DeWu Technology
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DeWu Technology

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DeWu Technology
DeWu Technology
Apr 22, 2026 · Artificial Intelligence

How AI Turns Real‑World Operations into Automated E2E Test Cases

This article details an AI‑driven end‑to‑end testing solution that automatically generates test cases from real operation logs, compares traditional DOM‑based testing with AI‑enhanced approaches, selects Midscene + Qwen2.5‑VL‑72B as the execution engine, and builds a four‑stage pipeline that delivers code‑coverage metrics, platform dashboards, and a quality‑feedback loop for rapid product iteration.

AI testingCI/CDE2E automation
0 likes · 16 min read
How AI Turns Real‑World Operations into Automated E2E Test Cases
DeWu Technology
DeWu Technology
Apr 15, 2026 · Industry Insights

How Generative AI is Transforming Recommendation: A Deep Dive into DeWu’s Recall System

This article analyzes DeWu's generative recall system, detailing its background, technical design of the Generative and Rerank models, inference workflow, experimental gains in core consumption and diversity metrics, and future engineering directions such as framework migration, LLM integration, and multimodal generation.

Generative AIScaling Lawdeep learning
0 likes · 12 min read
How Generative AI is Transforming Recommendation: A Deep Dive into DeWu’s Recall System
DeWu Technology
DeWu Technology
Apr 13, 2026 · Artificial Intelligence

How to Turn AI into a Structured Component‑Reuse Assistant: A Three‑Layer Skill Architecture

This article explains why a dedicated AI skill is needed to enforce component‑reuse discipline in a monorepo, outlines a three‑layer design (AGENTS.md, Hook, Skill), and details the implementation of a unified entry point, weighted matching, index pipelines, and feedback loops that together make AI decisions reliable and repeatable.

AIMonorepoSkill Architecture
0 likes · 13 min read
How to Turn AI into a Structured Component‑Reuse Assistant: A Three‑Layer Skill Architecture
DeWu Technology
DeWu Technology
Apr 1, 2026 · Backend Development

How AI‑Powered /log‑diagnosis Skill Automates Bug Tracing in Backend Logs

This article explains how the /log‑diagnosis Skill, built on Claude Code and the Model Context Protocol (MCP) log platform, creates a closed‑loop workflow that automatically fetches logs, extracts key information, maps it to source code, diagnoses root causes, and generates remediation suggestions, dramatically speeding up backend debugging.

AI debuggingClaude CodeMCP
0 likes · 17 min read
How AI‑Powered /log‑diagnosis Skill Automates Bug Tracing in Backend Logs
DeWu Technology
DeWu Technology
Mar 25, 2026 · Big Data

How Code LLM Transforms E‑commerce Data Warehouses: From Data Rights to AI‑Driven Automation

This article analyzes how large‑language models for code, exemplified by Claude Code, are integrated into an e‑commerce data‑warehouse ecosystem, defining data‑rights boundaries, introducing agentic workflows, decoupling cognitive and execution runtimes, and establishing standardized I/O contracts to achieve safe, scalable AI‑assisted development and governance.

Data WarehouseStandardized I/Obig data
0 likes · 24 min read
How Code LLM Transforms E‑commerce Data Warehouses: From Data Rights to AI‑Driven Automation
DeWu Technology
DeWu Technology
Mar 23, 2026 · Artificial Intelligence

Why Context Management, Not Model Size, Is the Real Bottleneck for AI Coding

The article argues that the true limitation of AI‑assisted programming lies in managing context and intent rather than model capacity, and it details how Claude Code’s agentic loop and the OpenSpec specification framework together enable scalable, spec‑driven development and sustainable team knowledge accumulation.

AI codingClaude CodeOpenSpec
0 likes · 15 min read
Why Context Management, Not Model Size, Is the Real Bottleneck for AI Coding
DeWu Technology
DeWu Technology
Mar 16, 2026 · Frontend Development

Boosting Frontend Code Review with AI: From Manual CR to Automated Cursor Agent

This article outlines the challenges of manual frontend code review, compares AI-powered CR solutions, details a pipeline integration using Cursor Agent CLI, and provides practical guidelines, model selection tips, and built‑in prompt engineering to automate and improve code quality checks.

AI code reviewCI integrationCursor Agent
0 likes · 12 min read
Boosting Frontend Code Review with AI: From Manual CR to Automated Cursor Agent
DeWu Technology
DeWu Technology
Mar 11, 2026 · Artificial Intelligence

How AI‑Driven Spec Coding Accelerated a Front‑End Project by 36% in 10 Days

In ten days, a team built a 25,000‑line front‑end application using Claude‑based Spec Coding, achieving a 36% productivity boost through a three‑layer specification workflow, detailed data analysis, code‑style enforcement, MCP tooling, and a deep exploration of AI’s capabilities and limits.

AI codingAI productivityfrontend development
0 likes · 22 min read
How AI‑Driven Spec Coding Accelerated a Front‑End Project by 36% in 10 Days
DeWu Technology
DeWu Technology
Mar 9, 2026 · Backend Development

How We Engineered a Scalable Regression Testing Pipeline for a High‑Frequency C++ Search Engine

This article details the motivation, design, and implementation of a systematic regression testing framework for a high‑frequency C++ search engine, covering traffic recording, DIFF testing, one‑click load testing, pipeline integration, and future automation plans to match rapid iteration cycles.

C++ search engineCI/CDDIFF testing
0 likes · 11 min read
How We Engineered a Scalable Regression Testing Pipeline for a High‑Frequency C++ Search Engine
DeWu Technology
DeWu Technology
Mar 4, 2026 · Backend Development

How the Multiplicative Tree Framework Enables Instant Formula Deployment and Stable High‑Performance Ranking

The article details the design and evolution of the Multiplicative Tree framework—from version 1.0 to 3.0—showing how a DSL‑based, compile‑time‑checked configuration system delivers instant formula deployment, robust stability safeguards, and significant performance gains for multi‑objective ranking models.

CDSLJava
0 likes · 18 min read
How the Multiplicative Tree Framework Enables Instant Formula Deployment and Stable High‑Performance Ranking