew Warner talks with Nevo David, the creator of Postiz, about how his revenue jumped to $45K+ MRR after a surprising shift: he stopped building primarily for humans and started building for agents.

Episode Highlights / Timestamps
00:00 Marketing to agents, not humans
00:45 What “agent marketing” actually means
01:30 How agents decide which products to pick
02:15 What works: clean docs, fast pages, agent-friendly content
03:54 How people are testing and tracking agent recommendations
04:48 Is SaaS dead?
04:57 Zapier’s CPTO vibe-codes a meeting recorder
05:24 Why they still won’t cancel SaaS subscriptions
06:27 When vibe coding is worth it (and when it isn’t)
06:45 Software spend vs headcount spend
07:57 The “War Council” Claude skill
08:33 How it spins up subagents + personas
09:54 How Wade built it fast using Cursor + Granola notes
11:06 Skills as a commodity vs software as a business
12:54 Using War Council for hiring decisions
14:51 Using it to analyze sales performance + feedback
16:21 Wade’s Cursor setup + switching between models
17:42 Using Codex to critique Claude when it gets stuck
18:09 How Wade structures personal context files
21:18 Building an AI chief-of-staff system
22:03 Using Zapier MCP to draft emails / run actions
24:09 Getting 800 people at Zapier using Cursor / Claude Code / Codex
25:39 Example: AI reviewing 4 massive spreadsheets fast
31:03 The “NO” hat and staying focused
32:06 Wrap

 📄 War Council Skill (Claude Skill mentioned in the episode):
 https://docs.google.com/document/d/1CU674IKmPCAZm2xuqMGklTA-Bq1xr1GNQW6hNydxXrE/edit?tab=t.0

Are you marketing to humans… or to agents?

In this episode of The Next New Thing, Andrew Warner sits down with Wade Foster to unpack a shift that’s already starting to change how companies grow:

AI agents are beginning to choose products on behalf of humans.

That means you may no longer be “selling to a person.” You’re trying to get ChatGPT, Claude, and other models to recommend you instead of a competitor — and the tactics are different. Wade explains what “agent marketing” actually means, what agents care about (and what they ignore), and why teams are already building tools to measure how models mention their brand.

They also tackle a question every founder is asking:

Is SaaS dead?

Wade shares an example from inside Zapier: their CPTO vibe-coded a meeting recording tool internally. It worked as a proof of concept — but they’re not canceling their SaaS subscriptions. Wade breaks down why building is cheaper than ever, but maintenance, polish, and focus are still what make commercial software worth paying for.

Then the conversation gets tactical: Wade shows how he’s using AI daily as a “second brain” inside Cursor — including a Claude skill he calls The War Council, which spins up sub-agents (ruthless CFO, wartime operator, hiring expert, design visionary, etc.) to debate decisions and return a synthesized recommendation.

This is a real look at how AI-native leadership works inside an 800-person company — without hype.

Episode Highlights / Timestamps
00:00 AI that runs your company
01:03 How Polsia’s agents are structured
02:33 One-click Meta ads explained
04:30 Why friction kills growth
06:18 Subscription model + nightly CEO agent
08:24 Launching multiple companies as a “fund”
10:21 Revenue split: 80/20 alignment
14:24 The Polsia economy vision
16:30 A real customer story
19:39 Should you build elsewhere first?
24:09 How Polsia grew from $20K to $600K+ run rate
25:12 The AI fundraising stunt
27:00 Live revenue dashboard explained
34:57 Live demo: launching a company
42:18 Tasks, credits, and iterations
49:30 Solo founder with AI engineers
52:12 Humans selling to humans vs agents selling to agents

In this episode of The Next New Thing, Andrew Warner interviews Ben Cera, creator of Polsia — a platform where autonomous agents build, market, and operate companies with minimal human involvement.

Polsia sets up the infrastructure (server, database, email, GitHub), builds the MVP, runs Meta ads, sends cold emails, posts on Twitter, answers support, and even iterates on product decisions.

Ben is a solo founder. Zero employees.

And Polsia is already showing a ~$600K+ run rate across subscriptions, tasks, ad usage, and revenue share — just weeks after launch.

But here’s the surprising part:

Most of the companies on the platform are only weeks old. The biggest revenue-generating startup inside Polsia is still early. This isn’t about overnight unicorns. It’s about a new operating model.

You bring the idea.
Polsia spins up the company.
You decide the budget.
The agents execute.

And Polsia takes 20% of revenue — aligning incentives with the founder.

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.

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.

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.

Episode Highlights / Timestamps

[00:00] Why Pat decided to build his own video platform after YouTube strikes
 [02:06] Rebuilding a YouTube-style site in just a few hours with Claude Code
 [07:30] Designing the video experience before worrying about features
 [14:06] Using modern frameworks without writing code
 [23:06] Adding video streaming with third-party APIs instead of building from scratch
 [34:03] Letting AI debug and test the app automatically
 [42:00] Deploying the app live with one command
 [48:18] Why your website should be the hub, not social platforms

In this episode of The Next New Thing, Andrew Warner talks with Pat Walls, founder of Starter Story, about how he used AI coding tools to quickly rebuild a version of YouTube after his channel was hit with content strikes.

Pat walks through how he used Claude Code to design, build, debug, and deploy a working video platform in real time — without writing traditional code. Along the way, he explains why founders should treat social platforms as distribution, not infrastructure, and how owning your audience and your software changes how you think about risk, growth, and leverage.

If you’ve ever wondered how far AI can really take you in building real products, this episode shows exactly what’s possible today.

Episode Highlights / Timestamps

[00:00] Building AI software for companies, not just selling tools
[00:36] Crossing $2M in annual revenue
[01:12] A real-world AI document automation example
[02:15] Why hourly pricing breaks in AI services
[03:36] Using consulting to learn before building products
[06:09] Landing the first customers through relationships
[09:18] Founder-led sales and networking strategies
[10:39] Hosting events to build credibility and deal flow
[17:06] Why most AI pilots fail in production
[23:06] How Press W positions itself as an AI engineering firm
[27:09] Why “AI transformation” stopped working as a pitch
[36:36] Inside Press W’s AI-native operating system

In this episode of The Next New Thing, Andrew Warner sits down with Tarun Thummala, founder of PressW, to break down how his team builds custom AI systems for real businesses — and why services, not SaaS, were the right starting point.

Tarun runs an AI engineering firm that designs and ships production-grade AI applications for companies in regulated industries like finance, healthcare, and legal. Instead of selling vague “AI transformation,” his team focuses on concrete workflows: document processing, internal tools, sales ops, and systems that actually ship and get used.

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 rollout
Used tools like Zapier and voice AI to stitch together a working system before SaaS existed
Learned why “just prompting” breaks down for sales calls
Transitioned from custom workflows to a self-serve product built on fine-tuned language models
Thought 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. 

[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.

[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.

[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

In this episode, Andrew Warner interviews Helen Hastings, founder of Quanta, an AI-powered accounting platform built for modern software companies.

Before AI could reliably understand financial data, Helen and her team had humans doing what AI does today — reading receipts, interpreting memos, categorizing transactions, and reconciling books by hand. That hands-on approach helped her uncover where automation really mattered, leading to a ground-up rebuild of accounting software that works in near real time.

Helen shares how Quanta replaces legacy systems by owning the data end-to-end, combining clean ledgers, continuous reconciliation, and AI-powered analysis — and why this approach helped the company raise $15M in Series A funding (over $20M total) and land nearly 100 customers so far.

In this episode, Andrew Warner talks with Ben Tossell, creator of Makerpad — the #1 community for no-code builders, which he later sold to Zapier. Now at Factory, Ben is helping developers build with AI instead of code — and rethinking what “technical” even means.

Ben opens up about the post-acquisition burnout that came after his sale, why he avoided starting another company, and how AI has reignited his creativity. Together, they explore what it means to go from no-code to “AI-native,” and why the dream of one-person billion-dollar companies might be closer than it sounds.

👉 Join us: https://thenextnewthing.ai/

In this episode, Andrew Warner interviews Anirudh Singla, founder and CEO of Pepper, a company that uses AI and human expertise to produce hundreds of thousands of pieces of content for enterprise brands.

Anirudh shares how he went from writing on Upwork to building a platform now doing over $10M ARR, powered by a blend of automation, creativity, and data. He reveals how Pepper uses AI agents to write, edit, and even refresh old content — and why the next big wave isn’t SEO, it’s GEO: Generative Engine Optimization.

🔗 Tools mentioned:

• Granola App: https://www.granola.ai/

• Claude Console: https://console.anthropic.com/

• TextBlaze: https://chromewebstore.google.com/detail/text-blaze-templates-and/idgadaccgipmpannjkmfddolnnhmeklj?hl=en-US

• Wade’s Zap: https://agents.zapier.com/copy/f17868bc-cc23-433a-b211-af402f47e1b4

• Garry’s Script Prompt: https://l.thenextnewthing.ai/r/OD14YA

• Alex Lieberman's EOS GPT: https://l.thenextnewthing.ai/r/5BB4do

Which of these are you already using — or planning to try next?

SEO is changing—and the next frontier is AEO: Answer Engine Optimization.

In this episode, Andrew Warner sits down with Ethan Smith, founder of Graphite, to break down how brands are already winning visibility on ChatGPT, Perplexity, and Claude — before their competitors even realize what’s happening.

Ethan explains why SEO isn’t dead, but answer engines are the next big channel — and how to optimize your site, videos, and community presence so AI models actually cite your brand in their answers.

[00:00:00] Intro
[00:02:06] Alex & Arman’s founding story — from pivot to partnership
[00:03:09] Why engineers experience AI’s biggest leverage
[00:05:15] “Think of it as a high-quality AI-powered dev shop”
[00:06:36] The big vision: Building the McKinsey of AI
[00:09:09] Crossing the chasm: From pre-AI to post-AI
[00:13:03] Intelligence arbitrage vs. labor arbitrage
[00:15:00] Using AI to double productivity in dev work
[00:19:12] Why services with recurring revenue outperform “one-off” AI projects
[00:23:06] Real client examples: healthcare, billboards, SaaS
[00:26:06] Debate: Will AI transformation companies run out of work?
[00:29:15] Becoming the CEO’s “growth partner” in the AI era
[00:31:00] The trillion-dollar dev industry opportunity
[00:33:00] Live demos: Claude Code, multi-agent coding, and real-time automation
[00:50:00] Human-in-the-loop AI and the ethics of automation
[00:55:00] How Tenex thinks about pricing, margins, and scaling
[01:00:45] Building “Morning Brew for AI leaders”

In this episode, Andrew Warner, along with Jesse Pujji sits down with Alex Lieberman (Morning Brew) and Arman Hezarkhani, co-founders of Tenex, to unpack how their company is reshaping software development and consulting with AI.

They reveal how engineers are “living in the future,” how AI is collapsing the cost of production, and why most companies won’t have the resources to cross the chasm from pre-AI to post-AI. From building mobile apps in days instead of months to using AI agents that code and run business tasks autonomously, Tenex shows what AI transformation really looks like inside modern organizations.

00:00 – Intro Montage
00:52 – Every’s portfolio: Monologue, Spiral, Cora, and Sparkle
01:48 – How many people use their tools today?
02:15 – Mostly bootstrapped, with a small raise from Reid Hoffman
04:00 – Building based on internal needs and workflows
06:45 – Monologue’s origin story: weekend build, instant love
09:00 – Why Monologue works for “hybrid language” thinkers
10:30 – Writing → Building → Sharing: the creative flywheel
12:00 – Dan’s AI rituals: Journaling, reading, and thinking
15:00 – Using GPT for self-reflection and lightweight therapy
17:30 – Getting through dense philosophy (e.g., Kierkegaard) with AI
19:00 – Spiral’s evolution from summarizer to ghostwriter
21:00 – Cora: an AI assistant that preps your inbox
23:00 – Sparkle: automatic file organization, context-aware
25:00 – How Dan uses AI to create team handbooks and meetings
27:00 – The “interviewer agent” and writing in your voice
30:00 – Why Spiral isn’t just a wrapper—it’s a writing copilot
33:00 – “Software is the new content”: product = publishing
35:00 – AI is the new Excel, and apps are the new templates
37:00 – How Every maintains creativity while growing beyond 10 people
40:00 – “Smuggled Intelligence” and why AI benchmarks need humans
43:00 – Launching without distribution: the value of momentum
46:00 – Dan’s personal life as product inspiration (love, thoughts, therapy)

Dan Shipper Every, Spiral AI, Monologue app, Cora email assistant, Sparkle file organizer, AI startup tools, bootstrapped SaaS, AI writing tools, AI for journaling, AI productivity apps, GPT for thinking, AI therapy use, AI benchmarks, smuggled intelligence, building with LLMs, Andrew Warner podcast, product-led AI

Every’s style guide + prompt
https://l.thenextnewthing.ai/r/rjyLzl

✍️ About This Episode
Neil Patel is one of the most respected names in digital marketing. In this episode, he brings hard-won lessons from AI consulting, automation experiments, and agency growth. With examples from HubSpot, med spas, SaaS tools, and beyond, this conversation cuts through the noise to show how AI really creates business value. Whether you're a founder, marketer, or agency builder, you'll walk away with practical frameworks to deploy immediately.

✅ JOIN US: https://thenextnewthing.ai/
Neil Patel’s AI sales automation:
https://l.thenextnewthing.ai/r/nrxLBo

✍️ About This Episode
Garry Tan doesn’t just lead Y Combinator—he’s reshaping how startups are built in the AI age. In this in-depth conversation, he and Andrew Warner explore the rise of solo devs, the true impact of LLMs, and how startups are re-emerging as the cultural engine of innovation. Whether you're building with AI, launching a niche SaaS, or trying to 10x your founder journey, this episode is packed with practical wisdom and future-facing insights.

✅ JOIN US: https://thenextnewthing.ai/
Garry Tan's video creation prompt
https://l.thenextnewthing.ai/r/OD14YA