Build the web for agents, not agents for the web
Recent advancements in Large Language Models (LLMs) and multimodal
counterparts have spurred significant interest in developing web agents -- AI
systems capable of autonomously navigating and completing tasks within web
environments. While holding tremendous promise for automating complex web
interactions, current approaches face substantial challenges due to the
fundamental mismatch between human-designed interfaces and LLM capabilities.
Current methods struggle with the inherent complexity of web inputs, whether
processing massive DOM trees, relying on screenshots augmented with additional
information, or bypassing the user interface entirely through API interactions.
This position paper advocates for a paradigm shift in web agent research:
rather than forcing web agents to adapt to interfaces designed for humans, we
should develop a new interaction paradigm specifically optimized for agentic
capabilities. To this end, we introduce the concept of an Agentic Web Interface
(AWI), an interface specifically designed for agents to navigate a website. We
establish six guiding principles for AWI design, emphasizing safety,
efficiency, and standardization, to account for the interests of all primary
stakeholders. This reframing aims to overcome fundamental limitations of
existing interfaces, paving the way for more efficient, reliable, and
transparent web agent design, which will be a collaborative effort involving
the broader ML community.
684b9fa13b733ba333687066
Xing Han Lù
claimed_verified
2025-06-13T07:39:26.665Z
5fa9ff3ea13e063b8b2b60cb
https://cdn-avatars.huggingface.co/v1/production/uploads/1633380224986-5fa9ff3ea13e063b8b2b60cb.jpeg
Xing Han Lù
user
xhluca
684b9fa13b733ba333687067
Gaurav Kamath
684b9fa13b733ba333687068
Marius Mosbach
684b9fa13b733ba333687069
Siva Reddy
Build the web for agents, not agents for the web
Recent advancements in Large Language Models (LLMs) and multimodal
counterparts have spurred significant interest in developing web agents -- AI
systems capable of autonomously navigating and completing tasks within web
environments. While holding tremendous promise for automating complex web
interactions, current approaches face substantial challenges due to the
fundamental mismatch between human-designed interfaces and LLM capabilities.
Current methods struggle with the inherent complexity of web inputs, whether
processing massive DOM trees, relying on screenshots augmented with additional
information, or bypassing the user interface entirely through API interactions.
This position paper advocates for a paradigm shift in web agent research:
rather than forcing web agents to adapt to interfaces designed for humans, we
should develop a new interaction paradigm specifically optimized for agentic
capabilities. To this end, we introduce the concept of an Agentic Web Interface
(AWI), an interface specifically designed for agents to navigate a website. We
establish six guiding principles for AWI design, emphasizing safety,
efficiency, and standardization, to account for the interests of all primary
stakeholders. This reframing aims to overcome fundamental limitations of
existing interfaces, paving the way for more efficient, reliable, and
transparent web agent design, which will be a collaborative effort involving
the broader ML community.
A new Agentic Web Interface (AWI) design paradigm is proposed to optimize web agents for navigating websites, focusing on safety, efficiency, and standardization to address fundamental interface mismatches.
Large Language Models multimodal web agents Agentic Web Interface AWI DOM trees screenshots API interactions