Mobile version of tech blog https://jianghushinian.cn/, covering Golang, Docker, Kubernetes and beyond.
This article explains how the Go dyno package lets you effortlessly read, modify, and serialize deeply‑nested JSON/YAML structures by providing Get, Set, Delete, Append and conversion utilities that work with map[string]interface{}, map[interface{}]interface{} and []interface{} without using reflection.
This article explains why converting a YAML document containing both numeric and string keys (e.g., 1 and "1") to JSON fails in Go using yaml.v3, demonstrates the resulting errors, and shows how to resolve the issue with dyno.ConvertMapI2MapS or alternative libraries, while also comparing behavior in Python and JavaScript.
In the AI‑driven era, Go programmers face a dilemma about mastering Python, and this article explains when Python is essential, how to prevent naïve code translation, and provides concrete examples of writing truly Pythonic code versus direct Go‑style conversions.
This article explains the role of the doc.go file in Go projects for centralized package documentation, demonstrates its structure with real examples, shows how to generate docs using godoc and go doc, and explores advanced uses like canonical import paths and code generation annotations.
Vibe Coding, introduced by Andrej Karpathy in 2025, lets developers describe software goals in natural language while large language models generate the code, reshaping the developer’s role, outlining the workflow, discussing tools, risks, and future prospects of this AI‑driven programming paradigm.
This comprehensive guide explores Go 1.23's iterator system, detailing the underlying principles of push and pull iterators, code transformations performed by the compiler, coroutine implementation, and practical examples that compare Go's approach with Python and JavaScript, helping developers master iterator usage and design.
This article explores the newly introduced iterator feature in Go 1.23, explaining what iterators are, why they were added, how to implement them manually, how to use the new iter package, and how the slices and maps packages provide iterator‑friendly utilities for Go developers.
The article explains how the rapidly emerging MCP protocol has become a de‑facto standard for AI agents, why developers should treat it like HTTP, and offers practical learning paths—including official docs, books, and hands‑on projects—to master MCP efficiently.
This article documents a step‑by‑step investigation of an AI Agent that fails to return results when it selects multiple MCP services, detailing log analysis, network packet capture, MCP protocol behavior, the discovery of tool‑name conflicts, and both temporary and permanent remediation strategies.
Model Context Protocol (MCP), an open-source standard from Anthropic, standardizes how large language models interact with external tools and data sources, introducing a client‑server architecture with hosts, clients, and servers, and promises to simplify AI application development compared to traditional function‑calling approaches.
