Sam Barton on Twitter / X

vercel-labs/agent-browser

Browser automation CLI for AI agents

The next user agent

Hey, Rupert here from Unternet. We're building a new, intelligent client for the web — and I'll be posting a little update about our progress here every week.

agent-browser/skills/agent-browser/SKILL.md at main · vercel-labs/agent-browser

Browser automation CLI for AI agents. Contribute to vercel-labs/agent-browser development by creating an account on GitHub.

On Programming with Agents

From the Zed Blog: Agents handle typing so we can focus on thinking.

w3ctag/user-agents

A Draft Finding on User Agents

Warp on Twitter / X

To make this possible, Oz-managed agents do the heavy lifting (coding, planning, testing). This lets community members focus on ideas, direction, and verification.We believe this workflow will let us build a better Warp, faster.https://t.co/bsVk3DE61V 🔖 pic.twitter.com/KqvR6jkZ40— Warp (@warpdotdev) April 28, 2026

1Password & Browserbase - Pioneering agentic autofill for credential access

Browserbase is the complete platform to build and deploy agents that browse and interact with the web like humans.

Are we evolving from pages to apps to agents?

Recently, Vercel came to London and teamed up with Anthropic’s local chapter to host a skills event.

Interact — Scrape a page, then take actions on it with AI prompts or code | Firecrawl

Scrape any page, then click, type, fill forms, and extract data with natural language or Playwright code. Live view, persistent profiles, session chaining.

Lauren Wilford on Twitter / X

I work at a restaurant that does events and we received some challenging last-minute requests from a client. We scrambled to fill them. I realized later that these requests were likely made by an AI agent, and that the human client might not have personally cared. This felt bad! https://t.co/AJWlxDGIA5— Lauren Wilford (@lauren_wilford) September 23, 2026

Big Help or Big Brother? Auditing Tracking, Profiling, and Personalization in Generative AI Assistants

Generative AI (GenAI) browser assistants integrate powerful capabilities of GenAI in web browsers to provide rich experiences such as question answering, content summarization, and agentic navigation. These assistants, available today as browser extensions, can not only track detailed browsing activity such as search and click data, but can also autonomously perform tasks such as filling forms, raising significant privacy concerns. It is crucial to understand the design and operation of GenAI browser extensions, including how they collect, store, process, and share user data. To this end, we study their ability to profile users and personalize their responses based on explicit or inferred demographic attributes and interests of users. We perform network traffic analysis and use a novel prompting framework to audit tracking, profiling, and personalization by the ten most popular GenAI browser assistant extensions. We find that instead of relying on local in-browser models, these assistants largely depend on server-side APIs, which can be auto-invoked without explicit user interaction. When invoked, they collect and share webpage content, often the full HTML DOM and sometimes even the user's form inputs, with their first-party servers. Some assistants also share identifiers and user prompts with third-party trackers such as Google Analytics. The collection and sharing continues even if a webpage contains sensitive information such as health or personal information such as name or SSN entered in a web form. We find that several GenAI browser assistants infer demographic attributes such as age, gender, income, and interests and use this profile--which carries across browsing contexts--to personalize responses. In summary, our work shows that GenAI browser assistants can and do collect personal and sensitive information for profiling and personalization with little to no safeguards.

browser-use/browser-use

🌐 Make websites accessible for AI agents. Automate tasks online with ease.