#worktree runtime
32 related articles
·2 min
CrewCode: An Open-Source Desktop Tool for Parallel Scheduling of Multiple AI Coding Agents
CrewCode is a free open-source Electron desktop app that runs multiple AI coding agents in parallel via Git Worktree isolation, supporting Claude Code, Codex, and more with crew orchestration and context handoff.
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·3 min
Git Worktree Is Not an Isolation Boundary for AI Coding Agents: Real Sandboxing Solutions Explained
Analysis of why Git worktree fails as a security boundary for AI coding agents like Claude Code and Cursor, and why containers and VMs are the real solution.
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·7 min
Harness Engineering: Why a Powerful Model Isn't Enough — Here's What Really Matters
A data-deletion disaster reveals the biggest AI Agent risk: the problem isn't the model, it's Harness design. Learn context management, process standards, and permission isolation.
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·4 min
Codex Major Upgrade: GPT-5.6 Powers Full-Stack Development from Idea to Deployment
OpenAI Codex gets a major upgrade with GPT-5.6: extended reasoning, multi-agent parallelism, browser control, one-click Sites deployment, task orchestration, and mobile dev support.
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·4 min
Loop Engineering in Practice: Designing and Deploying a Multi-Agent Collaborative Development System
A deep dive into Loop Engineering: how multi-agent collaborative dev systems achieve automated coding loops through workflow scheduling, step isolation, and validation.
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·3 min
Open-Source Dynamic Workflows: How awman Enables Multi-Model Collaborative AI Programming
awman's --dynamic flag enables cross-framework dynamic workflows with multi-model collaboration. Explore its leader agent architecture, shared context design, and auto fault-tolerance mechanisms.
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·4 min
Agent Loop in Practice: A Guide to Building Self-Improving Automation with Guardrails
A deep dive into building verifiable, self-evolving Agent automation loops with Claude Code and Codex — covering Loop Contracts, four trigger types, three-phase execution architecture, and Evolve Loops.
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·4 min
Why Do AI Agents Crash the Moment They Go Live? A Practical Guide to Harness Engineering for Runtime
A deep dive into the Claude Code source code, systematically analyzing the five-layer Harness Engineering architecture: environment, tool, control, memory, and evaluation. Build a stable runtime system for production AI Agents.
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·6 min
Cross-Model Review Between Claude and Codex: A Practical Workflow to Systematically Eliminate AI Code Bugs
Vibe Coding saves time but leaves piles of bugs? This article details the cross-model review workflow: Claude generates, Codex auto-reviews, with Stop Hook and Skill mechanisms building an AI code review system that intercepts problems automatically.
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·5 min
A Deep Dive into Cloud Coding Agents: How Users in China Can Choose Wisely
What exactly is the Cloud Coding Agent Silicon Valley is hyping? This article breaks down the core concept across three axes—where it runs, who watches, where tasks start—and gives users in China practical advice on local alternatives.
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·2 min
no-mistakes: An AI Code Quality Gate Before git push
no-mistakes is an open-source tool that runs AI code review, lint checks, and unit tests before git push — with auto-fix support, so every PR arrives clean.
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·7 min
Fable AI Coding in Practice: Optimizing Reasoning Levels and Multi-Model Collaboration to Cut Costs
How developer Theo used Anthropic's Fable model to rebuild his AI coding workflow — controlling reasoning levels, multi-model routing with Codex, and sub-agent orchestration to cut costs from thousands to $150.
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·7 min
Fable AI Coding in Practice: Optimizing Reasoning Levels and Multi-Model Collaboration to Save Money
Hands-on guide: Use Anthropic's Fable model to optimize AI coding workflows — control reasoning levels, leverage Claude-Codex multi-model collaboration, and cut costs from thousands to $150.
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·6 min
10 Billion Tokens in Practice: An In-Depth Review of Codex's Long-Horizon Engineering Capabilities
Creator Ajiang burned 10B Tokens on Codex to migrate cc-haha from Tauri 2 to Electron. A deep dive into Codex's long-horizon engineering, Computer Use, costs, and practical advice for developers.
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·3 min
AI Programming Power User Workflow: A Practical Guide to Automated Loops and Multi-Model Collaboration
A deep dive into expert AI programming workflows covering Cursor rules, skills systems, automated loops, cloud agent parallel development, and multi-model collaboration strategies.
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·4 min
Mastering Claude Code: Five Hardcore Strategies to Transform It from Intern to Architect
A systematic guide to advanced Claude Code usage covering context management, plan mode, parallel development, and security — transforming your AI coding assistant into a virtual architect.
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·2 min
Getting Started with Loop Engineering: Making AI Agents Run Workflows Autonomously
A deep dive into Loop Engineering: core concepts and hands-on setup including Codebase Harness, shared file systems, triggers, and Loop Contracts to make AI agents run autonomously.
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·3 min
OpenAI Codex Deep Dive: Core Capabilities and Engineering Design Philosophy
Deep dive into OpenAI Codex's core capabilities and engineering design philosophy, covering multi-task parallelism, code review, Agent Loop, Spec-Driven Development (SDD), and context engineering.
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·4 min
A Complete Guide to Multi-Agent Teams in AI Coding: From Solo Work to Team Collaboration
Deep dive into multi-agent solutions from Cursor, Claude Code, and Tencent CodeBuddy — covering parallel exploration, cross-layer collaboration, context isolation, practical tips, and selection guide.
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·4 min
PeakCode Open-Source AI Coding Tool: An All-in-One Solution Combining Claude Code and Codex
PeakCode is an open-source AI coding tool combining Claude Code's engineering power with Codex's UX, featuring Web/desktop modes, plugins, Git integration, and automated Agent capabilities.
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