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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

Mobile AI Agents Tested Across 65 Real-World Tasks [2026]

AI AgentsJan 23

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.

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AI AgentsJan 23

Agentic CLI Tools: Claude Code vs Cline in 2026

Agentic CLI tools are AI coding tools that can create and delete files, run commands, plan, and execute the coding of the entire project. We tested the leading tools in 20 real-world web development scenarios to see which one truly delivers a production-ready website.

AI AgentsJan 22

15 Security Threats to LLM Agents (with Real-World Examples)

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 22

The Industrial AI Agents Landscape: 30+ Platforms to Watch

Industrial AI agents address the limitations of siloed data by autonomously integrating and deriving actionable insights from IoT, controls systems (e.g. SCADA), and connected assets.

AI AgentsJan 22

AI Agents: Operator vs Browser Use vs Project Mariner ['26]

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 AgentsJan 22

Computer Use Agents: Benchmark & Architecture in 2026

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 19

Best 7 AI Test Agents for QA in 2026

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 16

Building AI Agents with Anthropic's 6 Composable Patterns

We spent 3 days experimenting workflows and agent pipelines in n8n according to Anthropic’s and OpenAI’s guides on building effective AI agents. We are going to distill down everything we have learned to give you a guide to build functional AI agents in your LLM projects.

AI AgentsJan 16

Building a No-Code AI Lead Generation Workflow with n8n

I have been reviewing popular AI sales agents, including  AiSDR and Outreach.io. While these platforms support lead management, they are typically focused on broader sales engagement and delivered as commercial packages with costs ranging from $2K to $5K per user per month.

AI AgentsJan 16

Low/No-Code AI Agent Builders: n8n,make, Zapier in 2026

Low- and no-code AI agent builders let users create automated, AI-driven workflows without writing complex code, making agent development faster and accessible to non-technical teams.

AI AgentsJan 14

AI Agent Deployment: Steps and Challenges in 2026

Organizations are increasingly relying on AI agents to manage tasks that once required constant human effort, such as responding to customer queries, automating workflows, or coordinating data across different systems. While these agents can extend productivity and reduce operational load, their value is realized only when they are deployed correctly in production.