Tag

#ai agents

20 articles

How to Build Advanced Cybersecurity AI Agents with CAI Using Tools, Guardrails, Handoffs, and Multi-Agent Workflows

Learn how to build advanced cybersecurity AI agents using the CAI Framework in Google Colab, covering tools, guardrails, and multi-agent workflows.

Mar 2926

A Coding Guide to Exploring nanobot’s Full Agent Pipeline, from Wiring Up Tools and Memory to Skills, Subagents, and Cron Scheduling

Learn to build a lightweight AI agent framework by manually recreating nanobot's core subsystems including tool integration, memory management, skills, subagents, and cron scheduling.

Mar 2829

tech

An Implementation of IWE’s Context Bridge as an AI-Powered Knowledge Graph with Agentic RAG, OpenAI Function Calling, and Graph Traversal

Build an AI-powered knowledge graph system inspired by IWE, integrating markdown parsing, graph traversal, and OpenAI's function calling.

Mar 2710

Meet GitAgent: The Docker for AI Agents that is Finally Solving the Fragmentation between LangChain, AutoGen, and Claude Code

Learn how to build and deploy AI agents using GitAgent, a Docker-inspired solution that solves the fragmentation between LangChain, AutoGen, and Claude Code frameworks.

Mar 2229

Xiaomi launches three MiMo AI models to power agents, robots, and voice

Learn about Xiaomi's new MiMo AI models that combine multiple data types to create autonomous AI agents capable of controlling software, robots, and voice systems.

Mar 2233

Anthropic turns Claude Code into an always-on AI agent with new channels feature

Learn how to create always-on AI agents using Claude Code's new Channels feature that can monitor CI results and chat messages automatically.

Mar 2035

tech

Google Colab Now Has an Open-Source MCP (Model Context Protocol) Server: Use Colab Runtimes with GPUs from Any Local AI Agent

Learn to connect local AI agents with Google Colab's GPU resources using the Model Context Protocol (MCP) server for remote code execution and development workflows.

Mar 1926

OpenClaw-RL trains AI agents "simply by talking," converting every reply into a training signal

This explainer explores OpenClaw-RL, a new reinforcement learning framework that enables AI agents to learn continuously from every interaction, turning conversational feedback and GUI actions into training signals.

Mar 1535

RL agents go from face-planting to parkour when researchers keep adding network layers

Learn how adding more layers to AI neural networks helped reinforcement learning agents master complex behaviors like parkour, showing the power of deeper AI systems.

Mar 1526

Nyne, founded by a father-son duo, gives AI agents the human context they’re missing

Learn to build a context-aware AI agent that understands human interaction patterns, similar to the approach taken by Nyne's data infrastructure startup.

Mar 1345

Model Context Protocol (MCP) vs. AI Agent Skills: A Deep Dive into Structured Tools and Behavioral Guidance for LLMs

This explainer compares Model Context Protocol (MCP) and AI Agent Skills, two approaches for enabling LLMs to interact with external tools. It covers their architectural differences, operational mechanisms, and practical implications for AI system development.

Mar 1223

ByteDance Releases DeerFlow 2.0: An Open-Source SuperAgent Harness that Orchestrates Sub-Agents, Memory, and Sandboxes to do Complex Tasks

Learn to build a SuperAgent framework inspired by ByteDance's DeerFlow 2.0 that orchestrates planning, execution, and memory for complex task automation.

Mar 957