“We actually compete with sleep.” – Reed Hastings from Netflix

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❓ What You’ll Learn

• Why do 90-second serials now win more daily watch time than Netflix on the phone?
• How do free opening episodes and pay-per-cliffhanger unlocks add up to an $11B category?
• Why will free ad-supported viewing overtake pay-per-episode as the dominant Western model?
• What happens when PineDrama hits 17.6M downloads in 30 days while ReelShort tops the charts?
• What happens to your margins when AI makes a series for $30 a minute?
• Why are micro-dramas TV’s slot machine — free pulls, paid spins and whales who fund the house?
  

💎 Why It Matters

ReelShort viewers spend more time in the app each day than they spend in Netflix.

🔍 Problem

You have 3 minutes in line and nothing built for them.

A streaming episode wants 45 minutes. A clip gives you 15 seconds with no story under it.

The in-between moment of your day had no narrative in it.

💡 Solution

Short drama apps captivate you with free episodes of a 90-second cliffhanger serial.

Then sell the rest one episode at a time.

🏁 Players

Western Drama Apps

• ReelShort • Category leader on roughly $400M in 2024 revenue, about 90% of it from US viewers.
• DramaBox • The rare profitable operator: $323M revenue and $10M net profit in 2024.
• Holywater • Maker of the Fox-backed My Drama app, 85M+ installs and a reported $20M hit series.

AI-Native Production

• StoReel • AI-native North America app, $34M raised, built on Google Veo 3 quality.
• Crazy Maple Studio • The US production company behind ReelShort, around $10M a month, a TIME100 company.

Niche Platforms

• Vurt • Creator-owned vertical platform with a 50/50 split, founded by music exec Ted Lucas.
• Kuku TV • India regional-language leader, 100M+ downloads and 10M+ paid subscribers.
• JioHotstar Tadka • Free ad-supported feed that reached 100M users in two months, 42% under 24.

China Super-Apps

• Kuaishou • Short-video giant running its own drama vertical plus the Kling AI video model.
• Tencent Video • Long-form streamer now commissioning micro-drama slates at scale.

Tools

• VertiCast • Swipe-to-match casting app built for vertical-drama producers.
• Stage 32 • Filmmaker network running a DramaBox incubator that routes outside writers into commissions.
  

🔮 Predictions

• Non-English markets will drive most download growth, carried by AI dubbing.
  • LatAm downloads grew 69% in a single quarter, Southeast Asia 61%.
  • 16 of the top 20 international dramas were local-language productions.
• Free ad-supported viewing will overtake pay-per-episode as the dominant Western model.
  • JioHotstar’s free Tadka reached 100M users in two months.
  • DramaBox opened its inventory to programmatic ad demand through The Trade Desk.
• A second US platform will launch a dedicated vertical-drama product.
  • TikTok’s PineDrama hit 17.6M downloads in 30 days.
  • ReelShort and DramaBox were the two most-downloaded streaming apps worldwide, ahead of Netflix.

☁️ Opportunities

• Ship an AI-native studio for Western niches.
  • StoReel raised $34M building AI-native vertical drama for North America.
  • AI tools now make a series for as little as $30 a minute.
• Build AI dubbing for vertical drama to port hits across borders.
  • The first major partnered play, Panjaya and Shortical, formed in 2026 to auto-dub into four languages for a 1B+ audience.
  • Porting a finished 90-second episode into ten languages is now a compute cost, cheap enough to run on every hit.
• Sell production tooling to the people making the dramas.
  • Casting just got its first dedicated app, VertiCast.
  • White-label storefronts already exist, so the open lanes are writers’ rooms, AI script-to-vertical pipelines and per-series analytics.
• Run a for-hire vertical-drama studio that supplies the apps.
  • Incumbents buy series outright at $150,000 to $250,000 per 60-to-90-episode run.
  • ReelShort alone runs a 20-writer room shipping 15 to 20 scripts a month.
    

🏔️ Risks

• Ad Arbitrage • Marketing eats up to 90% of a title’s budget, so margins vanish when ad spend stops.
• Platform Dependence • Growth is rented from Meta and TikTok, the same platforms now launching rival apps.
• AI Commoditization • When a series costs the price of compute, cheap output stops being a moat.
  

🔑 Key Lessons

• The open ground is production and tooling. The apps are taken, so the money in 2026 moved to studios, dubbing and pipes.
• Distribution economics decide who survives. Solve organic attention before you make a better episode, because reach is the real constraint.
  

🔥 Hot Takes

• The next media moat is distribution, now that production has fallen to the price of compute.
• Micro-dramas are TV’s slot machine: free pulls, paid spins and whales who fund the house.
  

😠 Haters

“It’s disposable trash people forget by morning.” 
Even bullish coverage grants the dramas “kind of suck,” so a business with weak brand loyalty re-buys its audience every title. That is also the bet: disposable content that prints $11B is still an $11B business. Taste-driven niches are exactly where a brand can form.

“Quibi already lit $1.75 billion on fire proving this fails.” 
Quibi sold A-list talent on a subscription with a lean-back mindset, while micro-dramas use unknown actors, cheap sets and pay-per-cliffhanger. The format that died and the one winning share a screen size and little else.

“Isn’t this just gambling for your attention?” 
The coin-by-coin unlock and the whale economics borrow straight from free-to-play games, so the comparison is fair. The same loop also funds the cheapest serialized storytelling ever made. Regulation will shape the billing long before it kills the format.

🔗 Links

1. Inside The Numbers Of The Microdrama Year • 35.7 minutes a day and an $11B market, the engagement and size data in one place.
2. Insidious Impact of Micro-Dramas • How micro-dramas hook you with cliffhangers, auto-play and addictive dopamine hits.
3. China’s New License Rules For Micro-Dramas • The registration regime that now gates every title in the largest market.
   

📈 What else?

Trends PRO #0171: Short Drama Apps has more insights.

What you’ll get:

• 23 Players (92% more)
• 6 Predictions (100% more)
• 8 Opportunities (100% more)
• 5 Risks (67% more)
• 4 Key Lessons (100% more)
• 4 Hot Takes (100% more)
• 7 Links (133% more)

With Trends Pro you’ll learn:

• (📈 Pro) Which two moves capture the niches the Chinese apps refuse to serve?
• (📈 Pro) How does a single US viewer end up worth 6x one anywhere else?
• (📈 Pro) Which studio layer will consolidate IP and distribution before the apps run out of niches?
• (📈 Pro) How to turn the 90%-marketing cost line into a service business?
• (📈 Pro) Why will the regulators’ next move hit the exact billing trick that prints the money?
• (📈 Pro) Why does the Quibi lesson invert when unknown actors beat A-listers?
• (📈 Pro) How to build the discovery layer above 50,000 new episodes a month?
• And much more…

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Brought to you by the team behind HeadsUp

This week’s Founder Finds includes:

⚡ AI cost optimization
🔮 How to run a premortem 
📁 An AI workspace tutorial
💸 AI-powered solopreneurs
♟️ A guide to counter-positioning
➡️ And more…

🪶 Remember This

Slow progress is a million times better than no progress.

🤓 Fav Finds

Tools, tweets and more from Trends Pro Members

💸 The Age of the Solopreneur shared by Elia Zane
A report on the rapid growth of solo businesses in the AI era

⚡ How to Scale AI Without Scaling Costs? shared by Eddie Forson
A post on reducing AI costs through smarter infrastructure

📁 AI Workspace Tutorial shared by Kieran Ball
A video on organizing project folders for better agent performance

🏆 Trends Pro Member Wins

🔗 Dru Riley wrote Your Habits Are Only as Strong as Your Worst Day, on the cost of a single target

🛠️ Jason A Erickson launched the waitlist for Project Machine

🧩 Matt Spear launched the Kosu Chrome extension

⚛️ Elie Steinbock launched Atom Eve

📘 Read This

Why Can’t Incumbents Copy You (Even When They Obviously Should)?

The incumbents don’t crush you because copying you would tank their business and make them look foolish for ever doubting you.

• Attack the incumbent’s business model. Vanguard beat mutual funds with lower fees.
• Trap the incumbent in a bad choice. Copying you means killing their margins and admitting they misjudged the market.
• Anchor your model to a real customer need. Counter-positioning only works when you deliver more value, not just a different one.

🛠️ Tools of the Week

🎞️ Multi — Grow on YouTube on autopilot

🧿 HeadsUp.bot — Stay ahead of competitors

💵 StockDrifts — Visual stock research that builds conviction fast

🔧 Try This

What 15-Minute Exercise Saves Big Decisions?

Psychologist Gary Klein has a wording trick that gets risks out of a room where no one feels safe enough to mention them.

• Flip the question from “what could go wrong?” to “assume this failed, why?“. The past tense makes it safer to name real problems.
• Write every reason for 2 minutes straight. Silly, cynical, obvious, uncomfortable. Then pick the 3 most damaging and own them.
• Run it before any decision you have to live with: hire, launch, contract, budget.

🔧 Try This

60 Seconds to Your First Competitive Insight

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Brought to you by the team behind HeadsUp

“Encryption works.” – Edward Snowden

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❓ What You’ll Learn

• Why can someone subpoena the AI chats you deleted?
• How do you charge for AI that physically can’t read your data?
• Which 7 businesses can you start in the gap between encrypted AI and merely “trusted” AI?
• How much do idle MacBooks really earn overnight?
• What vault attack, Helium economics or Apple clause could sink a company built on this?
  

💎 Why It Matters

Blind AI inference launched at or below the price of the kind that can read your prompts.

The choice between privacy and capability just collapsed.

🔍 Problem

You paste a contract, a diagnosis or your source code into AI to get real work done.

That prompt now lives on someone else’s server, under their retention policy and any court order they get.

“Delete” turned out to mean “retain, segregate and produce in discovery.”

💡 Solution

Blind AI companies run your encrypted prompt inside a sealed hardware vault that even the machine’s owner can’t open, so the server side can’t read what it serves.

Encrypted on your device. Attested before it runs. Decrypted only for you.

🏁 Players

Blind Inference Providers

• Darkbloom • Operator-blind inference on idle Apple Silicon Macs, priced ~50% below API rates. The supply-side wild card.
• Tinfoil • YC-backed confidential inference plus a $20/mo private chat. The cleanest “trust the hardware” pitch.
• Confer • Signal creator Moxie Marlinspike’s E2EE chatbot, now being integrated to underpin Meta AI.

Confidential Clouds

• Apple Private Cloud Compute • The reference architecture: stateless Apple Silicon servers Apple itself can’t inspect, now expanding onto Google Cloud.
• Microsoft Azure • Furthest-along hyperscaler: confidential VMs pairing AMD SEV-SNP with H100s plus a managed confidential inferencing service.
• NVIDIA Confidential Computing • The shared silicon: H100 and Blackwell GPUs with GA confidential computing that nearly every startup here rides.

Consumer GPU Networks

• Salad • The largest consumer network: 60,000+ daily active GPUs across 450K+ nodes, where the host can in principle observe the workload.
• Aethir • The revenue leader: reported $39.8M Q3 2025 revenue across 435,000+ datacenter-grade GPU containers.
• io.net • Solana-based GPU aggregator processing up to 4B AI tokens per day after an $8M enterprise deal.

Local and Adjacent Tools

• Ollama • The default local-model runner. Privacy by locality, free locally, with a $20/mo cloud tier that reintroduces a trusted operator.
• LM Studio • Free desktop GUI for local models where data never leaves the machine.
• Exo • Open-source clustering of your own Macs into one inference machine. Darkbloom’s closest technical cousin minus the marketplace.
  

🔮 Predictions

• A frontier lab will sell operator-blind access to a proprietary model.
  • The model developer is the one party a logged API can’t hide from, which is exactly what a hardware vault removes.
  • Providers in the lane serve open weights today, leaving blind access to GPT, Claude and Gemini as unmet demand.
  • Apple now runs Apple Intelligence on Google Cloud vaults it doesn’t own, proving frontier models can run blind on rented silicon.
• Courtrooms will outpace regulators as the demand driver. A major AI vendor will market “we can’t produce what we can’t read.”
  • A court affirmed production of 20 million ChatGPT logs in January 2026.
  • An earlier order preserved deleted chats users believed they had deleted.
  • Each discovery order is free advertising for an architecture with nothing to produce.
• The privacy premium will stay at zero. Blind inference prices at or below standard rates.
  • Competition removes any pricing-power basis for a privacy upsell.
  • Vault overhead is measured below 7%, so there’s no cost basis for a markup.
  • Comparable open-weight models run $0.10-0.15 per million tokens on commodity providers. Blind providers launched under that.
• A public side-channel break of GPU confidential computing will force fleet-wide re-attestation.
  • Apple’s $1M PCC bug bounty prices how much a break is worth.
  • GPU vaults went generally available with CUDA 12.4 and carry far more value per machine, making them the most attractive unbroken target.
  • CPU vaults have fallen repeatedly: WireTap pulled Intel SGX keys with a sub-$1,000 interposer and Battering RAM bypassed AMD SEV-SNP for ~€50.
    

☁️ Opportunities

• Ship the “LiteLLM of blind AI”. Offer one proxy that encrypts, attests and routes to the cheapest vault provider.
  • AI gateways are already how developers route open-weight inference.
  • The wedge is friction. Change one base URL and your app stops leaking prompts.
  • Providers in the lane are OpenAI-compatible by design, including Tinfoil keeping your existing OpenAI clients.
• Launch the blind-AI benchmark site.
  • Providers differ on price, latency and attestation, from post-quantum encryption inside Intel TDX and NVIDIA CC to re-attestation clocks that range from seconds to hours.
  • Build the Artificial Analysis of private inference. Monetize with enterprise API access. The site becomes the category’s front door.
  • Few track them side by side today.
• Start a Mac-fleet supply business for agencies and schools with idle racks.
  • Individual owners earn beer money, which is exactly why aggregated fleets are the play.
  • Handle onboarding, uptime and payouts for a management cut while early-mover margins are best.
  • Roughly 110-130M Apple Silicon Macs have shipped since 2020. Agencies own racks that sit idle 16+ hours a day.
    

🏔️ Risks

• Helium Economics • Consumer-node payouts are hobby-grade. DePIN supply leaves when incentives normalize.
• Prospective Compliance • No EU regulator has blessed attestation, so “compliant by hardware” stays an argument until one signs.
• Apple License • Multi-tenant inference on strangers’ Macs runs on Apple’s certificates in untested territory.
  

🔑 Key Lessons

• Courtrooms are the category’s best salespeople. Sell to the subpoena-afraid first: legal, HR and M&A feel discovery risk in their bodies.
• Trust is migrating from terms of service to silicon. Ask for attestation before a DPA. Build so your privacy claim is a hardware property you can verify.
  

🔥 Hot Takes

• The next AI moat won’t be the model. It’ll be what you can prove you never saw.
• “We can’t read it” beats “we won’t read it” in enterprise deals from here out.
  

😠 Haters

“You sealed the box. What about the pipes?”
Even a blind vault can’t help if the prompt travels in weakly or the answer gets logged after your device decrypts it. The strong builds encrypt the channel end to end and pin the endpoints, so the sealed middle and the secured ends form one chain. The weak ones leave a gap that reaches the same exposure inbound or outbound.

“Local AI eats this from below.”
A good local 14B model is free and private by default. The counterweight is the strongest fact here: Apple, the on-device champion, moved frontier Apple Intelligence to cloud vaults because frontier models exceed what a laptop holds.

“The node operator is exactly the attacker vaults don’t defend against.”
A stranger’s Mac is physically held by the person you’re hiding from, where CPU vaults have already fallen to sub-$1,000 attacks. GPU vaults have no public break yet. The new PCC design uses two independent roots of trust so one broken vendor isn’t fatal.

“Nobody pays for privacy. The prices prove it.”
Tinfoil charges ChatGPT Plus parity and Darkbloom launched below market, so the premium really is zero. That cuts the other way: features priced at zero become defaults. Defaults eat markets.

🔗 Links

1. Powering the next era of Confidential AI • Google’s account of the Apple PCC stack: Titan chip, Intel TDX and NVIDIA CC assembled for blind inference at scale.
2. Project Darkbloom: Unlocking Idle Compute for AI • Eigen Labs’ own economics thesis: idle Mac capacity, 95% provider share and why structure beats subsidy.
3. Confidential Computing on NVIDIA H100 GPUs • NVIDIA’s technical blog on where vault overhead actually hits: PCIe transfers, not GPU compute.
   

📈 What else?

Trends PRO #0170: Blind AI has more insights.

What you’ll get:

• 28 Players (133% more)
• 7 Predictions (75% more)
• 7 Opportunities (133% more)
• 5 Risks (67% more)
• 4 Key Lessons (100% more)
• 4 Hot Takes (100% more)
• 8 Links (167% more)

With Trends Pro you’ll learn:

• (📈 Pro) Which 30-second signal turns “trust us” into proof a normal user can read?
• (📈 Pro) How does a stranger’s idle Mac earn its owner only six dollars a month while the calculator promised $280-600?
• (📈 Pro) Which two moats decide who survives the private-AI consolidation?
• (📈 Pro) Which audio workflow is still an open lane while the field crowds chat?
• (📈 Pro) How do you migrate one regulated vertical off logged APIs after a $670,000 breach penalty?
• (📈 Pro) What UX gap leaves privacy claims unverifiable when vendors hand you measurement hashes?
• (📈 Pro) Why does a “private edition” at +40% fight the whole market’s pricing?
• (📈 Pro) What single upstream flaw could take down every blind-AI provider at once?
• (📈 Pro) How do you run a subpoena-shielded AI workspace law firms would actually buy?
• (📈 Pro) Which Fortune 500 ban turned generative AI from a perk into a firing risk?
• And much more…

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📖 160+ Trends Pro Reports • To make sense of new markets, ideas and business models, check out our research reports.

💬 1:1 Founder Intros • Make new friends, share lessons and find ways to help each other. Keep life interesting by meeting new founders each week.

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Brought to you by the team behind HeadsUp

This week’s Founder Finds includes:

🧪 A SaaS case study
👩‍🏫 An AI teaching skill
🪙 A GitHub monetization tool
🧰 When to build your own SaaS
☀️ How to have a good day, everyday
➡️ And more…

🪶 Remember This

Motivation is a feeling; discipline is a system.

🤓 Fav Finds

Tools, tweets and more from Trends Pro Members

🧰 Build vs. Buy shared by Kieran Ball
An article on when to build your own SaaS

👩‍🏫 Teaching Skill shared by Ben Fisher
A skill that lets your AI teach you anything

🪙 readme.cash shared by Elie Steinbock
A tool to monetize your readme on GitHub

🏆 Trends Pro Member Wins

🦎 Dru Riley published How to Adapt to Change Fast Enough, on staying fit to a moving world

✅ Matt Spear made a WWDC session tracker

📺 Elie Steinbock reached 100,000 subscribers on YouTube

⚙️ Barun Pandey was featured in a Context.dev case study

📘 Read This

What Happens After 600 Days of Failure?

A solo dev spent 600 days shipping things nobody used.

Then built 1 boring scheduling tool the right way. It’s now on track to $100,000/year.

• Embed in the audience before you ship. WriteStack worked because the founders were already on Substack hearing creators complain about scheduling Notes.
• Build in public to compound trust. Sharing the messy progress on The Indiepreneur brought in bigger creators who tried the tool and recommended it.
• Stay long enough to iterate. Past products died after silent launches. WriteStack survived because the founders replied to every support ticket and shipped what users asked for.

🛠️ Tools of the Week

🎞️ Multi — Grow on YouTube on autopilot

🧿 HeadsUp.bot — Stay ahead of competitors

💵 StockDrifts — Visual stock research that builds conviction fast

👀 Watch This

Why Is Burnout Doing Too Little of What Fills You Up and Not Too Much?

Here’s a surprisingly simple daily system to have a good day:

• Do one thing for your mind. Read 5 pages, journal, learn a new language for 10 minutes, sketch something. Whatever genuinely engages your brain before the noise starts.
• Move your body in some way. It doesn’t need to be a gym session. A 2-mile walk, breath work or dancing around your apartment while getting ready counts.
• Feed your soul before the world gets your energy. Meditate, pray, spend time in nature or do a good deed.

🔧 Try This

60 Seconds to Your First Competitive Insight

HeadsUp is an AI-powered competitive intelligence platform that watches your market 24/7.

It doesn’t just tell you what changed… It tells you what to do about it.

🏆 #1 Product of the Day on Product Hunt

Get 90 days of competitor intelligence in 60 seconds with HeadsUp:

• See what you’ve been missing (pricing, features, positioning)
• Know what to do about it, not just what happened
• Get weekly briefs summarizing what matters

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The Most Popular Link From Last Week:
🦾 Agentic Engineering Hacks

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Brought to you by the team behind HeadsUp

“Writing a novel is like driving a car at night. You can see only as far as your headlights, but you can make the whole trip that way.”, E.L. Doctorow

Get Full Access to Trends Pro

❓ What You’ll Learn

• Why did Amazon, Kakao and WEBTOON kill their serial fiction apps while the category grew toward $22B?
• How do contracted authors earn $350 to $1,500/mo writing daily chapters on coin apps?
• Which platform deaths opened a portability gap a solo builder can own this year?
• Why do reading-only serial apps keep dying while survivors earn on adaptations in video, audio and games?
• Why are creator-owned serial tools absorbing authors with a few thousand loyal readers?
  

💎 Why It Matters

Per-chapter fiction is heading toward $22B. AI translation already moves a third of the biggest platform’s revenue.

The chapter is becoming publishing’s growth unit.

🔍 Problem

A novel takes a year to write and pays once, at the end, if it sells.

The biggest serialized fiction platform has 400 million readers paying chapter by chapter, most of them on phones.

You write for a year before you learn if anyone wants it.

💡 Solution

Serialized fiction apps sell stories chapter by chapter.

Free opening, coin unlocks at the cliffhanger, daily updates and AI translation putting each story in every language at launch.

🏁 Players

Pay-Per-Chapter Platforms

• Webnovel • Tencent-backed global platform with about 400 million readers and 530,000 writers.
• Dreame • Stary’s flagship romance app; contracted authors report $350 to $1,500 monthly.
• GoodNovel • Werewolf and billionaire romance at scale; pays signing bonuses plus monthly attendance bonuses.

Free Reading Communities

• Royal Road • The home of progression fantasy and LitRPG; the standard first stop in the serial-first career path.
• Wattpad • The largest free serial community; monetization is invite-only.

Author Monetization Tools

• Ream • Subscription platform built for fiction: tiers, chapter scheduling and reader community.
• Laterpress • Direct storefronts for serial authors; courted displaced Kindle Vella writers.

AI Writing Tools

• Sudowrite • Fiction-tuned AI co-writer popular with authors holding a daily cadence.
• Novelcrafter • Codex-based workspace that keeps long serials consistent across hundreds of chapters.

Short Drama Adaptation Studios

• ReelShort • Crazy Maple Studio’s vertical drama app, roughly $1.2B in 2025 consumer spend, fed by COL Group’s webnovel library.
• Galatea • Inkitt’s paid reader at $10M monthly revenue; GalateaTV turns its proven novels into vertical drama.
• Yuewen • Tencent’s literature group (China Literature); launched 120+ short dramas in 2025.
  

🔮 Predictions

• Apps that only sell reading will keep dying while survivors earn on adaptations in video, audio and games.
  • Kakao shut Radish at the end of 2025, four years after a $440M acquisition.
  • Amazon closed Kindle Vella in February 2025 and WEBTOON, the comics giant that owns Wattpad, closed its prose app Yonder five months later.
  • The survivors monetize beyond reading: China Literature launched 120+ short dramas with 50 billion plays in 2025.
• AI translation will make every serial a global launch by default.
  • Webnovel hosts 17,000+ AI-translated works whose revenue grew 39% to more than a third of platform total.
  • Chinese online literature’s overseas revenue passed 4.8 billion yuan on the strength of translated catalogs.
• Creator-owned serial tools will absorb authors with a few thousand loyal readers: too small for a platform contract to chase, plenty to fund a direct business.
  • The free-serial-to-Patreon-to-Kindle-Unlimited path is now a documented, repeatable career.
  • Laterpress built its growth motion on migrating displaced Vella authors.
  • Ream positions itself as Patreon built for novelists, with chapter scheduling and reader tiers.
    

☁️ Opportunities

• Run an AI-assisted serial fiction studio under multiple pen names.
  • One writer with AI assistance holds a daily cadence across two or three pen names, stacking platform bonuses with owned channels.
  • GoodNovel pays a $150 monthly attendance bonus for 50,000 words across 25 writing days, on top of revenue share.
  • Per-chapter platforms pay for volume and consistency, the exact levers AI assistance multiplies.
• Launch a portability and backup tool for serial authors.
  • Amazon told Vella authors to save their own episodes and metadata before deletion.
  • Three shutdowns in 12 months made the fear recurring: each future closure is an acquisition spike, with displaced authors hunting for a new home in public.
  • The MVP is a browser extension plus a markdown vault; the channel is the author communities doing the grieving.
• Broker adaptation deals between serial authors and short-drama studios.
  • The job in one sentence: find serials with strong reader retention, option the screen rights from the author, pitch the package to studios buying stories and take a fee on each deal closed.
  • China Literature’s adapted Sweet Wife IP series cleared 50 million yuan in profit; adaptation buyers want pre-validated stories.
  • Indie serials outside the big platform libraries have no agent layer; a finder’s fee on a six-figure production pays for a year of scouting.
• Build chapter-level analytics for serial authors.
  • The reader-psychology mechanics are documented well enough to model: cliffhanger placement drives unlock behavior.
  • The data path is real without any platform deal: Royal Road lists follower counts, ratings and chapter histories in public; for the coin platforms, authors connect their own dashboard exports.
  • Platform revenue math stays opaque, so authors placing work across Dreame, Royal Road and Ream decide on vibes. Sell retention curves, drop-off prediction and genre trend tracking.
    

🏔️ Risks

• Stranded Balances • Readers who bought coins on Radish and Yonder lost them at shutdown; one more closure invites refund mandates.
• Formula Saturation • Interchangeable werewolf-billionaire catalogs decay retention; the formula has no moat against itself.
• Whale Dependence • A small share of readers funds the catalog; one policy change to spending caps cuts deep.
  

🔑 Key Lessons

• Platforms die. Catalogs and audiences survive. Keep rights term-limited, archive everything locally and move readers to a channel you own from chapter one.
• The chapter is the product. Cadence beats polish: bonuses, ranking algorithms and reader habit loops pay the author who ships daily.
• Serial fiction is now video’s low-cost testing ground for story ideas. Write with contained casts and 60-second beats; your retention data is the pitch deck.
  

🔥 Hot Takes

• The novel is becoming the cheapest pilot episode in entertainment. A serial with proven retention is a six-figure production decision someone else already de-risked.
• Per-chapter coins did what two decades of ebook innovation couldn’t: made Gen Z pay for fiction.
  

😠 Haters

“The platforms keep dying. Why build a career on quicksand?”
Three deaths in 12 months is real and each stranded authors and balances. The dead share a profile: subscale Western reading apps inside giants with better uses for the capital, while category revenue grew toward $22B. Treat coin platforms as cash flow and own the audience relationship somewhere a shutdown can’t reach.

“You’re feeding writers into a sweatshop.” 
Life-of-copyright exclusivity, ghostwriting clauses and opaque revenue math are documented at the big coin platforms. Non-exclusive paths pay slower with kept rights, so the contract is a per-pen-name choice an informed author makes. The real failure is information asymmetry, which is why contract literacy keeps appearing in this report.

“AI floods will bury these platforms in slop and kill reader trust.”
Volume is exploding and most of it is bad. Coin economics are ruthless about it: readers pay per chapter, so retention data executes weak serials within 40 chapters regardless of who or what wrote them.

“Per-chapter pricing is a dark-pattern casino for lonely readers.”
The cliffhanger-unlock loop deliberately borrows mobile gaming’s compulsion mechanics. The defense is partial: median spend stays low and the reader knows exactly what they’re buying. Expect disclosure norms and spending controls to tighten and expect early adopters of them to brag about it.

“Serious authors should just publish on Amazon. KU pays better per read.”
For a finished book with an existing audience, often true. Serial-first does a different job: it builds the audience while the book is being written, pays during the draft and produces retention data that de-risks the eventual launch. The documented serial career path ends on Amazon; the serial is the customer-acquisition layer in front of it.

🔗 Links

1. Radish Announces the ‘Difficult Decision’ to Close • The closure announcement with the author-royalty terms and the $325M impairment behind it.
2. Inkitt Raises $59 Million, Touts Success with Galatea • How reader-data-driven publishing became a $10M/mo business with a video arm.
3. Korea Short-Form Drama 2026: Webtoons Meet TikTok • How Korea’s webtoon and webnovel IP machine feeds the short-drama boom, from the market that invented the model.
   

📈 What else?

Trends PRO #0169: Serialized Fiction Apps has more insights.

What you’ll get:

• 22 Players (83% more)
• 8 Predictions (167% more)
• 9 Opportunities (125% more)
• 5 Risks (67% more)
• 5 Key Lessons (67% more)
• 5 Hot Takes (150% more)
• 10 Links (233% more)

With Trends Pro you’ll learn:

• (📈 Pro) Which buyers pay $200,000 to $250,000 per series for stories that already proved their cliffhangers?
• (📈 Pro) Why will the person unlocking tonight’s vertical drama episode unlock tomorrow’s fiction chapter?
• (📈 Pro) Why will a one-person fiction studio publicly cross $1M a year?
• (📈 Pro) How did reader data turn a free testing app into a $10M/mo paid reader with a video arm?
• (📈 Pro) Which genre verticals sit empty while incumbents reskin the same three romance formulas?
• (📈 Pro) Which contract clause quietly costs authors their backlist right when vertical drama money shows up?
• (📈 Pro) What turns scattered contract complaints into an organized author revolt against coin platforms?
• (📈 Pro) Who builds the paid contract-scoring layer every serial author checks before signing?
• (📈 Pro) Which moat keeps generic AI tools out of the serial fiction translation market?
• (📈 Pro) Why do the smartest serial-first careers end on Kindle Unlimited?
• And much more…

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This week’s Founder Finds includes:

📣 A social media API
✍️ 7 neuro-writing tricks
🦾 Agentic engineering tips
🪙 Reducing token costs by 90%
💭 Thinking skills for Claude Code
➡️ And more…

🪶 Remember This

Write to get clarity.

🤓 Fav Finds

Tools, tweets and more from Trends Pro Members

🦾 Agentic Engineering Hacks shared by Eddie Forson
A post on current best practices for AI coding

💭 Claude Code Thinking Skills shared by Alper Tunga
39 mental models and critical-thinking frameworks for Claude Code

📣 Publora shared by Elia Zane
An AI powered social media management and automation tool

🏆 Trends Pro Member Wins

🧶 Dru Riley published Analysis Paralysis Is a Bundling Problem, on getting both by doing one

📰 Eddie Forson launched the AI for Decision Makers newsletter

💼 Paul Martin recorded a podcast on AI agents hiring humans

🪮 Shivam launched an AI hairstyle generator with 12 hairstyles

⚽ Elie Steinbock launched a World Cup draft simulator

📘 Read This

What 5-Minute Fix Drops Your Token Costs by 90%?

AI-native SaaS runs at 50–65% gross margins while traditional SaaS sits at 75–85%

Here’s how to close this gap to take home more:

• Audit your inference logs per customer and per feature. The top 10% of users usually generate 50% to 70% of your cost and you can’t optimize what you don’t measure.
• Route Tier-3 tasks (classification, extraction, routing) to Haiku-class models instead of frontier ones. Many teams are paying Opus prices for Haiku work.
• Turn on provider-side prompt caching in an afternoon. It can cut cached-token costs by 90% and is the fastest win available.

🛠️ Tools of the Week

🎞️ Multi — Grow on YouTube on autopilot

🧿 HeadsUp.bot — Stay ahead of competitors

💵 StockDrifts — Visual stock research that builds conviction fast

🔧 Try This

What Are the 7 Neuro-Writing Tricks That Make Content Impossible to Ignore?

Do you feel energized, enjoy working or studying at night? Neuro-writing is crafting content that works with how the brain actually processes words.

These 7 techniques explain why some content sticks and the rest disappears.

• Trigger FOMO with negative language. Words like “ban,” “crash,” “never,” and “fail” create discomfort that motivates action. Fear of looking wrong or missing out is more powerful than the promise of gain.
• Put 2 numbers in your headlines. The first pulls readers in. The second answers “why should I care?” Odd numbers provoke curiosity (“why 11,093 people?”) while even numbers feel friendlier.
• Write sensory words. The brain processes sensory language as scenes. “Grip,” “reel in,” “pack a punch” activate the somatosensory cortex and make readers feel like they’re in your story.

🔧 Try This

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Brought to you by the team behind HeadsUp

“Content is king, but distribution is queen and she wears the pants.” – Jonathan Perelman

Get Full Access to Trends Pro

❓ What You’ll Learn

• How do solo clippers pull five-figure months posting other people’s content?
• Which layer of the stack keeps the money: the marketplace, the agency or the tooling?
• What stops the whole model from being gamed with bot views?
• Where is the open ground that Whop and Vyro have left wide open?
• How much does a brand really pay for a million views?
  

💎 Why It Matters

Whop pushed over 3.5 billion clipped views in a single month and now carries a $1.6B valuation.

The clip became the ad unit.

🔍 Problem

Making content is easy now.

Getting noticed is the bottleneck.

💡 Solution

Pay-per-view marketplaces turn distribution into a performance market.

A creator funds a campaign, independent clippers cut the footage and post it to their own accounts and the platform pays per verified thousand views.

🏁 Players

Clipping Marketplaces and Reward Platforms

• Whop • The largest clipping ecosystem. 3.5B+ clipped views in one month, $2.67B+ lifetime GMV, $1.6B valuation after Tether’s strategic investment.
• Vyro • MrBeast-backed, roughly $3 per thousand views with no audience required. 2B views and over $1M paid out, including a $300K Beast Games reward pool.
• Clipping.io • Performance network skewed toward creator and crypto brands, with over $1.5M paid to clippers.

AI Clipping Tools

• OpusClip • Category leader, 16M+ creators, $215M valuation. Turns one long video into dozens of captioned, reframed clips.
• Vizard • Team and enterprise play with text-based clip editing and approval workflows, 10M+ users, clients including Google.
• Submagic • Caption styling and one-click shorts, 4M+ users, 48 languages, clients including Shopify.

Clipping Agencies and Managed Distribution

• Clipping Culture • The flagship agency, 10B+ views and 100,000+ clippers, clients including Universal Music and HBO Max.
• Clipping Agency • Done-for-you distribution that recruits and vets editors and handles payouts, 2B+ client views.

Adjacent

• Canvas UGC • Get paid to post on brand-owned accounts, a pay-per-view model adjacent to clipping at roughly $2 to $8 per thousand views.
• Fourthwall • Creator commerce and the merch layer creators pair with clipping campaigns.
  

🔮 Predictions

• Brands will make performance clipping a standard ad line item.
  • About 80% of influencer deals now run under $300 as UGC’s campaign share more than doubled.
  • Pay-only-for-views is structurally attractive in a CFO-led ad market.
• AI auto-clipping will commoditize editing and move clipper value to distribution.
  • OpusClip alone serves over 16 million creators, turning one long video into dozens of captioned clips automatically.
  • When the cut is free, the moat becomes who can place clips across accounts and pick the winning three seconds.
• A major platform will deplatform high-volume multi-account clip farmers.
  • YouTube’s inauthentic-content policy already terminated 16 channels with 4.7B combined views in a single month.
  • Top clippers run up to 18 near-identical uploads a day, the exact pattern the new rules target.

☁️ Opportunities

• Run a managed clipping agency for one vertical.
  • Recruit a clipper roster for one niche, run a validation round off a creator’s back catalog and take 15% to 20%. Brand campaigns already run $5,000 to $20,000 with nobody to manage them.
  • There are more brand campaigns than skilled clippers right now.
• Ship vertical auto-clipping for one content type.
  • Wrap a transcription and clip API with niche hook prompts for sermons, earnings calls or sales webinars, sold at $39/mo. Generalist clipping is commoditized, so the edge is domain specificity.
  • OpusClip hit a $215M valuation as a generalist, leaving niche-tuned clippers for high-jargon formats wide open.
• Build a multi-account distribution dashboard for clippers.
  • Run 10 to 30 posting accounts from one screen with safe cadence and account warming, sold at $29 to $49/mo. Staying inside platform posting rules is the wedge.
  • The current 18-posts-a-day workflow is duct tape stitched from spreadsheets and burner phones.
• Launch clipper-training cohorts.
  • A $97 cohort that teaches hook selection and account hygiene, upsold into a recurring job board. Clipping matured into a profession in 2026 and demand for trained clippers outruns supply.
  • Beginners realistically earn $200 to $500 in month one, which fuels heavy search demand for structured training.
    

🏔️ Risks

• Platform Crackdown • Platforms are terminating high-volume identical accounts and a clipper’s accounts are the whole business.
• Bot Views • The reward model pays out on a view count bots can inflate and ad fraud runs above 5% baseline.
• Rate Compression • As AI lowers the barrier and clipper supply floods in, generic per-view rates drift toward the floor.
  

🔑 Key Lessons

• Clips used to be the byproduct. Now they are the product. Design every recording to be cut from the start.
• Pay-per-view is the cheapest distribution in marketing right now. It runs three to eight times below paid social. The arbitrage closes as the feeds saturate.
• The scarce skill is hook judgment. AI made editing free, so invest in taste over tooling.
  

🔥 Hot Takes

• The clip is the new ad unit.
• Follower count is dead. The only number that pays is views.
  

😠 Haters

“This is just gig-economy exploitation. The clipper does the work and the platform keeps the upside.”
Clippers can earn around $1,500 per million views while agencies charge clients a subscription plus a per-view spread. The honest framing is paid practice with a low floor, same-day payouts and no customer-acquisition cost. Calling it a career oversells it.

“The model manufactures outrage. The most clippable moment is the most extreme, so it rewards harm with reach.”
The most profitable clips are often the most outrageous and out-of-context political clips spread misinformation by design. Whitelisting, pre-post approval and content guidelines pull a campaign back from the edge. The default incentive still tilts toward it.

“It’s a fad riding MrBeast’s name. When the hype fades, the campaigns dry up.”
One clipping company booked around $7.7M in sales with 20,000 contracted clippers in ten months and a single Adin Ross campaign drove 430M views from 520 clippers. The durable primitive underneath is pay-per-result distribution cheaper than Meta ads. That gives it staying power as a channel.

🔗 Links

1. What Content Clipping Is and How Payouts Work • The category leader’s own playbook on reward campaigns and getting paid with zero followers.
2. How Clippers Are Overrunning the Internet • Mainstream primer on the scale, the spam fears and the crackdowns.
3. The Case for and Against Clipping • A $7.7M case study set against the brand-safety critiques.
4. Why Skilled Clippers Are Still Scarce in 2026 • The supply and demand read that explains why rates are holding.
   

📈 What else?

Trends PRO #0168: Clipping Businesses has more insights.

What you’ll get:

• 19 Players (90% more)
• 10 Predictions (233% more)
• 12 Opportunities (200% more)
• 5 Risks (67% more)
• 5 Key Lessons (67% more)
• 4 Hot Takes (100% more)
• 13 Links (225% more)

With Trends Pro you’ll learn:

• (📈 Pro) Who will pay clippers in stablecoins across nearly 200 countries?
• (📈 Pro) How big is the fraud hole in a model that pays on views bots can fake?
• (📈 Pro) Why will per-view rates fall below a dollar fifty?
• (📈 Pro) How to get paid to certify clean views?
• (📈 Pro) Which disclosure rule turns a clip army into a regulator’s next case?
• (📈 Pro) How to represent clippers the way agents represent influencers?
• (📈 Pro) Why will creators weaponize clip armies against rivals?
• (📈 Pro) Which major platform will launch its own per-view bounty and keep the arbitrage in-house?
• (📈 Pro) Which niches still pay clippers a premium as generalist rates compress?
• (📈 Pro) Why will out-of-context clips trigger the next platform policy reckoning?
• (📈 Pro) How do you sell clip distribution to brands with no creators on payroll?
• (📈 Pro) Where do mainstream advertisers go when marketplaces skew crypto and gambling?
• (📈 Pro) How do mid-size creators run campaigns and pay clippers without the marketplace middleman?
• (📈 Pro) What analytics play is missing now that AI made the cut free?
• (📈 Pro) How do clippers get early warning before platforms wipe identical accounts?
• And much more…

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Brought to you by the team behind HeadsUp

This week’s Founder Finds includes:

🔍 An AI SEO report
🦉 How to thrive as a night owl
💻 A performance optimizer skill
💼 The state of AI in knowledge work
🧠 65+ mental models for startup success
➡️ And more…

🪶 Remember This

Your pricing says more about your confidence than your costs.

🤓 Fav Finds

Tools, tweets and more from Trends Pro Members

🔍 Ahrefs AI Search Benchmark Report shared by Shivam
A report showing how traditional SEO assumptions are breaking

💻 Codex Complexity Optimizer Skill shared by Alper Tunga
A Codex skill that finds complexity hotspots in your codebase

💼 The Next Era of Knowledge Work shared by Elia Zane
A report on how AI is redefining knowledge work

🏆 Trends Pro Member Wins

♻️ Dru Riley published Turning Failure Into Success: 7,000 Subs, Zero Sales, on profiting from a failed launch

🧰 Mike Williams wrote about building marketplaces with AI

📩 Elie Steinbock launched Inbox Zero in the AWS Marketplace

🤖 Alexandre Kantjas wrote about Claude Cowork

📘 Read This

What Are the 65+ Mental Models That Drive Every Successful Startup?

This founder failed 3 times before building a $200,000,000 company. He collected 65+ mental models as the laws that determine why businesses win or fail.

• Find the desire. People don’t want your product. They want the outcome it creates. Evidence of desire lives in behavior, not in what people say they want.
• Understand what kills your moat. Switching costs determine valuation. Network effects compound them. Market leaders almost always get disrupted by someone who wasn’t even a competitor.
• Apply the laws of human behavior. Every pricing strategy, hiring decision and marketing move works or fails because of evolutionary instincts baked into the people.

🛠️ Tools of the Week

🎞️ Multi — Grow on YouTube on autopilot

🧿 HeadsUp.bot — Stay ahead of competitors

💵 StockDrifts — Visual stock research that builds conviction fast

✍️ Biography of the Week

Satoshi Nakamoto: Absent Authority

Satoshi Nakamoto built money that could run without personal trust, then protected it by becoming impossible to find.

This biography traces the technical record, the political timing and the deliberate disappearance of the most consequential anonymous person in financial history.

Listen to the episode (21 min) →

Read the full biography →

👀 Watch This

How Can You Thrive as a Night Owl?

Do you feel energized, enjoy working or studying at night?

You’re a night owl!

Here’s how to thrive during the day as a night owl:

• Make a list of tasks the night before. Prepare for the day.
• Do things that force you to move in the morning. Walk or exercise.
• Do things that don’t need a lot of energy. Check emails, run errands.

Use your peak performance time wisely. Work or spend time with your family.

🔧 Try This

60 Seconds to Your First Competitive Insight

HeadsUp is an AI-powered competitive intelligence platform that watches your market 24/7.

It doesn’t just tell you what changed… It tells you what to do about it.

🏆 #1 Product of the Day on Product Hunt

Get 90 days of competitor intelligence in 60 seconds with HeadsUp:

• See what you’ve been missing (pricing, features, positioning)
• Know what to do about it, not just what happened
• Get weekly briefs summarizing what matters

See what you’ve been missing 👉 Try HeadsUp free

👋 New Trends Pro Members

• David Longhini

• Stuart Hoover

• Stephanie Cion

• Alex

The Most Popular Link From Last Week:
🗂️ All-In-One Bookmark Manager

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📖 160+ Trends Pro Reports • To make sense of new markets, ideas and business models, check out our research reports.

💬 1:1 Founder Intros • Make new friends, share lessons and find ways to help each other. Keep life interesting by meeting new founders each week.

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Brought to you by the team behind HeadsUp

“People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.” – Theodore Levitt

Get Full Access to Trends Pro

❓ What You’ll Learn

• How are solo founders hitting 8 figures while the big dating apps keep shrinking?
• Which pricing model turns a churning Rizz app into a durable business?
• Where is the open ground the “pickup line” crowd keeps ignoring?
• How do you build for a market that uses AI freely yet punishes anyone caught using it?
• Why will agent-to-agent screening run the top of the funnel before two humans ever meet?
• What makes a screenshot-to-reply wrapper a thin moat anyone can clone in a weekend?
• Why is the profile photo the highest-leverage variable nobody closes the loop on?
  

💎 Why It Matters

AI dating usage jumped 333% in a year while the apps it runs on keep losing paying users.

The hardest part of dating just got handed to a model.

🔍 Problem

Dating apps made matching free and frictionless. They still haven’t solved the conversation.

The bottleneck moved from getting matched to knowing what to say.

💡 Solution

AI dating assistants coach a real person to talk to other real people.

You screenshot a stalled chat or a profile.

A multimodal AI model reads the context and hands back openers, replies and profile fixes.

🏁 Players

Reply and Opener Generators

• Rizz • The category-definer. Screenshot a stalled chat, get replies in a chosen tone. Over 7.5M downloads since 2022.
• YourMove AI • The most complete text toolset: openers, reply suggestions and profile rewrites in one app.
• Plug AI • Screenshot or selfie in, pickup lines and comebacks out, across the major apps.

Profile and Photo Optimization

• Roast • Upload selfies, get an AI photo critique plus an AI-generated dating photoshoot, purpose-built for dating apps.
• PhotoAI • Trains on a handful of selfies to generate dating and headshot photos. Profitable solo business, 29.7M photos generated.
• DatePhotos.AI • Dating-specific photo generator that returns 80 to 180 shots across 40-plus scenes, each scored for realness.

AI Matchmaking

• Sitch • Concierge AI matchmaker that sells curated introductions in setup packs, no infinite swipe deck.
• Iris Dating • Learns your facial preferences and acts as a personal matchmaker.
• Keeper • AI matchmaker for marriage-minded users, pairing AI suggestions with human review. Raised a $4M pre-seed.

Incumbent Platforms

• Hinge • Shipped AI Convo Starters and Prompt Feedback to push stalled matches into conversations.
• Bumble • Added AI photo feedback and is testing an AI matchmaker to replace the swipe.
• Tinder • Match Group is pouring AI investment into fixing the matching experience.
  

🔮 Predictions

• The endgame will be agent-to-agent screening before two humans ever meet.
  • Known uses a voice AI to profile personality and book in-person dates.
  • Industry forecasts expect most top dating apps to offer agentic discovery and scheduling by late 2026.
• The long tail of near-identical rizz wrappers will collapse to a handful of survivors.
  • Rizz already shows the prize at over 7.5M downloads.
  • Early economics were real, with one run to roughly $190,000/mo on 1.5M downloads.
    

☁️ Opportunities

• Build a photo-to-match-rate optimizer that bills on measured lift.
  • Roast generates and rates photos but stops short of closing the loop on real match-rate gains.
  • The photo is the highest-leverage variable in the funnel, so tie the price to the result.
• Charge for dates booked, billed on the outcome the user actually wants.
  • The closest proof is matchmaking sold by the introduction, where Sitch charges per setup.
  • Billing on dates forces you to capture which conversations convert, the one signal a phone keyboard can’t see.
    

🏔️ Risks

• Thin Moat • Most apps are a prompt over a model anyone can call, so price and novelty erode fast.
• Channel Decline • The dating apps these tools depend on keep losing paying users.
• Abuse Surface • The same engine that helps a shy person also industrializes romance scams.
  

🔑 Key Lessons

• The only metric worth owning is the date itself. Messages are free to copy, so they make a worthless moat, while real-world meetings are the one signal platforms can’t see inside your app.
• Build the tool users are meant to outgrow. A fake persona collapses on the first date, so the product that visibly builds skill survives the authenticity backlash and earns referrals.
  

🔥 Hot Takes

• Charisma just became a monthly subscription.
• In a few years your profile dates for you, screening matches before you ever swipe.
  

😠 Haters

“Two bots flirting with each other isn’t a relationship.”
Fair. The fake-persona apps deserve to fail when the witty texter freezes in person. The tools that coach genuine skill survive the first date because the user actually improved.

“Why would I pay for this when ChatGPT is free?”
For most people the wedge is the screenshot-to-reply speed and the dating-specific tone, not raw capability. The apps that survive own a distribution channel or outcome data that a generic chatbot can’t match.

🔗 Links

1. Rizz Co-Founder Q&A • The category-definer explains the screenshot-to-reply playbook in his own words.
2. Every Dating App Has AI Now • How the incumbents bolt AI onto matching and whether it helps.
3. The New Rules of Online Dating: Swipes, Scams, and Synthetic Charm • Nearly half of US daters report being scam-targeted, with AI profiles and chatbots industrializing the same playbook honest assistants use.
   

📈 What else?

Trends PRO #0167: AI Dating Assistants has more insights.

What you’ll get:

• 22 Players (83% more)
• 5 Predictions (150% more)
• 5 Opportunities (150% more)
• 5 Risks (67% more)
• 5 Key Lessons (150% more)
• 4 Hot Takes (100% more)
• 7 Links (133% more)

With Trends Pro you’ll learn:

• (📈 Pro) Who raised $6M to book 2,000 real dates a month without a swipe deck?
• (📈 Pro) Why does distribution beat the feature when the reply generator clones in a weekend?
• (📈 Pro) How do you launch the verified-human counter-brand before AI openers flood every inbox?
• (📈 Pro) Why will incumbents ship first-party AI and choke third-party reply tools?
• (📈 Pro) Why does winning at matchmaking wreck your unit economics?
• (📈 Pro) How do you sell the safety and age-verification layer apps can’t build in-house?
• (📈 Pro) Why is “human-verified” becoming the next status symbol on a profile?
• (📈 Pro) Why do dating apps fear you not needing them more than AI-on-AI dates?
• And much more…

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This week’s Founder Finds includes:

♟️ When to quit?
💵 Naval on sales
🗂️ A bookmark manager
🧠 AI-powered habit change
🤖 An introduction to Hermes
➡️ And more…

🪶 Remember This

Success is the sum of small efforts repeated daily.

🤓 Fav Finds

Tools, tweets and more from Trends Pro Members

💵 Naval on Sales shared by Barun Pandey
A podcast episode with Naval

🗂️ Raindrop.io shared by Stan Wilson
An all-in-one bookmark manager tool

🤖 Why I’m Switching to Hermes shared by Elia Zane
An introduction to using Hermes Agent

🏆 Trends Pro Member Wins

🚧 Dru Riley published Consistent But No Progress? It’s the Hurdle Rate, on how consistency can kill you

📅 Maciej Cupial launched Calendesk in the ChatGPT Store

🤖 Alexandre Kantjas is hosting a workshop on Claude Cowork

⚽ Elie Steinbock launched a fantasy football game for the World Cup

🎧 Listen To

What Will AI-Powered Habit Change Actually Look Like?

Here’s a breakdown of what the military figured out that most productivity advice misses.

• Understand the cue-routine-reward loop. The brain doesn’t distinguish between good and bad habits. It just runs the loop automatically, which means you can hack it by changing the cue or the reward.
• Design for immediate rewards. Habits tied to long-term goals (saving money, losing weight) fail because the brain needs a near-term payoff to reinforce the loop.
• Treat willpower like a battery. It depletes throughout the day, which is why planning for relapse matters more than hoping you’ll stay strong.

🛠️ Tools of the Week

🎞️ Multi — Grow on YouTube on autopilot

🧿 HeadsUp.bot — Stay ahead of competitors

✨ Charm — Get customers through Google and AI Search

💵 StockDrifts — Visual stock research that builds conviction fast

❔ Ask Yourself

How Does “Train the Monkey” Mental Model Save Founders Millions?

Annie Duke is a decision science expert and former poker pro. She says that founders who learn to quit are building better companies than those who never do.

• Recognize pivot as a quit. Stewart Butterfield quit building an online game and made Slack. The Notion founders threw out all their code and rebuilt from scratch.
• Set kill criteria. Write down specific states and dates. “If by [date] I haven’t reached [specific metric], I quit.” Doing this early is the only way to avoid moving the goalposts when you’re inside the failure.
• Tackle the monkey before the pedestal. Find the hardest, most uncertain part of your idea first. Every “low hanging fruit” you pick before solving the bottleneck creates sunk costs and an illusion of progress.

🔧 Try This

60 Seconds to Your First Competitive Insight

HeadsUp is an AI-powered competitive intelligence platform that watches your market 24/7.

It doesn’t just tell you what changed… It tells you what to do about it.

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• See what you’ve been missing (pricing, features, positioning)
• Know what to do about it, not just what happened
• Get weekly briefs summarizing what matters

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The Most Popular Link From Last Week:
💧 AI Agent Monitoring​ Platform

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📈 Unlock Pro Reports, 1:1 Intros and Masterminds

Become a Trends Pro Member and join 1,200+ founders enjoying…

🧠 Founder Mastermind Groups • To share goals, progress and solve problems together, each group is made up of 6 members who meet for 1 hour each Monday.

📖 160+ Trends Pro Reports • To make sense of new markets, ideas and business models, check out our research reports.

💬 1:1 Founder Intros • Make new friends, share lessons and find ways to help each other. Keep life interesting by meeting new founders each week.

💲 100k+ Startup Discounts • Get access to $100k+ in startup discounts on AWS, Twilio, Webflow, ClickUp and more.

Brought to you by the team behind HeadsUp