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Welcome back 👋 AI just got personal. OpenAI’s decision to allow adult content marks a clear shift toward “AI as companion,” not just assistant. Meanwhile, a solo developer quietly built a $20K/month business by cloning an existing tool, and virtual “founders” are earning eight figures without ever existing. The lines between originality, identity, and automation are blurring fast—and for indie builders, that’s pure opportunity..
In this issue:
OpenAI’s policy shift opens the door to adult AI experiences 🔓
The solo founder cloning SaaS tools and pulling $20K/month 💰
AI workflows turning raw trends into full products ⚙️
The rise of non-human founders earning $10M/year 💡
The era of sameness is over. For too long, we've been running the same plays, chasing the same tired metrics, and expecting different results.
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News
TL;DR: OpenAI will soon allow erotic content in ChatGPT for users who verify their age, marking a major policy shift toward more permissive “adult” interactions. The change, coming with new age-gating in December, reflects Sam Altman’s “treat adults like adults” philosophy and arrives as OpenAI rebalances between safety and user enjoyment.
OpenAI plans to enable erotica for verified adults, alongside the rollout of age verification tools in December.
The move follows criticism that recent restrictions made ChatGPT “less useful/enjoyable,” especially for users without mental health concerns.
Elon Musk’s xAI has already leaned into the “flirty AI” space with anime-style companions, signaling competition for adult-oriented AI experiences.
A new “well-being and AI” council was also announced to guide ethical boundaries—though notably without suicide prevention experts, despite public calls for inclusion.
Altman acknowledged OpenAI made ChatGPT overly cautious but said new mental health detection tools make relaxing restrictions “safe in most cases.”
OpenAI’s pivot highlights a broader industry tension: building emotionally intelligent AI that’s both safe and human-like. As AI assistants become companions and creators, adult content will test not just OpenAI’s moderation systems, but society’s comfort with emotionally charged AI. For builders, this move signals a coming wave of niche, age-gated AI experiences—where intimacy, entertainment, and personal connection become new frontiers for monetization and trust.
Founder Story
TL;DR: Adrian, a solo developer from Austin, built a $20,000/month SaaS by replicating and improving an existing scraping API he found on Micro Acquire. Instead of chasing originality, he validated demand using public revenue data, rebuilt the tool with better reliability and support, and grew entirely through Twitter and consistent execution.
Adrian discovered a scraping API for sale on Micro Acquire, studied its public metrics, and rebuilt it with improvements using his own scraping expertise.
The app, powered by Node.js and hosted on render.com and AWS Lambda, now handles 20M+ monthly API calls for analytics and link tools.
His growth came from simple, direct tactics: offering free credits, engaging on Twitter, and communicating transparently with customers.
Adrian published a nine-step playbook for finding and cloning SaaS ideas, from validating via public listings to executing on a lean stack.
His core lesson: stop searching for “original” ideas—focus on copying what works, improving it, and showing up daily.
Adrian’s story breaks a sacred startup myth: that originality drives success. For indie hackers and small teams, replication paired with improvement is often the fastest route to product-market fit. Public marketplaces like Micro Acquire give builders access to real data—revenues, churn, customer profiles—that can turn inspiration into executable blueprints. In a world obsessed with disruption, the smarter play might be disciplined imitation.
Idea Generation
TL;DR: A new workflow is emerging: founders use AI agents to go from zero ideas to fully built SaaS products. In this episode, creators demonstrate Idea Browser—a tool that scrapes social platforms to surface trending, validated business ideas—and OpenAI’s Codeex, a coding copilot that builds full applications from Product Requirement Documents (PRDs). Together, they form a closed loop: discovery → validation → execution, all powered by AI.
Idea Browser scrapes Reddit, Facebook, and other platforms to identify trending pain points, surfacing ideas with high demand and low competition.
Users can analyze growth, sentiment, and underserved niches, then use GPT-5 to expand those insights into concrete app concepts with names, features, and market fit.
The team’s demo app, Habit Flow, originated from a wellness trend and evolved into a dynamic habit tracker that adapts to users’ energy levels and goals.
Before coding, users generate a structured PRD in ChatGPT, which defines the MVP and guides Codeex to build efficiently.
Codex—a VS Code plugin—lets local or cloud-based AI agents handle coding, debugging, and even parallel tasks like building a marketing plan.
This workflow reframes solo entrepreneurship. Instead of starting from a blank page, founders can now begin with validated data and let AI shoulder the heavy lifting—from idea generation to code deployment. It’s the early sketch of what AI-native startups will look like: human direction, AI execution. For indie builders, this means less time guessing, more time iterating, and potentially, the ability to run an entire startup studio with just one person and a few well-orchestrated agents.
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AI
TL;DR: AI-generated influencers like Mikuela are pulling in millions annually without ever existing physically. Roma Torres, founder of Arcads, explains how businesses now use AI avatars and automation to create scalable, data-driven ad campaigns that rival traditional influencer marketing—faster, cheaper, and often more effective.
AI influencers are earning up to $10M per year, proving that virtual personas can command sponsorships and brand deals on par with real creators.
AI avatars can now display emotion, accents, and realistic lip-syncing—solving the “robotic” problem that used to limit audience trust.
Smart marketers target less AI-savvy audiences (like older or international users), where AI content still feels authentic and performs better.
A language-learning app scaled to $20M ARR through AI-generated Facebook ads, using 650+ creative variations simultaneously for rapid testing.
Automation via APIs allows creators and agencies to mass-produce ads and influencer videos—hundreds per day—with minimal human input.
AI-generated personas are not just a novelty—they’re becoming marketing infrastructure. For startups and agencies, this unlocks scalable, always-on campaigns with near-zero production overhead. The creative edge now lies in strategy and storytelling, not filming. As AI-driven content saturates feeds, understanding which audiences embrace it (and which reject it) becomes a new competitive moat. The next wave of digital marketing won’t be about who’s most charismatic on camera—it’ll be about who can orchestrate the most effective AI talent.
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