Introduction

The atmosphere in Silicon Valley is once again charged, with OpenAI at the center of the excitement. Recent reports indicate that Codex has officially taken over 100% of the coding work for OpenAI researcher “Roon.”

Roon expressed his feelings about this transition:

Programming has always been painful, but it was a necessary path. I’m glad it’s finally over. I’m surprised I was able to escape the shadow of programming so quickly and don’t miss it at all. I even regret that computers weren’t like this before.

The Rise of Codex

Back in December, Boris Cherny, the creator of Claude Code, dropped a bombshell by stating that his contributions to Claude Code were entirely completed by Claude Code itself. This self-evolution has sparked a coding automation frenzy in Silicon Valley.

OpenAI, clearly unwilling to concede such a significant opportunity, has begun its counterattack. Recently, Sam Altman announced that a series of new products related to the Codex coding model would be released in the coming month.

The community’s sentiment is also shifting. Some seasoned developers noted that in 90% of cases, GPT-5.2-Codex can fulfill their requests in one go. While Claude is good, it occasionally inserts “bad code”; in contrast, OpenAI’s new solution is more like Apple—emphasizing an out-of-the-box experience.

The End of Human-Coded Software?

Roon’s revelation has led many online to declare that AI has finally reached this singularity. It seems that the era of humans writing code is indeed coming to an end. After years of model iterations and data accumulation, we appear to be standing at a critical juncture where writing code by hand is becoming increasingly meaningless and even a waste of efficiency.

In Roon’s comments section, people began collectively saying goodbye to the programming era. For many, programming is merely a means to achieve goals, not an end in itself.

Complex syntax is just an expensive price we pay to execute logic, and now these intermediaries can finally step aside.

Radical viewpoints are emerging, with some suggesting that since humans no longer need to read code, we should skip human-readable assembly language and directly use machine code. Today’s programming should vanish like the punch card did.

OpenAI’s Rapid Development

Meanwhile, another explosive piece of news has emerged from within OpenAI. A researcher revealed that with the help of Codex, they built OpenAI’s MCP server from scratch in just three days and completed scale validation. Not only that, but they also launched the Sora Android app within three weeks. A wave of internal tools built and even self-reviewed by Codex is also set to go live.

Without Codex, it’s hard to imagine OpenAI could release products at such an astonishing speed.

Some have commented that this is just the first phase of “takeoff,” and the next step may be truly end-to-end AI autonomous research.

Codex CLI 0.9+ Released

As the paradigm of “human-machine collaboration” has changed, the tools that support this paradigm naturally need to be upgraded. OpenAI seems well-prepared in light of Anthropic’s pressures. Today, Codex CLI has pushed two updates, bringing the version number to 0.91.0.

The most anticipated feature in Codex 0.9.0 is Plan Mode!

Plan Mode differs from the default Code Mode by breaking down programming tasks into two distinct phases:

1. Understanding Intent (clarifying goals, defining scope, identifying constraints, setting acceptance criteria)
2. Technical Specifications (generating a comprehensive implementation plan)

In this mode, the output is detailed enough to execute directly without any follow-up questions.

Plan Mode’s brilliance lies in its commitment to “evidence-first exploration.” Before asking questions, Codex conducts targeted searches in your codebase, checking configurations, schema structures, program entry points, etc.

Additionally, Plan Mode can call a full suite of tools, enabling it to construct high-level implementation plans.

When Codex requires user input, it is structured and focuses only on critical questions that will materially change the plan.

Who Reviews the Code?

It seems perfect, right? Codex thinks, executes, and fills your GitHub. However, as we celebrate this extreme efficiency, an overlooked abyss is opening beneath us—the biggest suspense in this new era is no longer who writes the code, but who reviews it.

As AI generates code at lightning speed, human developers face a DDoS attack on their attention. AI-generated code is produced in milliseconds, while humans take minutes or even hours to understand the context of that code.

This extreme asymmetry between production and review leads to two terrifying consequences:

• Reviewers are overwhelmed and begin to habitually click “Approve,” reducing code review to a formality.
• Code blocks that appear to work but lack systematic thinking are spreading through codebases like cancer.

Conclusion

Regardless of whether we are ready, this era has arrived. For different groups, this means entirely different survival rules.

• To Developers: AI coding tools are not “coming soon”; they have already arrived. The question is how to integrate them without losing core value. Tech experts continue to tackle the challenging thinking work, while AI takes over the role of the “typist.”

• To Non-Developers: The boundaries between “technical work” and “non-technical work” are dissolving. Tools like Claude Cowork create new species, where tasks that previously required developers may soon only need clear descriptions of what you want.

The ability to clearly describe requirements will become the new programming language.

While OpenAI researchers and Claude Code creators claim that AI handles 100% of the code, remember—this is their lab environment, not your production environment. What is certain is that we are experiencing an irreversible shift from “writing code” to “commanding code to be written,” and it is accelerating.