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Happy Tuesday 👋 Some weeks it feels like the internet is sprinting in every direction at once. This was one of those. From no-code clones to AI-fueled exits to OpenAI’s next business model, builders are moving fast, and the ground keeps shifting. Let’s dive in.
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In this issue:
OpenAI eyes e-commerce, not ads (for now) 📣
Rocket.new clones a $100M app 💥
Is AI in a bubble? What to build either way 💬
From no-code SaaS to profitable exit 👏
Why AI agencies fail (and what to do instead) 👀
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News
Will ChatGPT ever run ads?
TL;DR: Subscriptions are growing faster than expected, but OpenAI isn’t ruling out ads completely. For now, the bigger bet is commerce.
20M+ paid subs and 5M+ businesses now use ChatGPT, with new cohorts monetizing as strongly as early ones.
Turley is “humble enough” not to rule out ads but says they’d need to be tasteful and never interfere with answer quality.
Near-term focus is “Commerce in ChatGPT”: recommending products and potentially taking a referral cut if users buy.
OpenAI frames commerce as a way to keep answers independent while still unlocking a huge new revenue stream.
Ads may eventually appear in edge markets, but subscriptions and commerce are already proving OpenAI can scale without breaking trust.
Startup Idea
Cloning a million-dollar app with AI (no code)
TL;DR: Mikey used Rocket.new, an AI-powered app builder, to recreate the popular plant ID app Picture This without writing a single line of code. The build included Gemini-powered plant scanning, push notifications, safety alerts, subscriptions via Stripe, and full iOS/Android support—shipped in days, not months.
Rocket.new generates production-ready Flutter code from prompts, giving builders ownership instead of no-code lock-in.
Core app features included plant recognition, health diagnostics, and treatment suggestions using Google Gemini APIs.
Engagement layers like watering reminders and seasonal care tips turned it into a companion app, not just a one-off utility.
Stripe integration enabled a $4.99/month premium tier, showing monetization doesn’t need to be an afterthought.
The real differentiator will no longer be technical execution but distribution, positioning, and community. If app development is now accessible to anyone with an idea and persistence, the moat shifts from code to strategy.
Productivity
Are we in an AI bubble—or just the build-up?
TL;DR: The AI bubble debate is heating up. On one hand: hype-driven valuations, shaky economics, and copycat startups all riding on the same base models. On the other: undeniable utility, falling inference costs, long-term enterprise adoption, and billions in durable infrastructure investment. The takeaway? Even if this is a bubble, history suggests lasting winners will emerge from the shakeout.
Valuations at seed are hitting $20–30M with little revenue, echoing dot-com–era exuberance.
Most startups are distribution plays on top of the same foundation models—making differentiation about go-to-market, not core tech.
Unit economics are fragile, with many apps losing money per user and relying on VC to cover GPU/API bills.
Yet, AI is proving sticky: multi-year enterprise contracts and consumer adoption curves are real, not speculative.
For founders, the “bubble or not” question isn’t academic—it changes strategy. If you believe a crash is coming, focus on cash flow, lean ops, and extending runway. If not, lean into growth, proprietary data, and community moats. Either way, distribution and retention—not raw AI capability—will separate survivors from the noise.
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Founder Story
TL;DR: JJ built and sold Trade Backlinks, an AI-powered SaaS that automated backlink acquisition, almost entirely with no-code tools like Bubble plus AI and API integrations. He validated the product on his own projects, reached early traction, and eventually sold it via acquire—citing his passion for building over scaling.
JJ validated Trade Backlinks by using it on his own domains and podcast, proving value before chasing growth.
The platform automated the tedious backlink outreach process, showing how steady, low-volume outreach can compound.
He sold the business on acquire to an SEO agency owner, highlighting the value of SaaS marketplaces for small but profitable exits
JJ stresses the importance of knowing when to let go: if you love building but not scaling, selling early can free you to focus on your strengths.
JJ’s journey is a blueprint for founders who love the creation phase but not the grind of growth. AI + no-code drastically lower the bar for launching SaaS, but passion and distribution still make or break a product. Marketplaces like acquire.com now give indie builders real exit opportunities—turning even “small” projects into stepping stones.
Tutorial/Framework
Don’t start an AI agency… do this instead
TL;DR: Starting an AI agency sounds exciting, but most new builders crash early from delivery chaos, underpricing, and client churn. This video lays out a smarter path: begin as a freelancer, prove results, then evolve into a high-leverage consultant solving real business problems with AI workflows.
Freelancing lets you build proof, sharpen client skills, and avoid overhead—critical before you touch anything "agency".
Start by solving one clear problem for a specific niche; vague generalist offers don’t sell.
Show, don’t tell: use demos or simple before-after case studies to prove ROI.
Speak in terms of time and money saved—this is how you close deals.
Most indie AI builders skip ahead to “build an agency” and quickly drown in ops. This roadmap flips that: master delivery solo, earn trust through results, and position yourself as the rare expert who actually solves business problems. If you're selling AI services, this is the blueprint.
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