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AI Agents

AI agents are software systems that use reasoning, planning, and tools to assist or automate complex tasks. We compare the top open-source and commercial agents.

Explore AI Agents

OpenClaw (Moltbot/Clawdbot) Use Cases and Security 2026

AI AgentsJan 30

OpenClaw (formerly Moltbot and Clawdbot) is an open-source, self-hosted AI assistant designed to execute local computing tasks and interface with users through standard messaging platforms. Unlike traditional chatbots that function as advisors generating text, OpenClaw operates as an autonomous agent that can execute shell commands, manage files, and automate browser operations on the host machine.

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AI AgentsJan 29

15 Threats to the Security of AI Agents

Even a few years ago, the unpredictability of large language models (LLMs) would have posed serious challenges. One notable early case involved ChatGPT’s search tool: researchers found that webpages designed with hidden instructions (e.g., embedded prompt-injection text) could reliably cause the tool to produce biased, misleading outputs, despite the presence of contrary information.

AI AgentsJan 29

Best 50+ Open Source AI Agents Listed

Everyone has been building AI agents so after hands-on testing with popular AI coding agents, AI agent builders and tools use benchmarks to evaluate their real-world capabilities, we put together a curated list of the best 50+ open source AI agents.

AI AgentsJan 29

Top 10+ AI Agents in Healthcare with Examples

AI agents in healthcare are intelligent, autonomous systems that support clinicians, automate routine work, and personalize patient care by delivering data-driven insights, improving diagnostic accuracy, and enhancing both operational efficiency and patient support. We previously explained healthcare AI use cases. This article lists the AI agents for healthcare that automate workflows in clinical operations.

AI AgentsJan 28

Computer Use Agents: Benchmark & Architecture

Computer-use agents promise to operate real desktops and web apps, but their designs, limits, and trade-offs are often unclear. We examine leading systems by breaking down how they work, how they learn, and how their architectures differ.

AI AgentsJan 28

Agentic AI for Cybersecurity: Use Cases & Examples

Agentic AI refers to AI systems that combine models like large language models (LLMs) with automated workflows, tool integration, and decision support. These systems assist security teams in SecOps and AppSec by analyzing alerts, automating routine tasks, and supporting investigative work. Agentic AI tools generally operate under human oversight.

AI AgentsJan 28

Local AI Agents: Goose, Observer AI, AnythingLLM

Local AI agents are often described as offline, on-device, or fully local. We spent three days mapping the ecosystem of local AI agents that run autonomously on personal hardware without depending on external APIs or cloud services.

AI AgentsJan 28

Best 7 AI Test Agents for QA

We evaluated AI testing platforms embedded with AI agents; most were overhyped Selenium/Playwright with marketing. A few were capable of writing/maintaining test cases or visual testing, though even these tools still have notable limitations. From these, we selected 7 platforms and categorized them by their primary focus areas.

AI AgentsJan 23

Mobile AI Agents Tested Across 65 Real-World Tasks

We spent 3 days benchmarking four mobile AI agents (DroidRun, Mobile-Agent, AutoDroid, and AppAgent) across 65 real-world tasks using an Android emulator with applications such as calendar management, contact creation, photo capture, audio recording, and file operations.

AI AgentsJan 22

AI Agents: Operator vs Browser Use vs Project Mariner

AI agents are increasingly marketed as end-to-end digital workers, but real-world performance can vary widely depending on the task, tools, and execution environment. To understand what these systems can genuinely deliver today, we conducted hands-on benchmarking across practical business scenarios.

AI AgentsOct 24

Building Personal AI Agents + 18 Agent Platforms and Tools

We spent the two days experimenting with real-world demos and tools to build personal AI assistants that can handle your tasks, such as scheduling meetings, managing notes, or sorting through emails. We will dive into three main approaches to building and using personal AI assistants, with real-world examples for each: 1.