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359 results for “AI Agents”
… for Databases is an open-source Google tool that connects AI agents to databases through the Model Context Protocol standard. The practical reason for this tool check is version 1.7.0 from July 16, 2026: the release adds …
… is about BrowserOS is an open-source browser that treats AI agents as part of the browsing workflow rather than as a separate cloud service. The product page describes it as a privacy-first Chrome alternative with …
… July 29, 2026 asks a simple but hard question: can today's AI agents conduct open-ended AI research when the task is not just tests, code, and benchmarks, but real scientific judgment? The author group, including Peter …
… is about A new paper called ORAgentBench tests whether LLM agents can solve realistic operations-research tasks from beginning to end. The sober answer is: not reliably yet. The best tested agent configuration passed …
… designed less for humans watching a screen and more for AI agents and coding assistants. Instead of pushing a model through long DOM dumps or brittle CSS selectors, the CLI returns compact snapshots with references such …
… Net Security published an analysis on 20 May 2026 about AI agents in IT and network operations. The core issue is not that language models suddenly become malicious. It is simpler: many agents read text that attackers …
… about BrowserOS is an open, Chromium-based browser where AI agents run inside the browser instead of as a separate website. The practical promise is simple: a user describes a task in plain language, and the agent …
… down a problem many developers already feel in daily work: AI agents can solve small tasks correctly, but with far too much effort. Instead of making a simple change directly, they re-read files, inspect dependencies, …
… TencentCloud tool for teams working with multiple AI agents. The reason for this tool check is concrete: on August 5, 2026, the repository appeared on GitHub Trending with 14,386 stars, 1,318 forks, and 1,111 stars …
… introduces OpenSkillRisk. The benchmark tests how well AI agents handle risky third-party skills. The topic is practical because agents no longer only write text. They install tools, read files, call APIs, and change …
