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This guide explains how to use Git's built‑in worktree feature combined with a bare repository to check out multiple branches simultaneously, keeping a tidy project layout, reducing context‑switch overhead, and improving IDE friendliness for hot‑fixes, features, and maintenance work.
This article provides a comprehensive, engineering‑focused breakdown of large language models, covering their Transformer roots, tokenization, context windows, prompt engineering, tool integration via MCP, and autonomous agents, while offering practical examples and actionable insights for developers.
A recent GitHub issue reveals that attackers used AI‑assisted social engineering—posing as a company founder, creating a fake Slack workspace, arranging Microsoft Teams meetings, and tricking the maintainer into installing a malicious npm package—to inject a trojan into the widely used Axios library, bypassing 2FA and publishing malicious code.
StepSecurity uncovered a sophisticated supply‑chain attack on the popular Axios HTTP client where compromised maintainer credentials were used to publish malicious versions that injected a hidden postinstall RAT, evaded detection, and executed platform‑specific payloads before self‑destructing, prompting detailed forensic and remediation guidance.
This guide explains how to install and use the OpenAI Codex plugin for Claude Code, covering setup commands, core review functions, optional review gates, and practical scenarios where the plugin provides a seamless AI‑powered second opinion within your coding workflow.
This article explains why the traditional 100vh unit fails on mobile browsers, introduces the three new CSS viewport unit families (large, small, and dynamic), and provides practical code examples and guidance for choosing the right unit in responsive web designs.
This article explains a structured workflow that uses git worktree to run multiple independent worktrees for parallel agent execution, detailing the three‑step process, bottlenecks, and a bash orchestration script for managing front‑end and API worktrees in a multi‑repo environment.
Harness Engineering is the emerging discipline that unifies Prompt Engineering, Context Engineering, and system-level controls to create robust, maintainable AI agent pipelines, illustrated with real-world performance gains, architectural patterns, and practical guidelines for building scalable AI‑driven workflows.
MiniMax M2.7 is a self‑evolving LLM that combines a persistent Agent Harness, multi‑level memory, and autonomous improvement cycles to reach SOTA benchmark scores, cost efficiency, and real‑world software‑engineering capabilities, illustrating the emerging skill‑economy of agent ecosystems.
This article evaluates Claude's ability to translate isolated Linux kernel modules from C to Rust, presenting a detailed analysis of translation granularity, token costs, experimental results on drivers, networking, and file‑system modules, and discussing the technical and economic challenges of a full kernel rewrite.
