How to Build Profitable Apps With AI

After explaining the process to each existing customer, B7 Dev asks the AI agent (Claude) to scan the existing codebase and produce a diagnosis of stability, security, common problems and bugs, then offers to fix everything to bring it to top coding standards. Also offers AI-driven performance optimization and builds internal tools/services around the client's startup that used to be too expensive, instead of the client paying SaaS providers. Senior developers check all agent output.

1) Idea level: point the agent at existing apps ('make something similar, change this and that', or 'take the best of both') and ask for screens. 2) Have it write every conclusion into a plan document (MD/PDF); read, edit and question it, since agents lose context as it fills. 3) Ask for a development plan by stages. 4) Build one module (e.g. the server side), test it, freeze it, then add the next part; no one-shot 'build the whole app' prompts, and not micro-prompts either ('the right prompts'), specifying language and tech. 5) Have the agent role-play system architect, security expert and performance reviewer (plugins with preset rules) and review each other's work. Compile and run in Xcode/Android Studio, report bugs back ('Claude, I have this problem. Fix it'). Chaim uses Claude Code CLI; some developers use the Claude API, Codex or Cursor. A senior developer supervises throughout.

Since agentic development cut overall cost and time, B7 Dev prices its services differently (lower), reasoning it is not fair to charge the same. New projects are quoted with agentic development; some prospects on the back burner had been waiting for this.

While employed quoting app projects at a big company, Chaim saw many good ideas die because founders lacked development budget. He started B7 Dev working from South America instead of Europe or the US to lower development cost for those founders.

After spending 1.5 years and $120,000 on a first version that still needed a lot of work, the founder rebuilt 'the app of my dreams' with AI in 2 months and relaunched on the App Store. No detail on tools or what changed.

App Masters has a couple of developers vibe-code apps with AI, publishes them, pushes ASO to see if there is traction, and treats refund requests as feedback: people were willing to pay, so ask them why it didn't live up to their standards and fix that, instead of building internally. (Guest disagreed: prefers a private TestFlight with friends or a Facebook group to save marketing costs.)