OpenAI Raises Codex Limits as AI Agents Move Into Daily Development

When OpenAI launched the Codex app, the shift it proposed was structural: software development was no longer just about writing code faster but about supervising autonomous systems that execute work continuously.

Now, a follow-up move from OpenAI’s leadership makes that intent clearer.

“To celebrate the launch of the Codex app, we doubled all rate limits for paid plans for 2 months! And added access for free/go,” Sam Altman wrote on X.

To celebrate the launch of the Codex app, we doubled all rate limits for paid plans for 2 months!

And added access for free/go.

— Sam Altman (@sama) February 2, 2026

The announcement may read like a temporary incentive, but in practice it addresses a real constraint teams face as they move from experimenting with AI agents to relying on them for sustained, parallel work.

Why Rate Limits Matter More Than Features

In traditional development tooling, limits are rarely a bottleneck. Humans type, review, and commit at a natural pace. Codex changes that rhythm.

The Codex app is designed for long-running agents that plan, build, test, and iterate without waiting for prompts. These agents operate in parallel, revisit failed approaches, and continuously refine outputs. In that model, capacity constraints show up not as latency but as friction in orchestration.

By doubling rate limits for paid plans and opening access to free and Go users, OpenAI is effectively widening the runway for teams to let agents run longer, explore more paths, and surface more work for human review, without constantly hitting ceilings.

This is less about generosity and more about making the Codex operating model viable at scale.  Codex shifts the developer’s role from direct execution to oversight. Developers review diffs, comment on changes, and decide when to intervene, while agents handle the bulk of execution.

Higher rate limits reinforce that separation of duties. They allow agents to maintain momentum in the background while humans stay focused on decision-making rather than babysitting progress.

For teams testing multi-agent setups, where several Codex agents work on the same repository using isolated worktrees, throughput matters. The doubled limits reduce contention between agents and shorten feedback loops, especially during design-test-iterate cycles.

Lowering the Barrier to Adoption

The addition of access for free and Go users is equally telling. It brings Codex’s orchestration model within reach of smaller teams and individual developers who may not yet be ready to commit to paid plans.

That exposure matters because Codex is not an incremental upgrade to an IDE. It requires a mindset shift: planning work in chunks, trusting agents with autonomy, and reviewing outcomes rather than keystrokes.

Temporary access, combined with higher limits, gives developers enough room to experience that shift properly, without prematurely optimising usage.

Taken together, the Codex launch and the rate-limit expansion point to a consistent theme. OpenAI is not positioning Codex as a clever coding assistant. It is positioning it as infrastructure for AI-driven execution.

In that context, limits are not guardrails for abuse but levers that shape how organisations adopt new workflows. Doubling them, even temporarily, nudges teams toward treating AI agents as persistent collaborators rather than disposable tools.

The change may last only two months. The behaviour it encourages could last much longer.