Jason Liu, the creator of the 13k‑star Instructor library and new Codex team member, reveals how to turn Codex into a persistent, autonomous agent using long‑living threads, Heartbeats + @computer, Goal mode, local memory storage, and validation loops for continuous work.
The article recommends a progression of open‑source projects—starting with libevent, then muduo, Redis, and finally nginx—to help developers master C/C++ network programming through hands‑on exploration, performance tuning, and debugging techniques.
Using Codex to take over a real Spring Boot codebase—modifying packages, fixing beans, refactoring modules, adding idempotency, and even auto‑repairing compile errors—revealed that AI can now understand project context and act as an engineering agent, fundamentally shifting Java development practices.
The article outlines a six‑step workflow for leveraging Codex in research tasks—starting with reading the codebase, defining clear long‑term rules, planning complex changes, verifying assumptions, resetting the session after each task, and demanding explicit validation output—to make AI‑assisted development reliable and reproducible.
After struggling with AI‑generated code that failed on global edge cases, the author evaluates the FeiSuan JavaAI IDEA plugin, walking through its five‑agent workflow—from requirement planning to source generation—and demonstrates how it successfully creates a production‑ready mini‑redis Spring Boot starter with thorough testing.
This tutorial walks through building a controllable video‑generation pipeline that lets an AI Agent turn an article into a scripted, outlined, and visually animated web‑based presentation, covering skill design, execution phases, parallel development, self‑checks, and audio synthesis.
This article dissects a pure on‑device Android automation engine, detailing its four‑layer architecture, gesture injection techniques, visual perception handling, robustness mechanisms, current technical and regulatory roadblocks, and how AI‑driven vision and LLM agents could shape its next evolution.
This guide warns mobile developers that while VibeCoding can quickly generate SwiftUI, Compose, or Flutter code, they must still address security boundaries, cost implications, compliance rules, performance constraints, data‑schema design, testing, and incident‑response practices before releasing an app to real users.
DeepSeek released an official repository with guides for integrating its V4 models into 19 mainstream AI agents and coding assistants, covering desktop clients, IDE plugins, terminal agents, chat platforms, and research tools, with step‑by‑step installation, configuration, and first‑run instructions.
The article explains how everyday workplace interactions can be modeled with principal‑agent theory and Bayesian updating, showing how to infer a manager’s hidden intentions from explicit and implicit signals, illustrated by a product‑manager case study and practical guidelines for building priors, handling noise, and avoiding bias.
The fourth national database test shows a surge in II‑level certifications, a clear shift toward scenario‑specific and enterprise‑self‑use products, and highlights the need for continuous iteration and careful vendor selection as the Chinese database market moves into a deep‑technology competitive era.
The article explains why Codex needs explicit project rules, distinguishes between collaboration rules in AGENTS.md and command‑permission rules in .codex/rules, and provides concrete examples, templates, and a checklist for writing effective, specific rules that keep Codex aligned with team conventions.
This article explains a reproducible Linux network performance assessment covering latency, throughput, bandwidth, and packet loss, introduces built‑in and benchmark tools such as ping, ss, nstat, ethtool, iperf3, netperf and wrk, and provides a step‑by‑step workflow to generate a complete evaluation report.
SkillOpt treats an agent’s Skill document as a trainable external state, applying classic deep‑learning tools such as epochs, batch size, learning rate and validation gating, and in experiments across 52 benchmark units it lifts GPT‑5.5 performance by an average of 23.5 points while enabling cross‑model and cross‑environment transfer with no additional inference cost.
The article reveals that xAI’s upcoming Grok-5 (Grok V9-Medium) will feature a 1.5-trillion-parameter model trained with extensive Cursor programming data, while MiniMax-M3 introduces a new sparse-attention architecture that boosts pre-fill speed by 9.7× and decode speed by 15.6×, highlighting a strategic partnership between SpaceX, Cursor, and xAI.
The article outlines eight practical patterns—Context Cascade, Repo Map, Noise Filter, Symbol Lookup, Just-in-Time Skill, Scoped Skill, Scout Subagent, and Search-as-a-Tool—that enable Claude Code to efficiently navigate and operate within large, multi-team monorepos by providing structured entry points, filtering noise, leveraging language servers, and integrating existing knowledge systems.
Thorsten Ball outlines twelve decisive observations about the AI era, arguing that abundant code, the rise of autonomous agents, shifting bottlenecks, and new value drivers will fundamentally rewrite software development, organization, and engineer roles.
Reflow recalculates layout when geometric properties change, while repaint only redraws visual styles; the article explains their triggers, compares performance impact, and provides practical techniques—such as using DocumentFragment, batching reads before writes, and leveraging transform/opacity—to minimize costly reflows and achieve optimal front‑end rendering.
The article analyses Claude Code's Subagents, Agent View, and Agent Teams, explaining when to use each, how to partition engineering work, enforce permission and budget limits, and gather verifiable evidence so that multiple AI agents can collaborate safely and efficiently in real projects.
The article analyses Claude Code's new parallel‑working features—Subagents, Agent View, and Agent Teams—explaining when each should be used, how to break engineering work into clear boundaries, manage permissions and budgets, gather verifiable evidence, and avoid hidden coordination costs in real projects.
