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Learn LangGraph multi-agent development covering Supervisor and Collaboration architectures, with three hands-on projects: code assistant, prompt assistant, and WebRTC digital human.

Coding alone isn't enough anymore. Learn the 5 key steps to commanding AI Agents—define outcomes, split tasks, provide context, iterate small, and keep humans in the loop.

A deep dive into the /goal command in Claude Code and Codex — covering positioning, real-world cases, and a three-element Prompt framework (Goal, Termination Condition, Constraint Rules) for stable long-running AI Agent tasks.

A comprehensive guide to software testing fundamentals covering definitions, purposes, classification by phase, technique, and method, plus core concepts like smoke testing and regression testing.

Deep dive into AI coding agent architecture: from interview-level cognition to building a Codex-like CLI agent tool, covering agents.md, Skills systems, context management, and more.

A systematic guide to Claude Code debugging and observability, covering Token monitoring, context management, Compact compression, security, and Skills ecosystem.

In-depth guide to Kimi Code's advanced features: video understanding, Swarm parallel mode, ACP protocol IDE integration, Goal multi-round iteration, and Skills configuration with Claude Opus comparison data.

Explore three AI programming modes — Vibe Coding, Plan Mode, and AI Engineering — with practical comparisons of Claude Code, Codex, and domestic LLMs, plus SDD-driven enterprise development workflows.

A deep dive into the Vibe Coding four-module framework: paradigm cognition, open-source customization, SDD, and project rules for real engineering delivery.

When AI code generation outpaces human review, Code Review becomes the biggest bottleneck. Learn guardrail systems, architecture constraint tests, and TDD-driven Agent development strategies.

A deep dive into Codex and Claude Code for real-world AI programming—from Vibe Coding prototypes to Plan mode and SuperPAL engineering, with LLM selection strategies and enterprise workflows.

5 daily Claude Code tips: Grill Me for requirements, Brainstorming for architecture, Writing Plan for execution, TDD for testing, and Debugging for precise fixes — a complete AI coding workflow.

DeepSWE long-horizon benchmark shows GPT 5.5 leads Opus 4.7 by 15+ points with 70% pass rate at one-third the cost. Deep dive into contamination-free testing and AI coding implications.

How the Superpowers methodology constrains AI coding assistants through requirement clarification, task decomposition, TDD, and verification loops — with setup tips for Trae.

A detailed walkthrough of building real features with Claude Code: Grill Me requirement interrogation, auto-generated PRDs, AFK agent coding, and QA iteration loops with DDD and TDD strategies.

In-depth comparison of Claude Sonnet 4.6, GPT-5.1 Codex, and DeepSeek-R1 across API pricing, specs, and SWE-Bench Verified scores to help developers pick the best AI coding assistant.

A complete guide to Codex Superpowers: 14 composable skills covering brainstorming, planning, TDD, and code review, with a real-world WeChat Mini Program case study.

Xiaomi's MiMo Code is an open-source terminal programming Agent with cross-session memory and multi-Agent collaboration. Explore its memory system, self-evolution mechanism, and how it differs from Claude Code.

Deep dive into Harness AI Engineering Programming methodology, covering SDD, Skill development patterns, and core practices for enterprise-level AI-assisted development.

Explore Boris Cherny's Claude Code loop patterns with community insights on /loop commands, test-driven loops, multi-agent collaboration, and best practices to avoid loop divergence.