Dedicated research agents scan Reddit, X, and App Store categories for pain points — people complaining about broken workflows, missing tools, things they wish existed. They cross-reference demand signals with what's technically feasible, then generate a one-pager: target user, pain points, features, monetisation strategy. Every decision the AI made to get from "idea" to "execution" is documented so you can see exactly why it chose this concept.

The orchestrator pulls the next idea from the queue, spawns a Claude Code session with the right prompt, and the builder agent writes the full Swift/SwiftUI app from a single brief. A separate reviewer agent independently verifies every file for crash risks, missing features, and code quality — because the model that wrote the code will cut corners reviewing its own work. Then 6 automated checks run. Score below 8/10? It retries. Three failures? Flagged for human review. Apple rejected over a million apps last year — these quality gates make sure yours isn't one of them.

The factory is only half the job. Agents run TikTok and Instagram accounts across content categories — fitness, lifestyle, productivity, finance — building audiences with native content. When a relevant app ships, it gets surfaced to an already-engaged following. Content is generated autonomously with self-learning loops: if a hook gets views but doesn't convert, the agent writes that into its own code so it doesn't repeat the mistake. Promo videos are generated for each app before it even hits the store.