
A tweet from Nick Fiacco, a core contributor to OpenAI's innovative "Operator" project, has sparked discussion within the artificial intelligence community by stating, "Documentation is deprecated." The concise declaration, made on November 7, 2025, suggests a significant shift in how information and operational guidelines are perceived in the fast-evolving AI landscape, particularly from an insider at a leading AI research organization.
Fiacco is recognized for his work on OpenAI's Operator, an advanced AI agent designed to perform tasks autonomously using its own web browser. This project leverages a Computer-Using Agent (CUA) model, combining powerful vision capabilities with advanced reasoning to interact with graphical user interfaces. The development of such self-sufficient AI systems potentially reduces the reliance on traditional, static documentation for operational procedures.
OpenAI has a history of frequently deprecating older models and APIs as new, more capable versions are released. For instance, the company has announced the deprecation of various models, including earlier GPT-3 versions and text-davinci-003, with specific sunset dates. Similarly, the Assistants API is slated for deprecation in early 2026, to be replaced by a new Responses API.
This ongoing cycle of updates and retirements means that documentation for previous iterations quickly becomes obsolete. Fiacco's statement could therefore reflect a broader sentiment within OpenAI that the rapid pace of AI development inherently makes static documentation challenging to maintain and potentially less relevant for cutting-edge systems that can adapt and learn. The rise of agentic AI, capable of understanding and executing tasks without explicit, detailed instructions, further supports this perspective.
The implication for developers and users is a potential move towards more dynamic, perhaps AI-generated or context-aware forms of guidance, rather than relying on fixed manuals. While a bold statement, "Documentation is deprecated" underscores the unprecedented speed of innovation in AI and the need for new paradigms in how we understand, interact with, and manage these intelligent systems.