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A key driver for creating ChatGPT Work was the surprising adoption of the developer-focused Codex by non-technical teams like finance and marketing. These users felt they had a "superpower," signaling that agentic capabilities had a much broader audience than initially anticipated.
The narrative that AI agents are only for power users appears wrong. High engagement from non-technical people with complex tools suggests a massive, underestimated consumer appetite for agentic AI beyond simple work tasks, indicating the total market is far larger than assumed.
The planned "super app" overhaul of ChatGPT is less about bundling features for an IPO and more about closing the "advantage gap" between casual and power users. The new UI/UX will be designed to guide people away from simple chat and towards using agents and coding tools, fundamentally changing how they use AI.
Originally a code-writing assistant, OpenAI's Codex is being merged into ChatGPT and expanded into a versatile work agent. Through new plugins for tools like Salesforce and Figma, it can now automate complex tasks in data analysis, sales preparation, and marketing asset creation, not just programming.
Codex was initially a tool for senior engineers, but OpenAI, influenced by Anthropic's user-friendly Claude Code, transformed it into a versatile agent for all knowledge work. This pivot was a reaction to the market's preference for emotionally intelligent, general-purpose AI assistants.
OpenAI chose to feature Codex in its Super Bowl ad, not the more mainstream ChatGPT. This was a deliberate move to broaden Codex's appeal beyond professional engineers and inspire a wider audience of "builders" by framing it as an accessible, creative tool.
OpenAI's strategy to merge ChatGPT and Codex stems from the belief that AI is blurring the lines between roles like coder, strategist, and marketer. Creating hard boundaries between products for different user personas is a losing battle. The future is a unified experience that allows any user to access any capability.
Initially, Greg Brockman and his team viewed Codex as a tool strictly for software engineers. They later realized the underlying technology was not about code, but about general problem-solving and managing context. This insight shifted their strategy from 'Codex for coders' to 'Codex for everyone'.
Early ChatGPT use was dominated by information queries ('asking'). The release of agentic tools like Codex triggered a fundamental shift toward users delegating complex tasks ('doing'), signifying a new era of human-AI collaboration and workflow automation.
OpenAI is combining Codex with ChatGPT, recognizing that the software "harness" enabling Codex's actions is more effective for all knowledge work tasks. This success stems from building the model and its action-taking software together in one team, a key lesson for developing capable AI agents.
With top models reaching comparable performance, differentiation is moving to the "harness"—the user interface, tool integrations, and agentic workflows. OpenAI's ChatGPT Work, an extension of its Codecs interface to general knowledge work, shows that the system surrounding the model is now as crucial as the model itself for user adoption and value.