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.
Top 30+ Agentic AI Companies in 2026
Though AI agents are being hyped and some companies rebrand their chatbots as agentic tools, there are still few agents in production. Previously, we benchmarked some of these capable AI agents over several real-world tasks. In this article, we identified key agentic AI companies that live up to the hype.
Open Operator: A Free Alternative to OpenAI's Operator
Early in 2025, OpenAI announced Operator, a new research preview of ChatGPT that serves as an agent for repetitive activities. It can browse for plane tickets, book a table, or shop online, and execute daily digital tasks for you on its own.
10 AI Coding Challenges I Face While Managing AI Agents
From what I’ve observed, AI agents are most effective in the early, exploratory stages of development, such as: testing ideas, drafting solution paths, or helping clarify technical direction. They streamline discovery, but their limits become clear when work requires steady judgment, strong context awareness, or long-term strategic reasoning.
Best 50+ Open Source AI Agents Listed in 2026
Everyone is building AI agents these days. 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 Agents for Competitive Intelligence: Tools and Applications
The competitive intelligence landscape is shifting rapidly. MarketsandMarkets projects the global AI agent market will grow from USD 5.1 billion in 2024 to USD 47.1 billion by 2030, at a CAGR of 44.8%. Traditional methods, quarterly reports, and manual research are being replaced by AI agents that continuously track competitors, delivering insights in real-time.
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.
Compare Best AI Agents in Customer Service in 2026
AI agents powered by large language models (LLMs) can respond to customer queries in natural language, interpret context, and generate human-like responses. These agents can process and synthesize large volumes of information from sources such as knowledge bases. We compiled a list of the best use cases for the top 4 customer service AI agents.
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.
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.
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.