72 related articles

Kiro Crew is an open-source agentic development workspace that solves AI coding assistants' cold start problem through persistent memory, multi-agent collaboration, and purpose-built Apps.

Deep dive into OpenChamber's agentic development environment design and core capabilities. Learn why AI agents need dedicated isolated sandboxes and observable execution spaces.

AgentConnect is an open-source AI agent collaboration platform supporting cross-platform integration with Slack, GitHub, and Discord, featuring granular role permissions and multi-agent coordination.

Exploring the Agentic IDE concept: a self-building, self-iterating intelligent development environment. A deep analysis of how AI programming tools evolve from passive assistance to autonomous evolution.

A veteran user spent a year building Stimma, an open-source desktop app on top of ComfyUI that solves media asset management, multi-GPU load balancing, and agent-driven creation with local-first design.

Termexo is a local AI coding workbench for Windows that integrates Claude Code and Codex agents, offering multi-terminal grid layouts, session recovery, approval notifications, and model switching—no account required.

A senior developer admits 95% of work is done by Claude Code, with 10x productivity gains. From coding to architecture, AI is eroding programmers' core skill moats. Deep analysis of AI coding's impact on tech employment.

Google's official hands-on: how to go from idea to production fast with AI Studio and build AI Agents using the now-GA Interactions API. The core idea—Agents are just combinations of files.

Official Google hands-on: go from idea to production fast with AI Studio, and build AI Agents with the now-GA Interactions API. The core idea: an Agent is just a composition of files—Markdown plus a few scripts, no complex Python loops needed.

Anthropic's Claude Sonnet 5 claims near-OPUS 4.8 performance at lower cost. Real-world tests reveal hidden tokenizer costs, weak creative output, and only 13th place on Cursor rankings.

Anthropic engineers reveal Claude Code's 18-month evolution: system prompt cut by 80%, 65% of PRs shipped automatically by AI, Claude Tag collaboration, and the safety logic behind auto mode.

An in-depth guide to Anthropic's Claude Code agentic coding tool, covering installation, pricing plans, model selection, token management, CLAUDE.md global memory, MCP integration, Subagents, and more.

A creator tests GPT-5.6 Codex on two real projects: an Android MAUI app and a tower defense game prototype. Zero code written for the app; the game demo surfaces multiple bugs. Honest look at AI coding's real limits.

Can a single sentence generate a complete app or game with zero coding knowledge? We tested an AI coding tool building Snake end-to-end, analyzing its 9-step pipeline, open source code, and sharing features.

Complete guide to installing Claude Code in China: platform steps for Windows/macOS, VPN requirements, Git dependency, error fixes, and how it differs from Cursor and VS Code.

Explore why AI agent tools (Codex, Claude Code, Gemini) lack workspace-level config for multi-repo microservice dev, and discover practical solutions like symlinks, custom paths, and cascading config.

A deep dive into Claude Code, the definitive course from DeepLearning.AI and Anthropic: from agentic principles and context optimization to three hands-on cases—RAG chatbot, Figma-to-frontend, and data analysis. Master AI-assisted coding methodology.

OpenAI releases the GPT-5.6 model family, launching enterprise-focused ChatGPT Work, one-click ChatGPT Sites, and a major desktop client upgrade, with coding now ahead of rivals. Meta, Google, and Kimi follow intensively.

Deep dive into GPT-5.6 (Sol/Terra/Luna): one-shot complex coding, agentic workflows, benchmark wins over Claude — but hallucination and vision still lag. Must-read for developers.

OpenAI releases the GPT-5.6 series with Soul, Terra, and Luna models. Ranked first on Terminal Bench coding evaluation, Ultra mode natively bakes agent orchestration into the model, while revealing Agentic Trace data as the core competitiveness of next-gen AI training.