OpenAI Upgrades GPT-6 Astra Pro to Support Parallel Agents
OpenAI announced an upgrade to GPT-6 Astra Pro in ChatGPT, enhancing response speed and the ability to use plugins and tools, now available to Pro users in the Chat tab.
After the upgrade, multiple agents can simultaneously handle different parts of the same task, allowing users to track the progress of each agent in real-time and review their specific work upon task completion.
This feature breaks tasks into sub-tasks that can be executed in parallel, with different agents advancing separately, while the main process coordinates and summarizes results, enabling users to achieve parallel processing without manual task splitting.
Previously, GPT-6 Astra demonstrated higher completion speed and accuracy in computer usage, terminal tasks, and professional workflows. This upgrade further embeds parallel agent capabilities directly into the ChatGPT interface, lowering the barrier for users to orchestrate multiple agents.
Pro users can now directly invoke this capability through the Chat tab, with the system automatically assigning agents and displaying their progress when handling complex tasks, allowing for individual review of outputs upon completion.
In market dynamics, paid Pro users benefit from task acceleration brought by parallel agents, while developers and enterprises reduce manual orchestration costs through this capability. Competing model providers face pressure to offer native parallel capabilities beyond single-agent sequential execution, with funding and usage increasingly concentrating on platforms that support multi-agent collaboration.
OpenAI has previously provided asynchronous tool invocation and multi-agent capabilities in APIs and Codex. This time, a similar mechanism is introduced to the ChatGPT consumer end in the form of visual progress tracking, expanding its usability.
Source: Public Information
ABAB AI Insight
Since GPT-4, OpenAI has been transitioning its models from conversational tools to executable task agent systems. GPT-6 Astra has made significant progress in computer usage and long-cycle work. The addition of parallel agents in ChatGPT continues its technical path of breaking down complex tasks for parallel processing while reducing user supervision costs through visual progress tracking.
From a capital perspective, OpenAI prioritizes parallel capabilities for paid Pro users, shifting resources from single-threaded conversations to multi-agent collaborative execution. The motivation is to increase the volume of tasks completed in a unit of time and encourage users to delegate more actual work to the system, thereby increasing subscriptions and additional usage consumption.
In analogy, this is similar to software engineering, where large tasks are broken down into modules that can be developed in parallel. Current AI agents are transitioning from single sequential execution to multi-agent division of labor, akin to early distributed systems breaking through single-node performance limits through parallel computing. OpenAI applies the same logic to the conversational interface.
Structurally, this represents a technological substitution, shifting task execution from relying on a single agent in sequence to multi-agent parallel division of labor. The mechanism allows independent sub-tasks to advance simultaneously without waiting for preceding results, enabling users to retain final control through tracking and review, thus allowing the system to shorten the completion time of complex tasks without sacrificing supervisability.
ABAB News · Cognitive Laws
One agent does it sequentially, multiple agents do it in parallel.
Tasks that can be split should be advanced simultaneously.
Seeing progress allows users to entrust work to agents.