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.
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.
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
🎧 Highlights:
[00:00:00] Humans doing the work of AI — before AI existed
[00:01:12] Why accounting is mostly about language, not numbers
[00:02:33] Shadowing bookkeepers to find automation opportunities
[00:06:00] Manual work Quanta knew software had to replace
[00:07:30] Why building on top of legacy systems wasn’t enough
[00:08:24] Rebuilding the ledger from the ground up
[00:10:12] Continuous reconciliation vs. monthly closes
[00:11:24] From Affirm to founding Quanta
[00:13:30] Why delayed financials are useless for startups
[00:16:03] Validating willingness to pay before building
[00:17:42] Using humans for the “last mile” while automating the rest
[00:20:15] Solving trust and data-ownership concerns
[00:22:48] Why most QuickBooks challengers failed
[00:26:33] Saying no to customers to protect quality
[00:33:36] Why AI makes real-time margins mandatory
[00:36:45] Raising $15M Series A ($20M total)
[00:37:21] Prism: asking your financials questions in plain English
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.
🎧 Highlights:
[00:00:00] From Makerpad to Factory — Ben Tossell’s journey
[00:01:33] Life after acquisition and redefining work
[00:05:06] Why AI might make things harder, not easier
[00:07:30] No-code lessons and the illusion of simplicity
[00:10:42] From teaching no-code to debugging workflows
[00:12:00] Learning to code with AI as your translator
[00:15:09] Curiosity as the new technical skill
[00:16:21] Building a “source of truth” AI system inside Factory
[00:23:42] How Ben uses AI to search across code, docs, and tickets
[00:27:36] Teaching AI to follow his workflow
[00:30:27] Getting comfortable with the command line
[00:33:45] The first time AI made him feel like a real builder
[00:35:42] Makerpad’s growth, Slack community, and hiring from within
[00:41:24] Newsletter growth hacks and lessons from Ben’s Bites
[00:46:03] Selling Makerpad and rediscovering purpose
[00:49:39] Investing through Ben’s Bites Fund
[00:50:33] Returning to his roots: teaching, learning, and building again
[00:53:18] The one-person billion-dollar company — myth or movement?
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/
🎧 Highlights:
[00:00:00] From freelance writer to $10M ARR founder
[00:03:36] How Pepper scaled from a marketplace to an AI-powered content engine
[00:05:06] The hybrid model: humans and AI creating together
[00:07:12] Building “Nimbus” — Pepper’s internal AI platform
[00:08:24] Re-optimizing thousands of old pages automatically
[00:13:03] Why FAQs and freshness signals help you rank in AI results
[00:15:00] GEO: Generative Engine Optimization explained
[00:16:12] Tracking brand mentions across ChatGPT, Claude, Gemini, and Perplexity
[00:18:00] Using AI to generate videos, voices, and creative assets
[00:25:12] Scaling creative testing with 30,000+ AI-made ad banners
[00:27:18] How smaller creators can apply these lessons today
[00:30:27] Reddit, LinkedIn, and UGC as new AI search signals
[00:33:00] Cold-emailing OpenAI’s Greg Brockman and getting access to GPT-3
[00:34:21] Building PepperType.ai and learning from early AI adoption
[00:35:30] Using AI personally to optimize meetings and calendar time
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.
Andrew shares the AI tools that real startup founders are using every day — not hype, but the ones that actually help them work smarter.
From AI note-takers that surface your blind spots to automations that coach your team after meetings, these are the tools that top entrepreneurs rely on.
🔗 Tools mentioned:
Alex Lieberman's EOS GPT: https://l.thenextnewthing.ai/r/5BB4do
Which of these are you already using — or planning to try next?
🎧 Highlights:
[00:00:00] Intro – “Don’t start with SEO. Start with AEO.”
[00:00:36] Why this is the right time to focus on answer engine optimization
[00:01:30] Case study: Webflow drives 8% of signups from LLMs
[00:03:00] Onsite vs. offsite optimization — Reddit and YouTube matter most
[00:06:18] Why Help Center content outperforms traditional SEO pages
[00:13:30] Why AEO is ideal for small startups without big budgets
[00:16:39] “SEO is not dead” — and why Google’s share of search stays stable
[00:19:39] Myths: LLM.txt, robots.txt, and how misinformation spreads
[00:23:06] The scientific method for testing what actually works
[00:25:57] Affiliates and citations — how paid mentions impact LLM rankings
[00:27:27] How to find high-value questions to target
[00:31:12] 60+ AEO tools — and the new “content scoring” era
[00:35:06] How to build an AEO agency (and what services to offer)
[00:39:36] Marketing Graphite — why thought leadership still wins
[00:43:00] The AEO roadmap: what to do first, step by step
[00:47:00] The MasterClass SEO story
[00:48:18] Fires, gardens, and creative thinking in constraint
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.
🎧 Highlights:
[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.
⏱️ TIMESTAMPS
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
⏱️ Timestamps / Episode Guide
00:00 – Intro
01:12 – Why most companies fail to get ROI from AI
02:06 – The #1 mistake: Using AI for content without strategy
03:00 – Fragmented data = wasted AI potential
04:00 – How Neil’s team fixes that: Find what drives revenue first
05:24 – Real case study: Med spas using AI to win back Google traffic
07:00 – How to get your pages in Google's AI Overview box
09:00 – When AI writing is valuable—and when it’s not
11:06 – ChatGPT rankings: Why HubSpot wins (and how you can too)
13:00 – LLM SEO strategy: Tables, reviews, comparisons, citations
15:00 – How top companies (and AI startups) get actual user growth
17:00 – The influencer growth playbook—without needing followers
18:36 – Cursor: AI that saves $20K+/engineer per year
20:00 – The two AI use cases that never fail: saving or making money
22:00 – AI dashboard startup critique: “More data” ≠ better business
24:00 – Messaging that works: From “data hub” to “cost savings”
26:00 – Case study: SaaS site messaging that drives conversion
28:00 – Should you build an “AI agency”? Neil breaks it down
30:00 – Why verticalized AI services outperform generalists
31:00 – NP Digital’s full automation demo with AI scraping + voice + outreach
34:00 – Saulo walks through the end-to-end Make.com automation
36:00 – Scraping Yellow Pages → Personalized voice memos → Clients
39:00 – Using Perplexity, ChatGPT, DALL·E, and Gmail for outreach
41:00 – Tips for scaling this system legally and effectively
44:00 – Tool stack: Appify, Invent.ai, Perplexity, ChatGPT, HubSpot
45:00 – Using AI to fuel growth until your sales team can't keep up
✍️ 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
⏱️ Timestamps / Episode Guide
00:00 – Intro
00:46 – Garry Tan on CaseText, early LLMs, and hallucination risk
04:00 – The first AI breakthroughs in legal tech
08:00 – How vertical SaaS outperforms general AI platforms
11:00 – Avoca & HVAC: beating ServiceTitan with niche AI
13:00 – YC startup growth rates: 10%–20% revenue weekly
17:00 – The “startup energy” coming back in 2025
20:00 – Garry’s vision: CRMs for every niche, not just Salesforce
22:00 – Not everyone needs to build a unicorn—small exits still transform lives
24:00 – Lost generation of big-tech employees vs. hungry 22-year-olds
26:00 – Jasper.ai, Read.ai, and the “demo effect” on enterprise adoption
29:00 – How YC partners support founders post-demo day
31:00 – Garry’s AI video creation workflow: prompts, feedback loops, and 10-min scripts
35:00 – The rise of the 200x engineer: prompts as leverage
37:00 – Revamping YC: back to “Google,” not Alphabet
40:00 – Why YC stopped competing with later-stage VCs
42:00 – The role of trust in founder support and mentorship
43:00 – AI-powered consumer apps: Rosebud.ai and personalized therapy
45:00 – What today’s wrappers & MVPs need to become real businesses
47:00 – Codegen, Claude, and the birth of the 200x solo dev
48:30 – Earthquake analogy: AI already hit—most people haven’t noticed
49:15 – Closing thoughts: This is the best time to build
✍️ 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