OpenAI Has Some Catching Up to Do

2026-01-16 · Source: Chain of Thought - Every · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, medium

Summary

Anthropic's Claude Code, particularly with Opus 4.5, has rapidly become the preferred AI coding tool among startup founders and programmers, surpassing OpenAI's Codex. While a month ago the market was split, a recent poll showed almost universal preference for Claude Code. OpenAI initially responded to Claude Code's terminal-first approach with Codex CLI and Web, but its GPT-5 launch in August split its strategy, positioning GPT-5 for professional coding as a pair programmer and ChatGPT for "vibe coding." This contrasts with Claude Code's ability to handle 11 parallel coding projects in six hours and its versatility for non-technical tasks, leading to the launch of Cowork. OpenAI's Codex, despite growing tenfold since August and twentyfold by last night, is seen as too slow and engineer-focused for the emerging "vibe coding" market, which Anthropic is now dominating.

Key takeaway

For AI Engineers and entrepreneurs evaluating coding agents, recognize that Claude Code with Opus 4.5 is gaining significant traction due to its "vibe coding" capabilities and versatility across technical and non-technical tasks. You should consider integrating Claude Code for rapid prototyping and diverse workflow automation, as its user experience and ability to handle multiple parallel projects may accelerate development cycles more effectively than traditional, benchmark-topping models like Codex.

Key insights

Claude Code's "vibe coding" approach is gaining traction over OpenAI's more structured, senior-engineer-focused Codex.

Principles

• Terminal-first AI agents enable rapid prototyping.
• Versatility across tasks drives broader AI adoption.

Method

Anthropic's strategy involved a terminal-first approach, bypassing traditional code editors, and focusing on an "emotionally intelligent" model capable of handling multiple parallel projects and non-coding tasks.

In practice

• Explore Claude Code for rapid project prototyping.
• Consider AI agents for diverse non-coding tasks.
• Evaluate AI tools based on user experience, not just benchmarks.

Topics

• Claude Code
• OpenAI Codex
• AI-assisted Coding
• Agent-native Computing
• LLM Competition

Best for: AI Engineer, Entrepreneur, Machine Learning Engineer, Software Engineer, AI Product Manager

Related on AIssential

• OPUS 4.8!!! (also maybe GPT5.6??) — Opus 4.8 enhances AI agentic capabilities and cost-efficiency through parallel processing and optimized inference.
• How to Maximize OpenAI’s Codex — OpenAI's Codex has significantly improved, offering speed and precision advantages over Claude Code for coding tasks.
• I hated making this video... — Claude Code innovates AI agent interaction and capability through script execution, modular configuration, and parallel processing.
• Meet the winners of the Built with Opus 4.7 Claude Code hackathon — Claude Code and Opus 4.7 enable rapid development of complex, multi-agent AI applications across diverse domains, even for non-programmers.
• Claude Opus 4.6 vs OpenAI Codex 5.3: Which is Better? — Claude Opus 4.6 excels in UI/UX and deep reasoning, while Codex 5.3 prioritizes speed and backend reliability.
• What's going on with Claude Code? — AI models are rapidly transforming software development, shifting human roles from coding to supervision and taste.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Chain of Thought - Every.