Author of the rpcx microservice framework, original book author, and chair of Baidu's Go CMC committee.
The article explores the growing gap between AI's rapid code generation and developers' slow comprehension, detailing the risks of unread AI code and introducing the /understand tool that creates interactive, line-anchored explanations to help engineers truly own AI-generated changes.
This practical Go database/sql tutorial covers 39 lessons spanning core concepts like connection pools, transactions, and isolation levels, compares ORMs (GORM, Bun, XORM) and lightweight tools (sqlx, sqlc, Squirrel), and addresses logging, migration, testing, and production practices using modernc.org/sqlite for runnable examples.
The article explains how PRD, design documents, and SPEC each answer distinct questions—what, why, and how—while outlining their constraints, typical structures, real‑world examples, when to use or skip them, and how they fit into a seamless development pipeline.
The author prompts six recent large language models to create a web‑based Gomoku game and compares the results across four dimensions—AI opponent, execution method, visual design, and engineering rigor—revealing that Opus 5 and gpt‑5.6‑sol deliver the most complete solutions while deepseek‑v4‑pro and glm‑5.2 excel at quick, single‑file prototypes, and MiniMax‑M3, despite its polished UI, fails at human‑vs‑AI play.
This article details the creation of pigo, a Go‑based replica of the Pi coding agent, covering its installation, core features, extension mechanisms, and the step‑by‑step AI‑driven workflow that enabled a solo developer to build a fully functional, single‑binary agent in just one week.
The article explains how Claude Code defines a loop as an agent repeatedly executing work until a termination condition is met, categorizes loops by trigger, termination, primitives, and task type, and provides concrete guidance for turn‑based, goal‑driven, timed, and proactive loops while showing how to control token usage and maintain code quality.
The article explains why traditional code‑review methods are inefficient for AI‑generated projects and presents a three‑skill workflow—/teach, /insight-diagram, and /architecture-diagram—demonstrated on the open‑source Zero coding agent to turn codebases into lasting, self‑contained learning courses and professional diagrams.
The article explains the origin of the term “code smell,” expands the classic catalog to over 50 modern smells, and demonstrates how the AI‑powered /smell skill automatically scans a sizable Go project (Gitlawb/zero), identifies issues such as God objects, long files, and hidden performance hotspots, then generates a prioritized refactoring roadmap.
Autoreview is an AI‑driven skill that automatically reviews code before a PR, addressing volume, blind‑spot, and boredom problems by repeatedly running until the code is clean, using a Scope Governor, multi‑engine panels, and strict isolation to enforce quality without manual bottlenecks.
The article explains how Baidu’s open‑source evr tool leverages VXLAN VTEP reflection to monitor Edge Virtual Routers from a single side, detailing packet construction, payload encoding, raw‑socket handling, BPF filtering, ECMP coverage, and practical configuration for reliable loss, latency, and bit‑flip detection.
