Backend tech guide and AI engineering practice covering fundamentals, databases, distributed systems, high concurrency, system design, plus AI agents and large-model engineering.
The author, a heavy user of AI agents for daily code refactoring, compares the expensive Opus 4.6 with the budget‑friendly MiniMax M2.5, showing how a mixed‑model strategy cuts costs dramatically while maintaining speed and quality across two full‑stack development case studies.
This article explains why ThreadLocal values are not automatically transferred in asynchronous or thread‑pool contexts, compares JDK's InheritableThreadLocal with Alibaba's TransmittableThreadLocal (TTL), and shows how TTL captures, replays, and restores context safely with code examples and diagrams.
The author explains why state-owned enterprises are not always stable, why their low‑tech projects hinder interview performance, and offers concrete steps—such as adding Redis caching, multithreading, and using the STAR method—to turn a modest Java background into compelling interview material.
During a Spring‑based interview platform project, the author discovered four typical bugs introduced by Claude Code—transactional self‑invocation loss, AI‑generated NullPointerExceptions, async task failures after entity deletion, and Redis Stream message buildup—and explains the root causes and concrete remediation steps.
IntelliJ IDEA 2025.3.1 introduced severe Maven project initialization memory leaks and WSL2 file‑system configuration resets, causing IDE freezes and OOM crashes, but JetBrains addressed these issues in the 2025.3.1.1 update and provides temporary workarounds such as cache cleanup, icon disabling, and registry tweaks.
After testing MiniMax M2.1 on a full‑stack e‑commerce order‑management task, the author finds the model correctly implements DDD layers, transaction handling, custom exceptions, and even generates a polished cyber‑punk UI, while its Java‑to‑Go code respects each language’s concurrency model and scores over 88 on the VIBE benchmark.
The author, a non‑elite undergraduate and a modest 211 master’s graduate, shares a step‑by‑step 80‑day crash‑course that turned zero Java experience into multiple offers from major tech firms, emphasizing fundamental understanding, AI‑assisted learning, and thoughtful project trade‑offs.
The article details PDD’s 2023 Shanghai backend salary packages, intense 11‑11‑6 work schedule, Temu’s rapid growth, a comparison favoring Alibaba SSP offers, and provides a comprehensive breakdown of PDD’s interview style, typical coding questions, and high‑frequency technical topics.
The author integrates the newly released GLM‑4.7 model into Claude Code, runs three real‑world coding scenarios—including a React dashboard, a FastAPI authentication service, and a refined landing page—and finds that its stability, reasoning, and output quality closely match Claude Sonnet 4.5, positioning GLM‑4.7 as a strong open‑source alternative.
IntelliJ IDEA 2025.3.1 quickly follows the 2025.3 major release, fixing over 200 issues, reinstating the classic Query Console, addressing WSL‑related Java debugging problems, stabilizing Gradle/Maven sync for large multi‑module projects, improving Spring tooling, Java debugging, Kotlin‑MongoDB support, and correcting terminal and TypeScript bugs.
