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
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.
Agentic CLI Tools Compared: Claude Code vs Cline vs Aider
Explore top free and open-source agentic CLI tools that offer LLM integration, prompt chaining, and code editing capabilities, all within a terminal-based workflow. [aim_list] AI coding tools can generally be grouped into three categories: What are CLI-based coding agents? CLI-based coding agents are conversational, prompt-driven AI tools that operate entirely in the terminal.
Top 40+ AI Developer Tools for Software Development
We have been experimenting with AI development tools in our code generation and code editing benchmarks for months. We have seen that AI agents like Claude Code are highly capable of software development, achieving ~%90 success rate.
Agents.md: The README for Your AI Coding Agents
This guide introduces AGENTS.md, an open specification changing how AI agents interact with software projects. Unlike traditional README.md files, which are written for humans and often leave gaps, AGENTS.md provides clear, machine-readable instructions that both people and AI agents can follow with precision.
5 Steps from Chatbots to Secure Enterprise AI Agents
Though LLMs are great at text generation, their Enterprise AI agents are being built by leading SaaS vendors to address these issues. These bots need to be able to:[aim_list] [/aim_list] While these are table stakes, how they are implemented is important.
The Industrial AI Agent 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 Agent Deployment: Steps and Challenges
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.
Top 10+ AI Agents in Healthcare: Use Cases & Examples
We previously explained healthcare AI use cases. In this article, I listed the best AI agent examples for healthcare that automate workflows in clinical operations: Examples of AI agents in healthcare General-purpose healthcare agents Automates multiple business tasks (e.g., scheduling, medical coding, office operations), but not focused on diagnostics or deep clinical applications.
12 Reasons AI Agents Still Aren't Ready
For all the bold promises from tech CEOs about AI agents “joining the workforce” and driving “multi-trillion-dollar opportunities,” the reality is far less inspiring. What we currently have are not autonomous agents, but glorified chatbots dressed in fancy packaging; mostly mimicking scripts. Give them the same task twice, and you’ll often get wildly different results.
Top AI Financial Research Platforms for Investors
Investors face a crowded landscape of financial research tools, but many still struggle with fragmented data, time-consuming manual analysis, and limited predictive insights. AI financial research platforms are filling these gaps by combining automation, natural language processing, and advanced analytics to deliver faster, deeper, and more actionable intelligence.