Claude Opus 4.6 vs GPT-5.3 Codex: How I shipped 93,000 lines of code in 5 days
Summary
After testing AI coding assistants GPT-53 Codex and Opus 4.6, the author shipped 93,000 lines of code in just 5 days - a feat they couldn't have achieved manually. Key insights for founders and builders on unlocking AI's potential for rapid product development.
Key Takeaways
- Leverage Git primitives like branches and work trees to enable parallel development with AI agents.
- Use AI to tackle ambitious, complex coding tasks beyond simple landing pages or apps.
- Prioritize enterprise-readiness features like secure authentication and access controls when building AI-powered tools.
- Methodically test and compare the strengths and weaknesses of different AI coding assistants for your specific use case.
- Focus AI efforts on high-impact, repetitive coding tasks to boost developer productivity by 5-10x.
- Invest in tools that provide a seamless, enterprise-grade experience for AI integration across your tech stack.
Related topics
Transcript Excerpt
[music] Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive here on a mission to help you build better with these new tools. [music] Today, we're going to bring you up to date on all the new coding model releases from OpenAI and Anthropic. [music] In case you missed it, OpenAI released last week Codeex, their desktop app for AI engineering, the new model GPT53 Codeex. Try saying that five times fast. And Anthropic released their response, Opus 46 and Opus 46 Fast. If you're new here, then you don't know, but when these new models come out, I put them through their paces. I test them. I test them side by side on the same task and I'm going to give you my opinion about where they do well, where they fall apart, and which one goes where in my AI engineering stack. Spoiler…
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