OpenAI has taken a significant step by transforming ChatGPT from a simple chatbot into a complex 'orchestration layer'. This new approach enables the integration of embedded applications, an SDK to develop interfaces within conversations, and agents capable of executing complete tasks. The goal is ambitious: to create a unique interface that allows users to work, shop, learn, or design without leaving the conversational environment, thereby configuring a "meta-operating system" that complements the desktop and the browser.
This advance seeks to reduce technological friction: by simply expressing an intention, such as organizing a trip that fits a given budget, the platform can plan, decide, and act using third-party services. However, it also raises questions about the power of intermediation, since whoever controls this gate will determine which applications appear and under what rules, with implications for recentralization and dependencies.
The changes introduced with the apps and agents inside the chat are not only technical, but also conceptual. Applications "arrive" at the user when the system understands the context, which implies a unified user interface, direct actions by the agents, and a recognition of the context and the user's preferences, creating a true conversational command center.
On the one hand, this approach promises immediate productivity and a reduction in operating costs, facilitating simplified discovery and the cohesion of processes. However, it also concentrates risks, such as opacity in the selection of applications and workflows, as well as the possibility of quality and security problems due to the proliferation of low-quality applications.
Drawing on various archetypes from popular culture such as 'Her', HAL 9000, and JARVIS, this 'meta-OS' positions itself as a middle ground, offering customization and the ability to orchestrate. Nevertheless, the deployment of this technology faces real limits imposed by regulation and competition.
To ensure that this conversational operating system is equitable, it is necessary to implement granular permissions, decision traceability, and data portability, in addition to undergoing independent audits. The participation of users and businesses in this process can facilitate a safe and responsible adoption, while promoting technological diversity by avoiding dependence on a single system.
Ultimately, balancing comfort and control is crucial for this new technological paradigm to be truly beneficial for everyone, allowing innovation in human–machine interaction to evolve without compromising users' autonomy and neutrality.
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