Nate Herk | AI Automation
I Made Codex and Claude Code Build the Same App. One Clearly Won.
Summary
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This video compares the performance and output quality of Claude Code and Codex in building the same application, analyzing factors like cost, efficiency, and code quality. The creator provides a detailed breakdown of how each AI model approached the same prompt, revealing significant differences in their execution, cost-effectiveness, and reliability.
In this technical comparison, the creator tasks two AI models, Claude Code and Codex, with building the same production-ready application based on an identical prompt. By providing both agents with the exact same goal, the creator assesses them across several metrics including project judgment, architecture, reliability, and pragmatism. The results are stark: Claude Code significantly outperformed Codex in terms of efficiency, cost, and development speed, taking approximately 5.5 hours at a cost of $832, whereas Codex required nearly 62 hours and cost almost $3,000. While Codex demonstrated superior infrastructure handling and test coverage, its over-engineering and lack of focus on user-experience requirements made it less pragmatic. The creator concludes by reviewing the specific performance data, providing a nuanced perspective on why these models differ and emphasizing that selecting the right tool for a specific stage of the development lifecycle is key.
Verdict
Claude Code is significantly more efficient, faster, and cheaper for product development. Codex excels in complex architectural robustness at the cost of time and extreme resource consumption.
Pros
Cons
- Codex exhibited extremely long development times (61+ hours).
- Claude Code's design and UI choices for the generated app were less refined. 20:05
- Both models struggled with some UI-specific bugs during initial generation.
Specs
Compared to
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Codex
Claude Code is significantly faster and cheaper, though Codex shows better long-term architectural stability.
Best for
Not for
Key Points
- 0:26 The creator presents the identical prompt used for both agents to build a production-ready application clone of Typeform.
- 2:13 Introduction of the two apps built: Rillform (by Codex) and Formora (by Claude Code).
- 4:02 A live demonstration of the UI for both apps, highlighting UX bugs found in both.
- 14:34 Detailed breakdown of the AI agents' performance: Claude Code used ~35 sub-agents, while Codex used 126 sub-agents and many more tool calls.
- 15:06 Codex demonstrated higher test coverage with significantly more unit and browser tests than Claude Code.
- 17:13 Final verdict: Claude Code is praised for product judgment and pragmatism, while Codex is lauded for architectural maturity at scale.
- 19:09 Comparison of metrics: Claude Code took ~5 hours at ~$832, while Codex took ~62 hours at ~$2,932.
Worth watching if: You are a software developer or AI practitioner interested in the real-world application of coding agents. This video is highly valuable for understanding the trade-offs between different models regarding cost, development efficiency, and architectural choices.
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