👋 Hi and welcome to today’s edition of Venture Radar - where we uncover real internet businesses making real money, and break down how they do it.
Here’s today at a glance -
Steal this ideas: AI teammates, white-label AI apps & the AI app repair business.
Side hustles & passive income: 20 underrated boring side hustles, $126K dinner club and $10K washer rentals.
Real businesses: $132K drone farming, $115K budgeting templates & $36K faceless YouTube.
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🥷 STEAL THIS BUSINESS IDEA
Steal this business idea: Group chats with AI agents
Most AI products today are built around a single person chatting with a single AI.
But that’s probably not how people will work in the future.
Imagine a group chat where your teammates brainstorm ideas while AI agents sit in the conversation like additional participants. Instead of switching between ChatGPT, Claude, Slack, Notion, and GitHub, you simply mention an agent like you would tag a friend.
Need market research? Tag the research agent.
Need a landing page? Ask the copywriting agent.
Need code reviewed? Mention the coding agent.
The humans keep discussing while the agents quietly complete tasks in the background and post the results back into the conversation.
The interesting part isn’t another AI chatbot. It’s turning messaging into the operating system for work, where humans collaborate naturally and AI agents become teammates instead of separate tools.
As more companies adopt AI, group messaging with agents could become the default interface for getting work done - making conversations, not dashboards, the center of productivity.
Steal this business idea: White-label AI beauty apps
Most founders think they need a brand-new app for every market. In reality, one product can become multiple businesses just by changing the branding, messaging, and audience.
Take an AI teeth whitening app. A user uploads a selfie, the app analyzes their smile, shows a before/after preview, tracks progress, and recommends products or routines.
Now don’t stop there. Repackage the exact same backend for different audiences:
Young men (15–25): Focus on dating profiles, confidence, and looking better in photos.
Women (30–45): Bundle teeth whitening with skincare analysis and daily beauty routines.
Men (35–55): Pair smile analysis with hair loss tracking, grooming advice, and age-related appearance improvements.
The AI engine stays the same. Only the branding, onboarding, content, influencers, and marketing change.
This dramatically lowers development costs while opening up entirely new customer segments. Each version can have its own TikTok account, landing page, influencers, and community - making it feel like a completely different product.
As AI apps become easier to build, distribution will matter more than technology. The winners won’t always build more features - they’ll package the same product for different audiences better than everyone else.
Steal this business idea: AI app cleanup service
Thousands of apps are being built by non-technical founders using AI coding tools. Getting an MVP live has never been easier. Getting it ready for real users is a different story.
The pattern is already emerging: founders launch an app, get some traction, then hit a wall. Features break unexpectedly, performance slows down, the database becomes messy, and nobody understands how the pieces fit together anymore.
The opportunity? Become the specialist that fixes the last 20%.
Offer a service that audits and refactors AI-generated codebases:
Clean up architecture and technical debt
Fix database and migration issues
Improve reliability and performance
Add monitoring, logging, and security
Prepare the product for real customer growth
Start with founders who built products using tools like Lovable, Bolt, Replit, Cursor, or Claude-generated code. Many have paying customers but lack the engineering experience to scale what they’ve built.
Over time, productize the service:
“AI App Health Check” ($500–$2,000)
“Production Readiness Audit”
Monthly maintenance plans
AI-generated technical debt reports
The interesting part is that AI is making software creation cheaper, which means there will be far more software needing cleanup and optimization later.
Everyone is talking about building apps with AI. Fewer people are talking about the massive market that will emerge fixing them once real users arrive.
The first wave makes money building. The second wave makes money repairing.
