August 2026 Summaries

An experiment compared Fable 5 using Claude Code, GPT-5.6 Sol using Codex, and GPT-5.5 as a control by having each autonomously build three Expo and React Native applications from identical prompts, templates, tools, and simulator-validation requirements. Across an AI calorie tracker, a functional ChatGPT clone, and a SwiftUI sleep-tracker rewrite with live activities, Fable 5 consistently produced the highest-quality code, cleaner and more cohesive interfaces, fewer lines of code, and the fastest completion times, though it carried the highest hourly cost. GPT-5.6 was generally competitive in quality and particularly persistent in resolving well-defined problems, but it could spend much longer in validation loops, including 13.5 hours on the most complex rewrite. GPT-5.5 showed weaker results, including an inoperative chat feature, leftover boilerplate, visible UI compromises, and consistently greater technical debt. The experiment consumed more than two billion tokens and about $2,000, largely because simulator testing captured screenshots, interaction data, and metadata for every feature and debugging cycle; the author suggests delegating validation to subagents to limit context consumption. The conclusion recommends Fable 5 for end-to-end product development and larger code changes, while positioning GPT-5.6 as useful for focused automation, computer-use tasks, and smaller technical requests.