24 related articles

Claude Code creator Boris argues top engineers should embrace AI-era automation leverage. By encoding domain knowledge into infrastructure, preview environments, and lint rules, engineers multiply output—the core path to Staff Engineer.

A step-by-step Pi Agent configuration tutorial covering installation, LLM connection, extension ecosystem, MCP setup, and Token-saving tips. Learn to build a truly controllable AI coding assistant.

A complete guide to Claude Code: Node.js setup, CLI install, switching to Chinese LLMs with CC Switch, core commands, and conversational Git workflows with automated bug fixing.

Hit the Vibe Coding ceiling? This guide covers the three-stage AI coding progression path, Claude Code vs. Codex, SuperPower SDD, and how to go from vibe coding to enterprise-grade AI engineering.

T-Head open-sources AI software stack T-Head SAIL at WAIC to lower the barrier for domestic chip development; Kimi K3 tops the WebDev leaderboard; Qwen 3.8 Max Preview cuts prices aggressively; Moonshot prepares a Hong Kong IPO; and Oracle switches its data center to a fuel cell microgrid.
pi-web: An Open-Source Web UI Built fo…
pi-web is an open-source TypeScript Web UI for the pi coding agent, offering visual execution flows, interactive intervention, and session management. 1500+ stars on GitHub.

In-depth analysis of Claude Code customization methodology: from access, knowledge injection to tooling. Master context window management, zero-overhead Hooks, and MCP & Skills plugin primitives to build a scalable AI software engineering workflow.

OpenAI merged Codex into ChatGPT, killing a developer-beloved AI coding brand. A deep dive into the gains and losses of this brand consolidation.

An in-depth comparison of OpenClaw and Hermes Agent, covering skill management, memory mechanisms, security, and gateway configuration to help you find the right AI agent solution.

A hands-on comparison of 6 open-source LLMs (DeepSeek, Qwen3, Zhipu GLM, Kimi K2, MiniMax M3, Tencent Hunyuan 3) for on-premise deployment—covering hardware cost, inference efficiency, and deployment difficulty.

Pure frontend roles are shrinking; AI Agent development is the high-salary divide. This guide breaks down the full skill tree for frontend engineers pivoting to AI: TypeScript, frameworks, AI productivity, and Agent core concepts (MCP, Tool Calling, Skill).

Taiganet.com is simulating the WS4000 industrial control system. This niche project preserves the engineering wisdom from before the PLC and SCADA era. A deep look at the challenges of ICS simulators, knowledge preservation, and reverse engineering in OT security research.

A deep dive into the four-layer engineering design of AI Agents: planning, memory, tool use, API cost optimization, MCP protocol integration, and Skill encapsulation.

Two methods for connecting external models to Codex: manually configure keys via relay services, or use the CC Tool to auto-bridge GPT, DeepSeek, and more. Covers auth/config files, CC Tool usage, and multi-model switching.

Herdr is an open-source Rust-written terminal tool positioning itself as an AI Agent multiplexer, unifying Claude Code, Cursor, and more in one CLI interface.

A deep dive into three levels of AI programming: Vibe Coding for rapid prototyping, Plan Mode for structured development, and AI-engineered programming for enterprise-grade projects with SDD and Claude Code SuperPower.

A deep dive into AI engineering with Codex and Claude Code: Vibe Coding limitations, Chinese LLM rankings, Skill-driven development, and enterprise project practices.

Deep dive into AI engineering methodology, comparing Vibe Coding vs enterprise development, covering Claude Code, Codex tool selection, SuperPower plugin practices, and the path from prototype to production.

Learn how to use Codex for free with Codex++ and free APIs. Complete setup guide covering text, image, and video generation with a real-world creative workflow example.

Google CEO Pichai admits Gemini lags behind Cursor and Claude Code in AI coding, blaming lack of product entry points. But the real issues are failed product experience, lost developer trust, and ecosystem advantages that haven't converted to competitiveness.