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Vantage is an open-source Windows 11 app that turns a typed prompt into autonomous desktop actions, using AI models to read actual window text via UI Automation, click, type, and run PowerShell rather than relying on screenshots. It brings your own API key for any OpenAI-compatible provider, stores everything locally, and is an early-stage project still seeking failure-case feedback.
Mika is an open-source Android AI assistant that operates your phone apps on a background virtual screen (sending messages, reading group chats, comparing prices, adding to cart, etc.). It supports bringing your own model API key and doesn't route through their servers. It has already gained 3,810 stars in about 3 days since launch.
A follow-up on running agents on an Android phone to publish TikTok posts via app UI automation, detailing bugs around confirming whether a post actually went live and the need for idempotency keys and treating timeouts as 'unknown'.
Google has open-sourced ARTEMIS, enabling AI to perform natural language-driven cross-app automation testing on a real Android phone just like a human. It achieves a 99%+ task completion rate on the AndroidWorld benchmark and natively supports MCP, allowing IDEs like Claude Code, Windsurf, and Antigravity to drive devices directly.
A video demonstration shows web browsing tasks handled entirely by the Clef-Flash 9B decision model running locally, extracting page text at runtime to drive decisions and completing tasks in 11-17 seconds, though performance drops on complex UIs.
WinMind is an early-stage Windows MCP server that uses the accessibility tree for agent interactions instead of screenshots, aiming to improve efficiency and reliability in computer-use agents.
Arize enhances PXI workflows by integrating a JavaScript sandbox to automate multi-step UI tasks, enabling the assistant to control the UI via code for faster results.
The article introduces Windows Harness, an open-source Python tool designed for automating a wide range of Windows tasks, featuring UI automation, screenshots, raw input, and integration with browsers, files, and PowerShell.
The author developed a persistence layer for AI agents to remember app UI structures, reducing operation time from 110 seconds to 59.9 seconds and improving efficiency on tasks like automating Telegram Desktop.
This article explains how to use an AI agent to accurately move a cursor to a specific position, likely for automating UI interactions or tasks.
LUMOS introduces a semantic interaction layer that converts operating system metadata into machine-readable formats, enabling AI agents to interact with computer interfaces more efficiently by reducing dependence on screenshots and visual methods.
A new self-modifying harness is demonstrated drawing a house in canvas, claiming it can handle any UI element.
A comparison of Midscene and Browser-Use, two open-source tools with different focuses: Browser-Use is a web agent for one-time tasks, while Midscene is a vision SDK designed for reliable multi-platform repeated execution.
Midscene's Computer Agent enables desktop UI automation to run headless in Linux CI, automated via xvfb-run, without needing a real machine or VM, and supports Electron, Qt, and GTK applications.
ScreenSearch introduces a system for ambiguity-aware desktop exploration, combining structural screen retrieval and deduplication with a PUCT graph-bandit to handle partial observability in GUI agents. It collects over 1M screenshots across 11 applications and demonstrates a novelty–ambiguity trade-off in exploration policies.
The Midscene.js team decided to completely shift from a DOM + visual hybrid approach to pure visual UI automation, believing that future UI automation must be based on screenshots rather than the DOM. This change reduced token consumption and simplified cross-platform adaptation.
The author introduces Pupil, an open-source tool that enables AI agents to visually inspect PC UIs and identify click targets without relying on screenshots.
A developer demonstrates an AI agent autonomously modifying its own browser automation tools to handle edge cases in the Google Slides interface.
Google releases Gemini 2.5 Computer Use model via the Gemini API, enabling developers to build AI agents that can interact with user interfaces through clicking, typing, and scrolling. The model outperforms alternatives on web and mobile control benchmarks with lower latency and is available in preview on Google AI Studio and Vertex AI.