Code Mala Tang
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Code Mala Tang

Read source code together, write articles together, and enjoy spicy hot pot together.

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Code Mala Tang
Code Mala Tang
Mar 27, 2026 · Artificial Intelligence

What Is Harness Engineering and Why It Matters for AI Development

Harness Engineering is the emerging discipline that integrates Prompt Engineering, Context Engineering, and system-level controls to create reliable, maintainable AI‑generated code, and the article analyzes its origins, key components, real‑world performance data, and practical guidelines for building effective AI harnesses.

AI developmentHarness Engineeringprompt engineering
0 likes · 12 min read
What Is Harness Engineering and Why It Matters for AI Development
Code Mala Tang
Code Mala Tang
Mar 27, 2026 · Industry Insights

Why the Real GPU Shortage Is About Low Utilization, Not Supply

The article reveals that the perceived AI‑GPU shortage stems from misleading utilization metrics and wasted capacity, not actual supply constraints, and argues that better measurement and orchestration—not buying more hardware—will determine competitive advantage in the emerging AI infrastructure market.

GPU utilizationIndustry Analysisorchestration
0 likes · 9 min read
Why the Real GPU Shortage Is About Low Utilization, Not Supply
Code Mala Tang
Code Mala Tang
Mar 25, 2026 · Fundamentals

How to Build a gzip Decompressor in Rust – Inside DEFLATE, Huffman & LZ77

The article walks through creating a compact 250‑line Rust gzip decompressor from scratch, explaining gzip’s header, DEFLATE block types, bit‑reading logic, Huffman coding, and LZ77 back‑references, and shows how to test it with real compressed data, highlighting key implementation challenges and trade‑offs.

CompressionDEFLATEGZIP
0 likes · 14 min read
How to Build a gzip Decompressor in Rust – Inside DEFLATE, Huffman & LZ77
Code Mala Tang
Code Mala Tang
Mar 19, 2026 · Backend Development

Why Bun Beats npm and Node: A Deep Dive into Its Speed and Built‑in Tools

This article examines how Bun’s ultra‑fast package manager, integrated JavaScript runtime, native test runner, and built‑in database/S3 client together deliver a faster, lighter, and more streamlined development experience compared to traditional Node.js and npm workflows.

BunJavaScript runtimebackend development
0 likes · 8 min read
Why Bun Beats npm and Node: A Deep Dive into Its Speed and Built‑in Tools
Code Mala Tang
Code Mala Tang
Mar 12, 2026 · Artificial Intelligence

Getting Started with OpenCode: Terminal‑First AI Coding Assistant

This guide walks you through installing, configuring, and using OpenCode—a terminal‑first, open‑source AI coding agent—covering CLI commands, provider authentication, headless server mode, SDK integration, sample workflows, and a minimal JSONC configuration for seamless AI‑driven development.

AI coding assistantAutomationCLI
0 likes · 11 min read
Getting Started with OpenCode: Terminal‑First AI Coding Assistant
Code Mala Tang
Code Mala Tang
Mar 10, 2026 · Artificial Intelligence

What Is the “Lobster” AI Agent Trend and How Does It Work?

The “lobster” style in the AI community describes long‑running AI agents that stay on a server, receive commands via chat tools, and automate tasks such as code fixing, CI repair, and information summarization, turning AI from a occasional assistant into a continuous digital worker.

AI AgentsAutomationChatOps
0 likes · 6 min read
What Is the “Lobster” AI Agent Trend and How Does It Work?
Code Mala Tang
Code Mala Tang
Mar 10, 2026 · Artificial Intelligence

Why Chinese Tech Giants Are Racing to ‘Raise Lobsters’ with OpenClaw AI

In early 2026, the Chinese AI community was swept by the OpenClaw "lobster" phenomenon, prompting major cloud providers and tech firms to launch services that turn idle compute into revenue, battle for next‑generation interaction points, and ride policy‑driven hype, while exposing significant cost, security, and regulatory risks.

AIChinaCloud Computing
0 likes · 7 min read
Why Chinese Tech Giants Are Racing to ‘Raise Lobsters’ with OpenClaw AI
Code Mala Tang
Code Mala Tang
Mar 9, 2026 · Artificial Intelligence

How Claude’s New Prompt Caching Cuts Token Costs by 90% for Long‑Running Agents

Claude’s API now automatically caches static parts of prompts—system instructions, tool definitions, and context—so repeated calls reuse these sections at only 10% of the standard token price, dramatically reducing costs for multi‑turn agents, but developers must manage prefixes and avoid cache‑breaking changes.

Claude APILLM Engineeringautomatic caching
0 likes · 15 min read
How Claude’s New Prompt Caching Cuts Token Costs by 90% for Long‑Running Agents