Building a Generative Coloring Book App with Claude as Senior Dev

A developer on r/ClaudeAI shared their experience building Imagine: Coloring for Kids, a generative coloring book iOS app, using Claude as a senior development assistant. The app lets users prompt any idea (e.g., “Create a happy cat riding a bike”) to generate coloring pages, with themed packs and safety controls.
Architecture
The app follows a pragmatic SwiftUI pattern with service objects and model stores:
- SwiftUI views handle screens
- Models define prompt ideas, theme packs, saved coloring
- Services handle business logic (StoreKit, kid-safe prompt checking)
- Backend worker for image generation
- Swift Data for local storage
Where Claude Helped
As an intermediate iOS developer, the author found Claude most useful for:
- Identifying edge cases that would only surface from user complaints
- Implementing UX-friendly error handling
- Eliminating single points of failure in the architecture
Safety features include guard rails to prevent access to external links, purchases, or inappropriate prompt/rename input. The app offers 5 themed coloring packs as add-ons; the author offered promo codes for community suggestions.
Key Takeaway
Claude acted as a senior dev focusing on robustness and safety — catching issues before release and enforcing sandbox constraints suitable for a children's app.
📖 Read the full source: r/ClaudeAI
👀 See Also

Building a $20/month sales assistant with OpenClaw
A developer built a sales system using OpenClaw that monitors email for leads, researches prospects, writes personalized outreach emails, and prepares meeting briefs, running on a Mac Mini with API costs of $20-35/month.

OpenClaw experiment tests AI temporal continuity with memory and commitment systems
A team has been using OpenClaw for 8 days to test whether persistent memory and accumulated commitments can create temporal continuity in AI. They've implemented episodic/distilled memory splits, commitment checking, and per-turn state logging in JSONL.

Building an Agentic Research System with Claude Code: A Practical Implementation
A developer details how they built six specialized agents using Claude Code to create a living map of 250+ real AI implementations, with a human-in-the-loop orchestration pattern.

Mac Studio local LLM loadout: GLM 5.1, Kimi K2.6, and what's working for coding with Claude Code
A developer shares their May 2026 Mac Studio (M3 Ultra) setup with quantized GLM 5.1 (380GB, 17 tps decode), Kimi K2.6 (460GB, 21 tps decode), and notes on Minimax 2.7, Gemma 4 31B, Qwen 3.5 9B, and pending Deepseek/Mimo support.