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My First Million

We Bet This App Idea Could Be Bigger Than Reddit

Episode 610: Sam Parr and Shaan Puri talk about the $1b dollar app idea for millennial moms, how Solidcore founder Anne Mahlum emptied her life savings into a pilates studio that she sold for $88M + Shaan writes a movie using ChatGPT.

Shaan PurihostSam Parrhost

Jul 19, 20241h 5mWatch on YouTube

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Chapter summaries

A high-trust “Better Than Google” community: Reddit-style Q&A built for moms
Shaan pitches an app idea inspired by a Facebook group called “Better Than Google,” where millennial moms ask candid questions and get helpful, empathetic answers. He argues the group works because it delivers real-life, experience-based advice with higher trust than typical internet search.
- •Shaan explains the origin of the idea from a past “drunk ideas” discussion about being “Better Than Google.”
- •Sam describes the type of posts that thrive in the group, including sensitive self-image and beauty questions.
- •Shaan highlights how anonymity enables people to ask about taboo or personal topics without fear.
- •A story about troubleshooting iMessage privacy shows how the crowd can outperform generic search results.
- •Shaan frames moms as an especially valuable audience because of their influence over household decisions and spending.
Why AI will increase demand for human, experience-based answers
Shaan lays out his “reverse craving” theory: when something becomes dominant, people start craving the opposite. He predicts AI-driven answers will create more desire for trusted, human communities that share lived experience rather than generic responses.
- •Shaan uses Facebook-to-Snapchat as an example of popularity creating a craving for the opposite experience.
- •He argues cultural pressure can create demand for counter-voices that feel more direct or unfiltered.
- •Shaan says AI search will be huge, but its “opposite” is community wisdom from identifiable humans.
- •He believes a properly seeded “Reddit for moms” could become highly addictive due to the content and trust dynamics.
- •He emphasizes that the key is seeding a like-minded group to keep out trolls and preserve culture.
Can it make money? Comparing ChaCha, Quora, and niche “search engines”
Sam brings up ChaCha as a historical parallel: humans answering questions quickly, but eventually losing out to Google. Shaan responds by mapping different Q&A and search models, arguing there’s room for specialized communities even if they’re smaller than general search.
- •Sam recounts using ChaCha via text messages and questions whether the model can monetize.
- •Shaan contrasts Quora-like communities with paid expert networks and broad Google-style search.
- •They discuss how search gets “siloed” into verticals like restaurants, jobs, and workplace info.
- •Shaan argues niche versions can still become large businesses even as fractions of a massive market.
- •He claims Reddit and Quora aren’t culturally welcoming for the mom demographic he’s describing.
Distribution is the hard part: why building a new destination community is difficult
Sam plays devil’s advocate, arguing it’s extremely hard to get users to leave platforms they already use and actively post content somewhere new. Shaan agrees it’s difficult but insists the idea could be huge if executed with the right seeding and positioning.
- •Sam describes his experience running multiple Facebook groups and how hard it is to drive participation elsewhere.
- •He argues registration, posting, and building habit on a new site/app is one of the hardest internet problems.
- •Shaan acknowledges it’s not easy and calls it a “thread the needle” type of opportunity.
- •Shaan reiterates that seeding and culture are central to avoiding spam and trolling.
- •They frame the opportunity as potentially very high value per user if it works.
Etsy as an analogy: the counter-positioning play against “generic aggregation”
Shaan compares the proposed community to Etsy’s positioning as a human, trust-driven alternative to Amazon’s generic aggregation. He explains how “moms buying from other moms” and personalized recommendations reflect the same desire for authenticity and specificity.
- •Shaan calls Amazon the “Google of shopping” and frames Etsy as the counter-example.
- •He describes Etsy’s appeal: handcrafted, personalized products and visible makers that build trust.
- •Shaan predicts AI answers will increase demand for human recommendations from similar people.
- •He notes the group’s popularity for “best Amazon finds” threads and highly specific fit/quality advice.
- •The discussion reinforces trust and identity as the differentiators.
Using spouses as trend radar: what gets past the “non-early-adopter” filter
Shaan explains how paying attention to what his wife cares about has repeatedly signaled broader consumer trends. Sam contrasts this with his wife being more of a TikTok trend translator than a business signal.
- •Shaan describes initially ignoring stories from the group, then realizing the repeated engagement was meaningful.
- •He says his wife is “high signal” because she’s not an internet-native early adopter, so adoption implies broader appeal.
- •Shaan cites examples where his wife was early: Stanley mugs, vegan/plant-based products, and niche brands.
- •He recalls surprise at paying for an influencer’s workout PDF that later became a major app business.
- •Sam says his wife helps decode cultural moments and emerging artists through TikTok-driven chatter.
ChatGPT as a creative assistant: experimenting with writing a movie scene
The conversation pivots to how Shaan uses ChatGPT beyond search—specifically as a creative collaborator while exploring writing a movie. He describes trying to acquire rights to a book and using AI to learn film roles and the scriptwriting process.
- •Shaan says he’s been exploring turning a book into a movie and learning how films get made.
- •He uses ChatGPT to quickly understand industry terms like “executive producer.”
- •Shaan contrasts Q&A usage with creative collaboration and iterative drafting.
- •Sam shares how he uploads writing samples (like blog posts) to emulate a specific voice for inspiration.
- •They discuss admiration for Aaron Sorkin’s dialogue and what makes it feel fast and natural.
On-demand iteration: replacing the blank page with rapid drafts and feedback loops
Shaan details a workflow where he uploads a screenplay scene and has ChatGPT analyze what makes it effective, then generates variations he can edit. He argues the speed and ego-free iteration changes the creative process by making him the editor instead of the author.
- •Shaan uploads a screenplay PDF and asks ChatGPT to explain why the dialogue works, then to write a new scene with those traits.
- •He describes early drafts as weak but valuable because they arrive instantly and eliminate blank-page friction.
- •He iterates through prompts: changing setting, character traits, pacing, and requesting alternatives.
- •Shaan contrasts this with human collaboration delays and the need to “bubble wrap” feedback to protect ego.
- •He claims the final output was strong relative to his own skill and comparable to paying a professional for an average-plus draft.
Creation as a maze: Sorkin’s “50,000 bad ideas” and founder problem-solving parallels
They reflect on the creative process and how good ideas emerge from many dead ends. Shaan relates Aaron Sorkin’s description of idea generation to entrepreneurship and how outsiders underestimate the iteration behind a seemingly obvious outcome.
- •Shaan quotes Sorkin’s view that one good idea comes after sifting through enormous numbers of bad ones.
- •He compares that mental search to founders working through permutations of a business model.
- •Sam describes how insights often appear during downtime after intense mental processing.
- •They discuss how hard it would be to do that kind of creative labor purely for money.
- •The segment reinforces iteration as the hidden engine behind output quality.
Solidcore’s growth story: Anne Mahlum’s leap from nonprofit to boutique fitness
Sam shares a detailed story about Anne Mahlum, who built a nonprofit and later founded Solidcore after taking a Pilates class. He recounts her decision to invest her savings, open a studio quickly, and scale to many locations before eventually selling the business.
- •Sam describes Anne starting a nonprofit running club tied to helping people experiencing homelessness.
- •He says she discovered reformer Pilates, loved it, and decided to build a studio concept with an edgier brand.
- •Anne reportedly invested $175,000 of savings, built a studio rapidly, and launched with strong early revenue.
- •Sam explains her unit economics logic around classes, reformers, staffing, and filling schedules.
- •He recounts her scaling to multiple studios, taking some funding later, and ultimately selling the business.
The “insane confidence” takeaway: learning fast, separating emotion from logic, trusting decisions
Sam’s main lesson from Anne is her ability to learn a domain, commit, and stay steady without panicking. Shaan challenges what “trust the process” means when early results are strong, and Sam clarifies that confidence also applies to new initiatives and investing decisions.
- •Sam says Anne’s standout trait was her ability to study a topic and trust what she learned enough to act decisively.
- •He contrasts her steadiness with his own tendency to get nervous after committing capital and to bail.
- •Shaan questions whether “trusting the process” matters when the business succeeds immediately.
- •Sam emphasizes that uncertainty can persist even when outcomes look good and that her approach generalized across domains.
- •They note her self-described strength in branding and building community-driven word of mouth.
Every company is messy inside: from tweets to Twitch and “waves you don’t create”
Shaan connects to a quote that even successful companies are chaotic internally. He shares his experience at Twitch, saying it felt like “a clown car into a gold mine,” where exogenous trends drove growth more than controllable internal levers.
- •Sam references a quote Shaan shared: there’s no business that looks good on the inside.
- •Shaan says he expected a polished machine at a large, acquired company but found chaos instead.
- •He repeats the “clown car into a gold mine” line and applies it to Twitch’s situation.
- •Shaan argues marketplaces can survive many internal mistakes once the core network effect works.
- •He describes Twitch as “surfing waves” created by external factors like game popularity rather than creating growth on command.
“Who’s your Elon?” Choosing role models and the trade-offs you actually want
Shaan introduces an essay idea about selecting who you admire because it shapes how you behave and what you pursue. He argues Elon Musk is an obvious entrepreneurial default, but the lifestyle trade-offs may not match what many founders want.
- •Shaan claims founders often default to admiring figures like Elon Musk, Steve Jobs, or Bill Gates.
- •He lists reasons Elon is admired—big companies, ambition, and world-changing projects—while noting personal trade-offs.
- •Sam mentions Elon criticizing Zuckerberg’s leisure, and Shaan calls Elon’s framing “lame” and points to his heavy social posting.
- •Shaan argues it’s important to consciously pick a North Star that matches your desired life, not just business outcomes.
- •They connect this back to admiring Anne’s ability to learn and evolve across chapters of life.
Polymath heroes: Ben Franklin, Jesse Itzler, and the appeal of “riding all the rides”
Shaan names people he admires for having multiple successful arcs rather than optimizing one identity. He points to Ben Franklin as a historical example and Jesse Itzler and Neil Senturia as modern models of reinvention and sustained creative energy.
- •Shaan describes Ben Franklin’s many “eras,” spanning inventions, publishing, politics, and other pursuits.
- •Sam reacts with interest and shares a scene-heavy description of Franklin’s party-driven diplomacy from a TV portrayal.
- •Shaan highlights Jesse Itzler’s many career pivots and adventurous life approach, including entrepreneurship and endurance pursuits.
- •He introduces Neil Senturia and admires his multi-chapter career across writing, real estate, investing, and more.
- •Shaan emphasizes admiration for people who don’t disqualify themselves from new pursuits just because they haven’t done them yet.
Bryan Johnson’s Rejuvenation Olympics: the aging leaderboard, its incentives, and the site’s flaws
Sam revisits Bryan Johnson’s Rejuvenation Olympics leaderboard that ranks people by how slowly they’re aging according to a specific test, and notes the site has improved but remains hard to use. They discuss how the testing cadence creates recurring costs and how results skew toward wealthy biohackers, with a standout example of a seemingly normal participant ranking highly.
- •Sam explains the leaderboard concept and the requirement for multiple tests to be “verified.”
- •Shaan clarifies the core idea: comparing chronological time to biological aging pace across a year.
- •Sam says the costs add up and notes many top-ranked participants are rich, health-obsessed, or monetize biohacking content.
- •They discuss a highly ranked participant who appears to live a relatively normal, healthy lifestyle.
- •Shaan criticizes the site’s usability and argues it needs better identity linking (like Instagram) to make rankings meaningful.
Wrapping up: delayed Bryan Johnson interview, marketing remarks, and the show’s final banter
Shaan apologizes for not releasing a filmed, multi-camera interview with Bryan Johnson and commits to handing it off for editing and publishing. They debate whether Bryan is mission-driven, note his improved social media presence, and end with humorous remarks about one of Bryan’s tracked metrics.
- •Shaan explains he filmed a long interview with Bryan Johnson but delayed release due to editing/perfectionism.
- •He says he assigned the edit to someone else to finally publish it despite the time gap.
- •Shaan argues Bryan is genuine and purpose-driven rather than simply trying to profit, while acknowledging public skepticism exists.
- •They comment on Bryan’s strong online presence and speculate about who runs his social content.
- •The episode closes with jokes tied to Bryan’s tracking of nighttime physiological metrics and the device used to measure them.

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