Dec 9, 2024 · 41m · startup-ideas
3 AI app ideas that are goldmines (and how to grow them)
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
Host Greg Isenberg and AI startup incubator Dan Shipper brainstorm actionable, high-potential generative AI business ideas, covering voice-first interactive media, dataset monetization marketplaces, and counter-culture physical luxury products. They also analyze modern SaaS pricing psychology and audience-first distribution strategies for bootstrapping founders.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Greg holds 42.6% of the talking time here. How this is scored →
Greg as informed peer 3.6 Guest teaching 3.4 Guest disagreement 0.8 Greg pushing back 1.0
speaking balance: gold is Greg, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 24:59 Dan corrects Greg on AI luxury versus artisanal value
Dan directly revises Greg's framing about AI-generated luxury, emphasizing that high status specifically requires human and artisanal craft rather than automated generation.
Hardest push from Greg ▶ 37:48 Greg challenges starting a newsletter in 2025Greg directly questions Dan's recommendation to start with a newsletter and blog, arguing that discovery dynamics have changed and requiring Dan to re-evaluate his advice.
Biggest teaching moment ▶ 10:55 Dan explains 'n of one' predictive science methodologyDan educates Greg on how individual personal biometric bounties represent a departure from traditional population-level linear regression studies in science.
Greg holds their own ▶ 13:27 Greg demonstrates Kaggle dataset monetization strategyGreg shares his screen and articulates a practical Database-as-a-Service business model using Kaggle data, asserting deep entrepreneurial expertise.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Greg as informed peer | Guest teaching | Guest disagreement | Greg pushing back | Why |
|---|---|---|---|---|---|---|
| Episode Preview: AI Startup Concepts with Dan Shipper | 3 | 4 | 0 | 0 | Greg introduces Dan Shipper and prompts him to share AI startup ideas. Dan lays out his concept for interactive, voice-note summaries that colleagues can query, setting an agreeable, collaborative tone. | |
| Two-Way Media and Automated Meeting Podcasts | 4 | 4 | 1 | 2 | Greg asks Dan how to monetize interactive media concepts and target B2B audiences. Dan explains his team's experiments with TLDR meeting podcasts and discusses pricing based on usage rather than subscriptions. | |
| Sponsor Spotlight: Search Engine Optimization with BoringMarketing.com | 2 | 1 | 0 | 0 | Segment begins with Greg's ad read for BoringMarketing.com and transitions into a brief discussion on per-task pricing models in AI applications. | |
| AI Idea 2: 'N of One' Personal Data Bounties | 2 | 6 | 1 | 0 | Dan introduces Kaggle and explains his personal 'n of one' data bounty concept to predict biometric health symptoms like OCD. Greg listens as Dan educates him on how individual predictive modeling can disrupt traditional scientific studies. | |
| Unlocking Startup Opportunities from Kaggle Public Datasets | 6 | 2 | 0 | 1 | Greg pulls up Kaggle on screen to demonstrate concrete startup opportunities, proposing geo-focused database-as-a-service businesses built on public data sets. | |
| AI Idea 3: Modernized Great Books & Luxury Editions | 3 | 5 | 1 | 2 | Dan pitches translating classic public domain literature into accessible, multimodal formats and luxury physical editions. Greg questions the business model and monetization mechanics. | |
| Promo Spotlight: Startup Shortcuts with The Idea Bank | 4 | 4 | 2 | 1 | Following an ad spot for The Idea Bank, Greg and Dan discuss luxury goods. Dan gently pushes back on AI-made luxury, arguing status stems from handmade and artisanal craftsmanship. | |
| Anti-AI Sentiment and Counter-Culture Tech Opportunities | 5 | 4 | 2 | 2 | Greg shares insights regarding anti-AI sentiment among college students, while Dan counters with observations about young children adopting voice-first interfaces. Both explore potential startup moats against incumbents. | |
| Distribution Strategy: Building Audience and Media Funnels First | 6 | 3 | 1 | 2 | Greg challenges Dan on whether starting a text newsletter in 2025 is still optimal. Dan admits YouTube funnels are better today, and Greg provides tactical advice on audience segmentation via ConvertKit/Kit. | |
| Product Plugs, Future Projects, and Episode Conclusion | 1 | 1 | 0 | 0 | Standard wrap-up segment where Dan plugs Every, Spiral, and Sparkle, and Greg delivers outro remarks. |
Statements from this episode (20)
Shipper: Interactive AI voice notes give teams richer context with fewer follow-ups
“And I think, A, that'll just, like, help me, like, avoid, like, answering lots and lots and lots of questions, but B, it just gives everyone else, like, much richer, Access to much richer context. And it's sort of, it's basically like a voice note, but like it…”
Shipper: Every is incubating TLDR to turn meetings into NotebookLM-style podcasts
“One of the internal incubations we have is and I think we'll probably release it, I don't know, like in the next week or two. So it might be before this podcast is out. But it's called TLDR. And what it does is it takes all of the meetings that we have and the…”
Shipper: AI makes storytelling viable in previously uneconomic domains
“The thing that is true about this Wave of AI is it's taking storytelling and it's making it way cheaper than it has ever been before. And I don't think that that replaces professional storytellers, but what it does is it allows you to tell stories in places th…”
Shipper: Every bundles all incubated products into its core subscription
“Our strategy is like everything we incubate, we bundle it into the every subscription.”
Dan Shipper: Per-task pricing in AI will work really well
“I think, and I think that's a new sort of trend in the AI pricing realm is not charging per month, but charging like per successfully completed task or something like that. And I think that's going to work really well.”
Shipper: Anyone is a data scientist now using prompt-tuned GPT-4
“Everyone's a data scientist because, like, everyone, anyone can just, like, prompt tune, like, GPT-IV to, like, find some, like, do something interesting with the data set.”
Shipper: Science should build 'N-of-1' predictive models before generalized explanations
“The way that, like, science proceeds right now is, like, you're trying to find, like, underlying, underlying explanations for things by, like, doing high-end studies on, like, lots and lots and lots of people and, like, doing, like, a linear regression to, lik…”
Shipper: Anyone using GPT-4 can beat a 2019 data science PhD on Kaggle
“Kaggle was built for a time when the people who could do this stuff were people who, like, had, had, like, PhDs in data science. Yep. And it's, like, totally changed now, where, like, anyone can enter one of these competitions and, like, do better than a PhD c…”
Isenberg: The easiest dataset startup model is curated database-as-a-service
“I think the easiest startup ideas with some of these data sets is database as a service. So I've seen that trend pop up more and more, DAS, database as a service, which basically, what does that mean? It's a fancy way of saying you're taking some data, you're …”
Shipper: CliffsNotes and SparkNotes are outdated and their market is captureable
“And I think one, there's tons and tons and tons and tons of students that, like, need to, like, read this for school. And there are all these, like, sites like CliffsNotes or whatever, or SparkNotes that, like, are just so last generation. And I think that mar…”
Shipper: Physical books should return to high-priced luxury goods
“I think like books started out as luxury goods. And then because of the printing press, they became like, there is this push to make them cheaper because you needed ways to get more information into people's hands. And they're no longer necessary as cheap form…”
Shipper: What AI makes cheap will become more expensive as human luxury
“I think that trend will continue with AI stuff. So I look at what is AI making cheaper and then look at what, like that thing will become more expensive just for a smaller percentage of the population.”
Isenberg: A lot of college students are anti-AI
“I think so there's a really interesting trend that's happening right now, which is a lot of college students are anti-AI.”
Isenberg: Building anti-AI products is a huge opportunity
“All that to say, there's a huge opportunity to build Anti AI products just in general.”
Shipper: Kids master Siri because parents give them Apple Watches instead of phones
“Parents didn't want to give their kids phones for obvious reasons and so the compromise position was an Apple Watch. And the thing that Apple Watch has is, like, obviously, like, the screen is, like, it's really hard to do anything on the screen, so kids just …”
Shipper: Incumbent AI feature integrations mostly suck
“There was that whole thing of, like, for the last couple years of, like, oh yeah, every big company's just gonna, like, integrate AI and, like, no startup's gonna be able to compete, and it's just, like, pretty much all of those integrations suck. Like, maybe,…”
Shipper: Incumbents cannot risk UX changes, giving AI startups an advantage
“Big companies are really limited in the risk, the amount of risks that they can take to like make their actual interface good for that specific thing. Cause they can't risk like pissing off their regular users. And that's a tremendous advantage for startups to…”
Shipper: AI wave reopened low-hanging fruit for 'build-for-yourself' apps
“I think one of the interesting things about the AI wave right now is it sort of resets the playing field where there's a lot of low hanging fruit of things to build. And so it becomes that that's a real opportunity to build things for yourself that like was no…”