Official account of DaTaobao Technology
This article details a systematic set of optimizations—dual‑layer pre‑fetch, multi‑level caching, multi‑instance tab management, and white‑screen mitigation—that transformed an e‑commerce order list from sluggish and unstable to fast, smooth, and reliable for billions of users.
This article presents an AI‑driven accessibility solution that embeds code‑review and automatic fixing into the development workflow, tackles high‑frequency issues such as text reading, focus management and interaction recognition, achieves over 95% fix rates in both testing and production, and outlines future extensions to native and D2C scenarios.
This article aggregates ten technical case studies from Alibaba, covering AI‑assisted code cleaning, specification‑driven development, multi‑agent front‑end automation, AI coding fundamentals, index optimization, and workflow designs that together illustrate how AI can boost efficiency across backend, frontend, and database engineering.
The article presents five design patterns—Logits Masking, Grammar, Style Transfer, Reverse Neutralization, and Content Optimization—for steering the output of generative AI models, compares their suitable scenarios, advantages, drawbacks, and anti‑patterns, and provides concrete implementation steps, code snippets, and flowcharts to help developers reliably enforce style, format, and compliance constraints.
The article examines how AI engineering builds on, rather than discards, traditional software engineering principles, using the evolution of AI‑driven search at Alibaba to illustrate architectural upgrades that manage uncertainty, integrate context engineering, and combine classic design patterns with new AI‑specific tools.
This article examines how a rapidly growing Taobao flash‑sale service‑package system suffered from high development costs, duplicated code, and tight coupling, and shows how AI‑assisted domain‑driven design was applied to refactor the architecture, automate code generation, and dramatically improve efficiency, maintainability, and extensibility.
This article shares the author's practical experience in using AI to tackle complex repetitive tasks, presenting a reusable methodology that abstracts human actions into a perception‑decision‑execution loop, and demonstrates three automation modes—tool assistant, workflow, and intelligent agent—through real‑world cases in data governance, ticket handling, and baseline operations.
The article examines the difficulties of traditional front‑end component reuse, proposes a spec‑driven AI collaboration model that shifts from code reuse to specification reuse, and demonstrates the approach with a detailed Bottom component case study, including design principles, architecture, code snippets, and practical benefits.
This article walks through a real‑world slow‑SQL case on a massive e‑commerce order table, explains B+Tree index structures, index height estimation, index push‑down, sorting strategies, EXPLAIN and Query Profiler usage, and provides a step‑by‑step SOP for safe index changes and validation.
This article details Tmall's technology team's deep AI‑driven testing practice, outlining industry challenges, the need for intelligent test case generation, and a comprehensive strategy that combines prompt engineering, RAG‑based knowledge bases, and platform integration to boost coverage, reduce manual effort, and accelerate release cycles.
