320 related articles

Medley is a free Claude Code plugin that decomposes complex dev tasks into live task graphs via /mission, orchestrating multiple AI agents with BYOK model support and built-in review cycles.

Agent-Manager is an open-source Tmux-based terminal tool for managing multiple AI coding agents like Claude Code, Codex, and OpenCode in a unified interface with quick switching and session persistence.

Agent-Manager is an open-source Tmux-based TUI for managing multiple AI coding agents like Claude Code, Codex, and OpenCode in a unified terminal interface with quick switching and session persistence.

HeyZoku is a Mac voice-first agentic dev environment that runs 10 coding agents simultaneously. Command Claude, Codex, and Cursor by name with on-device voice recognition and one-time pricing.

HeyZoku is a Mac voice-first agentic dev environment that runs 10 coding agents simultaneously. Command Claude, Codex, and Cursor by name with on-device voice recognition and one-time pricing.

Heard is a free, open-source macOS tool that turns AI coding agent outputs into intelligent voice summaries, helping developers monitor multiple agents hands-free.

Deep dive into how Velane provides dedicated cloud infrastructure for AI Agents through zero cold start sandboxes, version control, multi-environment management, and 800+ integrations.

agent-manager is a lightweight tmux-based TUI tool that helps developers manage multiple AI coding assistants like Claude Code, Codex, and OpenCode from a unified interface for status monitoring, interaction, and code review.

Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.

Explore how AI agents are redefining enterprise work—from applied AI partnerships and multi-agent collaboration to structural workflow redesign and organizational transformation.

Deep dive into running OpenAI GPT-5.6 inside Claude Code: comparing Codex vs Claude Code on subagent orchestration, workflow design, and system prompt quality, revealing how harness engineering determines model output.

How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.

Learn AI Agent core principles from scratch: understand how Agents differ from LLMs, their execution mechanisms, why rule design matters, and find the right learning path for your goals.

A beginner's guide to AI Agents: understand core principles, how Agents differ from LLMs, their execution mechanisms, and get tailored learning path recommendations.

A 12-person product team shares real-world experiences with Cursor, Codex, Claude Code, and CodeRabbit—exploring efficiency plateaus, scenario matching, and selection criteria for AI coding tools that actually stick.

Herder is an open-source terminal multiplexer for macOS and Windows that unifies management of Claude Code, Codex, OpenCode, and other AI coding agents—with persistence and remote reconnection.

This week's GitHub trending focuses on AI coding: Skills sets rules for Agents, Omniroute is a never-down AI gateway, Code Review Graph is a code knowledge graph, PI is an open-source Agent toolbox, and AI Engineering from Scratch teaches from zero.

This week's GitHub trending focuses on AI coding: Skills sets rules for Agents, Omniroute is a never-down AI gateway, Code Review Graph builds a code knowledge graph, PI is an open-source Agent toolkit, and AI Engineering from Scratch teaches from the ground up.

After three months of costly AI coding mistakes, a developer built WishGraph: separating discussion and execution into dual windows with parallel multi-agent collaboration to make complex projects manageable again.

As models get stronger, why does the experience feel worse? The root cause is missing context. This article breaks down four stages—project descriptions, progressive disclosure, intra-memory, and three guardrails—to build a sustainable AI project memory system.