From journalist to iOS developer: How LinkedIn’s editor builds with Claude Code | Daniel Roth

What It Covers

LinkedIn editor Daniel Roth, a career journalist with zero software engineering background, demonstrates his Claude Code workflow for building and shipping iOS apps to the App Store. He uses two named AI agents — Bob the builder and Ray the reviewer — operating across dual terminal tabs to produce production-grade code on weekends.

Key Questions Answered

• •Dual-agent review system: Run two separate Claude Code instances in parallel terminal tabs with distinct personas: Bob handles building with instructions to plan before coding and document everything in markdown files, while Ray acts as a security-obsessed senior engineer who must approve every plan before Bob writes a single line of code. The human breaks any tie between them.
• •Markdown-first memory management: Claude Code loses context across sessions, especially for weekend-only builders. Counter this by instructing Claude to log every decision, plan, and feature into named markdown files stored in a project docs folder. Starting each new session with "read the retention plan MD" restores full context without re-explaining the entire project history.
• •Feature prioritization via standing Claude chat: Maintain a dedicated Claude web or desktop project chat solely for roadmap management. Feed it user feedback continuously and use a prompt that scores each feature on two one-to-three scales — customer happiness and growth impact — alongside estimated build hours, creating a ranked table to select tasks that match available weekend time.
• •Branch discipline as non-negotiable: Always instruct Bob to build in a Git branch, never directly to main. Roth learned this after a failed merge cost him weeks of debugging. The rule is enforced in Bob's system prompt, making branching automatic rather than a manual decision the builder must remember under time pressure.
• •"Picky customer" as the correct mental model for vibe coders: Non-technical builders are neither PMs nor architects — they function as their own most demanding customer. This reframe clarifies the actual job: walk through what the AI built, identify what feels wrong, and state preferences with conviction regardless of whether the AI agrees, rather than trying to manage scope or understand implementation details.