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Palmier Pro: An AI-Native macOS Video …
Palmier Pro is a native macOS video editor built for the AI era. Developed in Swift with nearly 12K GitHub stars, it rebuilds the editing workflow with AI-first principles for creators.

FableCut is an open-source browser video editor built on a zero-dependency architecture and programmable AI-agent-driven design. A deep dive for AI automation developers.

In-depth testing of SCAIL 2 video generation AI across character replacement, physics simulation, object permanence, and more—covering reference image prep, ComfyUI workflows, and real results.

Deep dive into Project Rai-chan's tech stack: Ollama+Gemma local LLM, Unity rendering, VOICEVOX speech synthesis, and more — exploring the technical path for local AI companions.

Should indie developers open source their projects? Using the game custom achievement tool Project Replay as a case study, this article analyzes the open source decision and offers a practical layered strategy.

OpenAI's Jason Liu shares how he uses ChatGPT Workbench and Codex to build an AI work OS: Chief of Staff automation, persistent threads, Skills/Plugins, browser control, and app-building methodology.

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.

Hands-on test of LibTV's AI Agent: from script and storyboarding to video compositing, one person completes an animated short in a day. Full breakdown of the Skill library, node workflow, and Story Board features.

A senior Java developer shares 7 years of IntelliJ IDEA configuration tips: JVM tuning, AI-assisted coding, Testcontainers testing, debugging tricks, and Spring toolchain setup.

Veteran AI practitioner Remy breaks down the leap from chat models to AI agents: how agents work, the three pillars of context, tools, and skills, MCP connections, and hands-on architecture to make you a 100x employee.

Understand Anything is a high-star open-source GitHub skill that runs static analysis on any codebase and generates interactive knowledge graphs. It supports Claude Code, Cursor, Copilot and other agents, letting engineers ask questions in natural language with path references.

Understand Anything is a high-star open-source GitHub skill that performs static analysis on any codebase to generate interactive knowledge graphs, supporting Claude Code, Cursor, Copilot and more.

Understand Anything is a high-star open-source GitHub skill that performs static analysis on any codebase to generate an interactive knowledge graph, supporting Claude Code, Cursor, Copilot and more.

A complete guide to Claude Code from beginner to enterprise practice: covering CLI installation, connecting domestic LLMs via CC Switch, basic commands, Git workflow integration, automated bug fixing, and engineering capabilities like MCP and SubAgents.

Learn how to use Vibe Coding to collaborate with AI in refactoring a Unity game, introducing ScriptableObject (SO) data architecture, with hands-on tips.

A deep dive into refactoring a Unity game with Vibe Coding and AI, introducing ScriptableObject (SO) architecture—covering visual map editors, Codex remote control, and collaboration pitfalls.

Vibe Coding lets non-coders build apps and websites fast with AI, but efficiency gains don't equal value gains. This article dissects the core trap and offers the right order: needs first, code later.

Build a personal website with Vibe Coding even from scratch! Practical tips for collaborating with AI via Codex and DeepSeek: have AI restate requirements, use screenshots to locate, change one thing at a time, and handle long Chinese text.

Build a personal website with Vibe Coding even with zero coding background! Practical tips for collaborating with AI via Codex and DeepSeek: have AI restate needs, use screenshots, change one thing at a time, and deploy your site with ease.

Vibe Coding lets non-coders build apps and sites fast with AI, but faster isn't better. This piece dissects its core trap—building isn't succeeding—and offers the right "demand first, code later" order plus three questions to gauge a project's value.