Backend tech guide and AI engineering practice covering fundamentals, databases, distributed systems, high concurrency, system design, plus AI agents and large-model engineering.
The article explains why, with stronger models like GPT‑5.6, many traditional coding Skills become redundant, outlines the progressive‑disclosure mechanism, highlights token and security costs, and provides concrete criteria and examples for deciding which Skills to retain or discard.
OpenHands is a self‑hosted coding‑agent console that lets multiple agents run across local machines, Docker, VMs or the cloud, integrates Claude Code, Codex and Gemini via ACP, supports automated workflows, and includes detailed installation and security guidance for safe long‑term use.
After Kimi K3’s official launch, the author evaluates its 2.8 T‑parameter, 1 M‑context, multimodal coding agent across three real‑world scenarios—a full‑stack hotspot‑tracking MVP, a Java project refactor fixing stock‑search encoding, and a 3A‑style game demo—detailing setup, performance, and limitations.
Step AOS introduces a three‑layer, agent‑native mobile OS that separates intent capture, memory/decision logic, and hardware resources, decomposes system functions into atomic abilities, and uses edge‑cloud routing with safety controls to let large language models reliably execute complex cross‑app tasks.
After Claude Code accounts were banned and security concerns rose, the author details how to migrate configurations, compare features, set up models, and run real tasks with Qoder CLI, while evaluating its security certifications, multi‑model support, and practical advantages for AI programming.
The article examines TalentsAI, a platform that lets programmers earn by creating expert data, evaluation tasks, and benchmarks for large language models, outlining required skills, application steps, income considerations, strict anti‑AI‑generation rules, and why this side‑gig suits developers.
The article introduces the open‑source drawio‑chart Skill, explains why draw.io remains valuable for editable technical diagrams, compares it with other AI drawing projects, details the workflow, constraints, installation steps, and shows how to generate and refine diagrams for documentation.
The article explains the technical differences between CLAUDE.md and Skill files, when to use each, their loading strategies, file structures, front‑matter fields, dynamic context, security considerations, and how Skills interact with Subagents, Plugins and Agent Teams in Claude Code.
AIGuide is a free, open‑source handbook that walks Java, Go, frontend, testing, and architecture professionals through the entire AI application development lifecycle—from LLM fundamentals and RAG to agents, system design, and practical AI‑assisted coding—providing real‑world scenarios, key parameters, pitfalls, and interview preparation.
Loop Engineering repackages existing concepts like Agent Loop, ReAct, and Workflow Graph, focusing on how Claude Code’s /loop and /goal commands enable autonomous, token‑aware agent cycles with defined triggers, goals, context, verification, and stop conditions, while highlighting practical design patterns, risks, and best‑practice examples.
